This document outlines Ritu Khare's dissertation presentation on mapping user-designed forms to relational databases. The presentation covers the motivation for the research, problems in existing approaches, and proposed solutions. Specifically, the presentation discusses understanding form semantics, discovering correspondences between forms and databases, and integrating forms into databases while maintaining properties like completeness, correctness, and normalization. The goal is to evolve databases from user forms with minimal user intervention.
The Statement of Conjunctive and Disjunctive Queries in Object Oriented Datab...Editor IJCATR
Entrance of object orienting concept in database caused the relation database gradually to replace with object oriented
database in various fields. On the other hand for solving the problem of real world uncertain data, several methods were presented.
One of these methods for modeling database is an approach wich couples object-oriented database modeling with fuzzy logic. Many
queries that users to pose are expressed on the basis of linguistic variables. Because of classical databases are not able to support these
variables, leads to fuzzy approaches are considered. We investigate databases queries in this study both simple and complex ways. In
the complex way, we use conjunctive and disjunctive queries. In the following, we use the XML labels to express inqueries into fuzzy.
We can also communicate with other sections of software by entering into XML world as the most reliable opportunity. Also we want
to correct conjunctive and disjunctive queries related to fuzzy object oriented database using the concept of dependency measure and
weight, and weight be assigned to different phrases of a query based on user emphasis. The other aim of this research is mapping fuzzy
queries to fuzzy-XML. It is expected to be simple implement of query, and output of execution of queries be greatly closer to users'
needs and fulfill her expect. The results show that the proposed method explains the possible conjunctive and disjunctive queries the
database in the form of Fuzzy-XML.
IRJET- Semantic Retrieval of Trademarks based on Text and Images Conceptu...IRJET Journal
The document proposes a novel Weakly-supervised Deep Matrix Factorization (WDMF) algorithm for social image tag refinement, assignment and retrieval. WDMF uncovers latent image and tag representations in a latent subspace by exploiting weakly supervised tagging information, visual structure and semantic structure. It can handle noisy, incomplete or subjective tags and noisy or redundant visual features. An optimization problem with a well-defined objective function is formulated and solved using gradient descent with curvilinear search. Extensive experiments on two real-world social image databases demonstrate the effectiveness of the approach.
Semantic Conflicts and Solutions in Integration of Fuzzy Relational Databasesijsrd.com
This document discusses semantic conflicts that can occur when integrating fuzzy relational databases and proposes a methodology for resolving these conflicts. It identifies five new types of conflicts specific to fuzzy databases: membership degree conflicts, inconsistent attribute values, missing attributes, missing fuzzy attribute values, and attribute domain conflicts. The methodology resolves these conflicts in a specific order to minimize the time needed for integration. It aims to resolve fuzzy database conflicts within the context of resolving other general integration conflicts.
This document proposes a method for annotating faces in images without supervision by mining the web. The method has two steps:
1. It ranks faces retrieved from a text-based search engine based on a local density score, which measures how similar a face is to its neighbors. Faces with higher scores are considered more relevant.
2. It then improves this ranking by modeling it as a classification problem, where faces are classified as the queried person or not. Multiple weak classifiers are trained on different subsets and combined via bagging to reduce noise from the unlabeled data. The faces are then re-ranked based on the classifier probabilities. Repeating this process iteratively improves the ranking.
Software Design Patterns - An OverviewFarwa Ansari
The document summarizes different types of software design patterns. It discusses creational patterns, which deal with object creation mechanisms and increase flexibility. Examples include abstract factory, builder, factory method, prototype and singleton patterns. Structural patterns provide relationships between classes and objects, such as adapter, bridge, composite, and decorator. Behavioral patterns define communication between classes, for example chain of responsibility, command, interpreter, and observer. Design patterns are reusable solutions to common programming problems and increase flexibility and reuse in software design.
This document provides an introduction and 18 problems related to linked lists of increasing difficulty. It begins with a review of basic linked list code techniques, such as iterating through a list and adding/removing nodes. The problems cover a wide range of skills with pointers and complex algorithms. Though linked lists are not commonly used today, they are excellent for developing skills with complex pointer-based data structures and algorithms. The document provides solutions to all problems to help readers practice and learn.
The document discusses object-oriented programming and its evolution from structured procedural programming. It describes some of the key disadvantages of structured procedural programming, including a lack of code reusability, extensibility and maintainability. Object-oriented programming aims to address these issues by emphasizing data over procedures and dividing programs into reusable objects that encapsulate both data and functions. The document outlines several fundamental elements of object-oriented programming, including objects, classes, encapsulation, inheritance, polymorphism and dynamic binding.
The Statement of Conjunctive and Disjunctive Queries in Object Oriented Datab...Editor IJCATR
Entrance of object orienting concept in database caused the relation database gradually to replace with object oriented
database in various fields. On the other hand for solving the problem of real world uncertain data, several methods were presented.
One of these methods for modeling database is an approach wich couples object-oriented database modeling with fuzzy logic. Many
queries that users to pose are expressed on the basis of linguistic variables. Because of classical databases are not able to support these
variables, leads to fuzzy approaches are considered. We investigate databases queries in this study both simple and complex ways. In
the complex way, we use conjunctive and disjunctive queries. In the following, we use the XML labels to express inqueries into fuzzy.
We can also communicate with other sections of software by entering into XML world as the most reliable opportunity. Also we want
to correct conjunctive and disjunctive queries related to fuzzy object oriented database using the concept of dependency measure and
weight, and weight be assigned to different phrases of a query based on user emphasis. The other aim of this research is mapping fuzzy
queries to fuzzy-XML. It is expected to be simple implement of query, and output of execution of queries be greatly closer to users'
needs and fulfill her expect. The results show that the proposed method explains the possible conjunctive and disjunctive queries the
database in the form of Fuzzy-XML.
IRJET- Semantic Retrieval of Trademarks based on Text and Images Conceptu...IRJET Journal
The document proposes a novel Weakly-supervised Deep Matrix Factorization (WDMF) algorithm for social image tag refinement, assignment and retrieval. WDMF uncovers latent image and tag representations in a latent subspace by exploiting weakly supervised tagging information, visual structure and semantic structure. It can handle noisy, incomplete or subjective tags and noisy or redundant visual features. An optimization problem with a well-defined objective function is formulated and solved using gradient descent with curvilinear search. Extensive experiments on two real-world social image databases demonstrate the effectiveness of the approach.
Semantic Conflicts and Solutions in Integration of Fuzzy Relational Databasesijsrd.com
This document discusses semantic conflicts that can occur when integrating fuzzy relational databases and proposes a methodology for resolving these conflicts. It identifies five new types of conflicts specific to fuzzy databases: membership degree conflicts, inconsistent attribute values, missing attributes, missing fuzzy attribute values, and attribute domain conflicts. The methodology resolves these conflicts in a specific order to minimize the time needed for integration. It aims to resolve fuzzy database conflicts within the context of resolving other general integration conflicts.
This document proposes a method for annotating faces in images without supervision by mining the web. The method has two steps:
1. It ranks faces retrieved from a text-based search engine based on a local density score, which measures how similar a face is to its neighbors. Faces with higher scores are considered more relevant.
2. It then improves this ranking by modeling it as a classification problem, where faces are classified as the queried person or not. Multiple weak classifiers are trained on different subsets and combined via bagging to reduce noise from the unlabeled data. The faces are then re-ranked based on the classifier probabilities. Repeating this process iteratively improves the ranking.
Software Design Patterns - An OverviewFarwa Ansari
The document summarizes different types of software design patterns. It discusses creational patterns, which deal with object creation mechanisms and increase flexibility. Examples include abstract factory, builder, factory method, prototype and singleton patterns. Structural patterns provide relationships between classes and objects, such as adapter, bridge, composite, and decorator. Behavioral patterns define communication between classes, for example chain of responsibility, command, interpreter, and observer. Design patterns are reusable solutions to common programming problems and increase flexibility and reuse in software design.
This document provides an introduction and 18 problems related to linked lists of increasing difficulty. It begins with a review of basic linked list code techniques, such as iterating through a list and adding/removing nodes. The problems cover a wide range of skills with pointers and complex algorithms. Though linked lists are not commonly used today, they are excellent for developing skills with complex pointer-based data structures and algorithms. The document provides solutions to all problems to help readers practice and learn.
The document discusses object-oriented programming and its evolution from structured procedural programming. It describes some of the key disadvantages of structured procedural programming, including a lack of code reusability, extensibility and maintainability. Object-oriented programming aims to address these issues by emphasizing data over procedures and dividing programs into reusable objects that encapsulate both data and functions. The document outlines several fundamental elements of object-oriented programming, including objects, classes, encapsulation, inheritance, polymorphism and dynamic binding.
TEXT SENTIMENTS FOR FORUMS HOTSPOT DETECTIONijistjournal
The user generated content on the web grows rapidly in this emergent information age. The evolutionary changes in technology make use of such information to capture only the user’s essence and finally the useful information are exposed to information seekers. Most of the existing research on text information processing, focuses in the factual domain rather than the opinion domain. In this paper we detect online hotspot forums by computing sentiment analysis for text data available in each forum. This approach analyses the forum text data and computes value for each word of text. The proposed approach combines K-means clustering and Support Vector Machine with PSO (SVM-PSO) classification algorithm that can be used to group the forums into two clusters forming hotspot forums and non-hotspot forums within the current time span. The proposed system accuracy is compared with the other classification algorithms such as Naïve Bayes, Decision tree and SVM. The experiment helps to identify that K-means and SVM-PSO together achieve highly consistent results.
This document discusses fuzzy querying of relational databases. It begins by introducing fuzzy relational database management systems (FRDBMS), which allow imprecise queries using fuzzy logic. It then presents the basic concepts of fuzzy logic and membership functions. The architecture of an FRDBMS is described, including how it translates fuzzy queries into equivalent SQL queries. An example student database is used to demonstrate a fuzzy query for "poor performers" and how it returns more graded results than an exact SQL query. The document concludes that FRDBMS improves the expressiveness of queries over traditional databases.
Feature selection, optimization and clustering strategies of text documentsIJECEIAES
Clustering is one of the most researched areas of data mining applications in the contemporary literature. The need for efficient clustering is observed across wide sectors including consumer segmentation, categorization, shared filtering, document management, and indexing. The research of clustering task is to be performed prior to its adaptation in the text environment. Conventional approaches typically emphasized on the quantitative information where the selected features are numbers. Efforts also have been put forward for achieving efficient clustering in the context of categorical information where the selected features can assume nominal values. This manuscript presents an in-depth analysis of challenges of clustering in the text environment. Further, this paper also details prominent models proposed for clustering along with the pros and cons of each model. In addition, it also focuses on various latest developments in the clustering task in the social network and associated environments.
FAST FUZZY FEATURE CLUSTERING FOR TEXT CLASSIFICATION cscpconf
Feature clustering is a powerful method to reduce the dimensionality of feature vectors for text
classification. In this paper, Fast Fuzzy Feature clustering for text classification is proposed. It
is based on the framework proposed by Jung-Yi Jiang, Ren-Jia Liou and Shie-Jue Lee in 2011.
The word in the feature vector of the document is grouped into the cluster in less iteration. The
numbers of iterations required to obtain cluster centers are reduced by transforming clusters
center dimension from n-dimension to 2-dimension. Principle Component Analysis with slit
change is used for dimension reduction. Experimental results show that, this method improve
the performance by significantly reducing the number of iterations required to obtain the cluster
center. The same is being verified with three benchmark datasets
This document describes linking a medical vocabulary to a clinical data model using Abstract Syntax Notation 1 (ASN.1). It discusses:
1) Creating a clinical data model in ASN.1 with simple primitive data types that are combined into more complex data types in a layered approach, with the highest level being clinical messages.
2) Incorporating vocabulary into the model using a BaseCoded data type that allows vocabulary concepts and relationships to be referenced using standard ASN.1 notation.
3) Finding ASN.1 to be a flexible and robust notation for representing the clinical data model, with benefits like built-in encoding rules, available tools, and ability to define and implement an electronic medical
Data structures and algorithms alfred v. aho, john e. hopcroft and jeffrey ...Chethan Nt
This document provides an overview of data structures and algorithms, including:
- Problem formulation and modeling problems mathematically before designing algorithms.
- Defining algorithms as finite sequences of instructions that terminate in finite time.
- Using an example of designing a traffic light algorithm to illustrate the problem-solving process. This involves modeling the problem as a graph coloring problem and discussing approaches to solving it optimally or heuristically.
Semantic Based Model for Text Document Clustering with IdiomsWaqas Tariq
Text document clustering has become an increasingly important problem in recent years because of the tremendous amount of unstructured data which is available in various forms in online forums such as the web, social networks, and other information networks. Clustering is a very powerful data mining technique to organize the large amount of information on the web. Traditionally, document clustering methods do not consider the semantic structure of the document. This paper addresses the task of developing an effective and efficient method to improve the semantic structure of the text documents. A method has been developed that performs the following: tag the documents for parsing, replacement of idioms with their original meaning, semantic weights calculation for document words and apply semantic grammar. The similarity measure is obtained between the documents and then the documents are clustered using Hierarchical clustering algorithm. The method adopted in this work is evaluated on different data sets with standard performance measures and the effectiveness of the method to develop in meaningful clusters has been proved.
Improving modularity and reusability are two key objectives in object-oriented programming. These
objectives are achieved by applying several key concepts, such as data encapsulation and inheritance. A
class in an object-oriented system is the basic unit of design. Assessing the quality of an object-oriented
class may require flattening the class and representing it as it really is, including all accessible inherited
class members. Thus, class flattening helps in exploring the impact of inheritance on improving code
quality. This paper explains how to flatten Java classes and discusses the relationship between class
flattening and some applications of interest to software practitioners, such as refactoring and indicating
external quality attributes.
The document discusses handling corporate data and information management. It covers objectives like data resource management, DBMS, data warehousing, and data mining. It describes the sources and types of information an organization uses, both formal sources like internal records and external reports, as well as informal sources like conversations. It also discusses database management systems, data models, data warehousing, and data mining - how organizations use these approaches to collect, process, analyze and extract useful information from their data.
The document describes Phenoflow, a clinical natural language processing tool for defining electronic health record (EHR)-based phenotypes. It discusses the need for clear and reusable phenotype definitions that connect a definition to its computable form. The document proposes Phenoflow's workflow-based phenotype model which separates phenotype logic from implementation. This model structure connects definitions to multiple computational implementations while prioritizing clarity and flexibility.
ICS Part 2 Computer Science Short NotesAbdul Haseeb
The document provides an overview of basic data concepts including data, data capturing, data manipulation, information, fields, records, files, databases, data integrity, and database management systems. It defines key terms and provides examples. The three main types of files are described as master files, backup files, and transaction files. Database components are listed as data, hardware, software, and personnel.
Processing vietnamese news titles to answer relative questions in vnewsqa ict...ijnlc
This paper introduces two important elements of our VNewsQA/ICT system: its semantic models
of simple Vietnamese sentences and its semantic processing mechanism. The VNewsQA/ICT is a
Vietnamese based Question Answering system which has the ability to gather information from
some Vietnamese news title forms on the ICTnews websites (http://www.ictnews.vn), instead of
using a database or a knowledge base, to answer the related Vietnamese questions in the domain
of information and communications technology.
A&D - Object Oriented Analysis using UMLvinay arora
This document discusses object oriented analysis using UML. It defines key concepts like objects, classes, attributes, behaviors, generalization/specialization, aggregation, and relationships. It also describes UML diagrams including use case diagrams, class diagrams, sequence diagrams, and activity diagrams. Finally, it outlines the process of object modeling including identifying objects and classes, organizing relationships, and constructing class diagrams.
This presentation discusses molecular similarity searching methods for drug discovery. It begins with an introduction to cheminformatics and the principle that structurally similar molecules tend to have similar biological properties. The document then covers molecular representations, methods for calculating similarity coefficients between molecules, and a probabilistic model for similarity searching. It proposes a contribution called the Molecular Dynamic Clustering method that uses molecular dynamics simulations and classification algorithms to better assess molecular similarity.
This document summarizes a study on the remote mentoring program called MAGIC (Get More Active Girls in Computing). MAGIC aims to increase female participation in STEM fields through one-on-one remote mentoring matches between young girls and women professionals in technology careers. The study analyzed data from MAGIC's first 5 years, finding that remote mentoring increased STEM skills, self-confidence, and career awareness for many mentees. However, challenges included maintaining mentor and mentee commitment over time. The study concludes that remote mentoring shows promise for improving gender diversity in STEM, but more data is needed to better understand impacts and how to address challenges.
This study investigated error control practices among gynecologic physicians using electronic medical records (EMRs). The researchers conducted a user study with 20 gynecologic physicians to understand how they detect errors in fabricated patient notes containing intentionally introduced errors. On average, physicians detected 49% of major errors and 36% of minor errors. The study identified common error detection triggers and derived guidelines for developing computational error detection algorithms, including comparing information across sections and identifying discrepancies. The algorithms should incorporate clinical knowledge from guidelines as well as natural language processing and controlled vocabularies. This research provides initial insights into physician error detection abilities to help design more effective automated error control for EMRs.
This document describes efforts to make a suite of text mining tools developed at the National Center for Biotechnology Information (NCBI) compatible with the BioC format. The tools identify various biomedical concepts like diseases, genes, species, and chemicals in text. To enable interoperability between these tools, their data formats were modified to support the BioC XML format for text documents and annotations. This involved creating a common key file and updating input/output. The tools can now take BioC formatted data as input and produce BioC formatted annotations as output, allowing the tools to be more easily combined into text mining applications.
TEXT SENTIMENTS FOR FORUMS HOTSPOT DETECTIONijistjournal
The user generated content on the web grows rapidly in this emergent information age. The evolutionary changes in technology make use of such information to capture only the user’s essence and finally the useful information are exposed to information seekers. Most of the existing research on text information processing, focuses in the factual domain rather than the opinion domain. In this paper we detect online hotspot forums by computing sentiment analysis for text data available in each forum. This approach analyses the forum text data and computes value for each word of text. The proposed approach combines K-means clustering and Support Vector Machine with PSO (SVM-PSO) classification algorithm that can be used to group the forums into two clusters forming hotspot forums and non-hotspot forums within the current time span. The proposed system accuracy is compared with the other classification algorithms such as Naïve Bayes, Decision tree and SVM. The experiment helps to identify that K-means and SVM-PSO together achieve highly consistent results.
This document discusses fuzzy querying of relational databases. It begins by introducing fuzzy relational database management systems (FRDBMS), which allow imprecise queries using fuzzy logic. It then presents the basic concepts of fuzzy logic and membership functions. The architecture of an FRDBMS is described, including how it translates fuzzy queries into equivalent SQL queries. An example student database is used to demonstrate a fuzzy query for "poor performers" and how it returns more graded results than an exact SQL query. The document concludes that FRDBMS improves the expressiveness of queries over traditional databases.
Feature selection, optimization and clustering strategies of text documentsIJECEIAES
Clustering is one of the most researched areas of data mining applications in the contemporary literature. The need for efficient clustering is observed across wide sectors including consumer segmentation, categorization, shared filtering, document management, and indexing. The research of clustering task is to be performed prior to its adaptation in the text environment. Conventional approaches typically emphasized on the quantitative information where the selected features are numbers. Efforts also have been put forward for achieving efficient clustering in the context of categorical information where the selected features can assume nominal values. This manuscript presents an in-depth analysis of challenges of clustering in the text environment. Further, this paper also details prominent models proposed for clustering along with the pros and cons of each model. In addition, it also focuses on various latest developments in the clustering task in the social network and associated environments.
FAST FUZZY FEATURE CLUSTERING FOR TEXT CLASSIFICATION cscpconf
Feature clustering is a powerful method to reduce the dimensionality of feature vectors for text
classification. In this paper, Fast Fuzzy Feature clustering for text classification is proposed. It
is based on the framework proposed by Jung-Yi Jiang, Ren-Jia Liou and Shie-Jue Lee in 2011.
The word in the feature vector of the document is grouped into the cluster in less iteration. The
numbers of iterations required to obtain cluster centers are reduced by transforming clusters
center dimension from n-dimension to 2-dimension. Principle Component Analysis with slit
change is used for dimension reduction. Experimental results show that, this method improve
the performance by significantly reducing the number of iterations required to obtain the cluster
center. The same is being verified with three benchmark datasets
This document describes linking a medical vocabulary to a clinical data model using Abstract Syntax Notation 1 (ASN.1). It discusses:
1) Creating a clinical data model in ASN.1 with simple primitive data types that are combined into more complex data types in a layered approach, with the highest level being clinical messages.
2) Incorporating vocabulary into the model using a BaseCoded data type that allows vocabulary concepts and relationships to be referenced using standard ASN.1 notation.
3) Finding ASN.1 to be a flexible and robust notation for representing the clinical data model, with benefits like built-in encoding rules, available tools, and ability to define and implement an electronic medical
Data structures and algorithms alfred v. aho, john e. hopcroft and jeffrey ...Chethan Nt
This document provides an overview of data structures and algorithms, including:
- Problem formulation and modeling problems mathematically before designing algorithms.
- Defining algorithms as finite sequences of instructions that terminate in finite time.
- Using an example of designing a traffic light algorithm to illustrate the problem-solving process. This involves modeling the problem as a graph coloring problem and discussing approaches to solving it optimally or heuristically.
Semantic Based Model for Text Document Clustering with IdiomsWaqas Tariq
Text document clustering has become an increasingly important problem in recent years because of the tremendous amount of unstructured data which is available in various forms in online forums such as the web, social networks, and other information networks. Clustering is a very powerful data mining technique to organize the large amount of information on the web. Traditionally, document clustering methods do not consider the semantic structure of the document. This paper addresses the task of developing an effective and efficient method to improve the semantic structure of the text documents. A method has been developed that performs the following: tag the documents for parsing, replacement of idioms with their original meaning, semantic weights calculation for document words and apply semantic grammar. The similarity measure is obtained between the documents and then the documents are clustered using Hierarchical clustering algorithm. The method adopted in this work is evaluated on different data sets with standard performance measures and the effectiveness of the method to develop in meaningful clusters has been proved.
Improving modularity and reusability are two key objectives in object-oriented programming. These
objectives are achieved by applying several key concepts, such as data encapsulation and inheritance. A
class in an object-oriented system is the basic unit of design. Assessing the quality of an object-oriented
class may require flattening the class and representing it as it really is, including all accessible inherited
class members. Thus, class flattening helps in exploring the impact of inheritance on improving code
quality. This paper explains how to flatten Java classes and discusses the relationship between class
flattening and some applications of interest to software practitioners, such as refactoring and indicating
external quality attributes.
The document discusses handling corporate data and information management. It covers objectives like data resource management, DBMS, data warehousing, and data mining. It describes the sources and types of information an organization uses, both formal sources like internal records and external reports, as well as informal sources like conversations. It also discusses database management systems, data models, data warehousing, and data mining - how organizations use these approaches to collect, process, analyze and extract useful information from their data.
The document describes Phenoflow, a clinical natural language processing tool for defining electronic health record (EHR)-based phenotypes. It discusses the need for clear and reusable phenotype definitions that connect a definition to its computable form. The document proposes Phenoflow's workflow-based phenotype model which separates phenotype logic from implementation. This model structure connects definitions to multiple computational implementations while prioritizing clarity and flexibility.
ICS Part 2 Computer Science Short NotesAbdul Haseeb
The document provides an overview of basic data concepts including data, data capturing, data manipulation, information, fields, records, files, databases, data integrity, and database management systems. It defines key terms and provides examples. The three main types of files are described as master files, backup files, and transaction files. Database components are listed as data, hardware, software, and personnel.
Processing vietnamese news titles to answer relative questions in vnewsqa ict...ijnlc
This paper introduces two important elements of our VNewsQA/ICT system: its semantic models
of simple Vietnamese sentences and its semantic processing mechanism. The VNewsQA/ICT is a
Vietnamese based Question Answering system which has the ability to gather information from
some Vietnamese news title forms on the ICTnews websites (http://www.ictnews.vn), instead of
using a database or a knowledge base, to answer the related Vietnamese questions in the domain
of information and communications technology.
A&D - Object Oriented Analysis using UMLvinay arora
This document discusses object oriented analysis using UML. It defines key concepts like objects, classes, attributes, behaviors, generalization/specialization, aggregation, and relationships. It also describes UML diagrams including use case diagrams, class diagrams, sequence diagrams, and activity diagrams. Finally, it outlines the process of object modeling including identifying objects and classes, organizing relationships, and constructing class diagrams.
This presentation discusses molecular similarity searching methods for drug discovery. It begins with an introduction to cheminformatics and the principle that structurally similar molecules tend to have similar biological properties. The document then covers molecular representations, methods for calculating similarity coefficients between molecules, and a probabilistic model for similarity searching. It proposes a contribution called the Molecular Dynamic Clustering method that uses molecular dynamics simulations and classification algorithms to better assess molecular similarity.
This document summarizes a study on the remote mentoring program called MAGIC (Get More Active Girls in Computing). MAGIC aims to increase female participation in STEM fields through one-on-one remote mentoring matches between young girls and women professionals in technology careers. The study analyzed data from MAGIC's first 5 years, finding that remote mentoring increased STEM skills, self-confidence, and career awareness for many mentees. However, challenges included maintaining mentor and mentee commitment over time. The study concludes that remote mentoring shows promise for improving gender diversity in STEM, but more data is needed to better understand impacts and how to address challenges.
This study investigated error control practices among gynecologic physicians using electronic medical records (EMRs). The researchers conducted a user study with 20 gynecologic physicians to understand how they detect errors in fabricated patient notes containing intentionally introduced errors. On average, physicians detected 49% of major errors and 36% of minor errors. The study identified common error detection triggers and derived guidelines for developing computational error detection algorithms, including comparing information across sections and identifying discrepancies. The algorithms should incorporate clinical knowledge from guidelines as well as natural language processing and controlled vocabularies. This research provides initial insights into physician error detection abilities to help design more effective automated error control for EMRs.
This document describes efforts to make a suite of text mining tools developed at the National Center for Biotechnology Information (NCBI) compatible with the BioC format. The tools identify various biomedical concepts like diseases, genes, species, and chemicals in text. To enable interoperability between these tools, their data formats were modified to support the BioC XML format for text documents and annotations. This involved creating a common key file and updating input/output. The tools can now take BioC formatted data as input and produce BioC formatted annotations as output, allowing the tools to be more easily combined into text mining applications.
BwN Concepts & Solutions For Wb Delegationmindertdevries
This document discusses building safety against flooding through nature-based solutions, or "Building with Nature" (BwN). It provides examples of practical BwN solutions implemented from 2007-2010, including saltmarsh creation, oyster reefs, forest-dike combinations, and hybrid hard-soft structures. The document emphasizes that BwN solutions are generic, practical, cost-effective, fit within legal constraints, and have been realized through partnerships. It highlights the need to integrate ecosystem functions and dynamics into flood protection through a green adaptation approach.
The document provides information about the OWASP AppSecUSA conference to be held in Austin, Texas from October 23-26, 2012. It discusses that OWASP is an open, volunteer-based organization focused on application security. The conference location of Austin is noted for its music, festivals, nature, creativity and technology. The document lists some of the one-day and two-day training sessions that will be offered, covering topics like cryptanalysis, secure coding, SQL injection, mobile security and web application testing.
Mike Thelwall is a professor known for his research in the field of webometrics. He received his PhD in mathematics and leads the Statistical Cybermetrics Research Group. Webometrics involves the quantitative analysis of web phenomena such as link analysis, search engine evaluation, and web citation analysis. Thelwall's research has explored using webometrics to study the dissemination of scholarly research and evaluate universities. He has emphasized the need for conceptual frameworks and methodologies to interpret webometrics results and address challenges like the size and changing nature of the web.
Clinicians rely on health information technologies (HITs) for clinical data collection, but current HITs are inflexible and inconsistent with clinicians' needs. The researchers propose a flexible electronic health record (fEHR) system to allow clinicians to easily modify the system based on their changing data collection needs. The fEHR uses a form-based interface for clinicians to design forms, generates a corresponding form tree structure, and designs a high-quality database from the tree. A user study with 5 nurses found they could effectively replicate needs in the system and their efficiency and understanding improved over two rounds of tasks of increasing complexity. The researchers conclude the fEHR has potential to reduce HIT problems and that the database design
10 Nonprofit Success Stories Using LinkedIn - Stanford Bus 109 Lecture 1/21/14Box
This lecture included 10 stories. The stories were about nine nonprofits and one social enterprise that are using LinkedIn to meet their important missions. Building relationships strategically, lifting brand, expanding their community, recruiting board members and volunteers, recruiting staff, raising money, etc etc.
Security Code Reviews. Does Your Code Need an Open Heart Surgery and The 6 Po...Sherif Koussa
The document discusses a 6-point strategy for conducting security code reviews to identify and remediate vulnerabilities in applications. It emphasizes focusing code reviews on high priority issues like authentication, authorization, encryption and input validation. It recommends starting with the OWASP Top 10 issues, using automated tools for initial analysis, and conducting manual reviews of sensitive code. Thorough reporting of findings with recommendations is presented as the final step.
Here are the key things to report:
- Vulnerability type
- Location (file, line number)
- Short description
- Impact
- Recommendation
Provide enough context for developers to understand and fix.
Prioritize vulnerabilities by severity and risk.
29 Softwar S cur
REPORTING
SQL Injection:
Location: \source\ACMEPortal\updateinfo.aspx.cs:
Description: The code below is build dynamic sql statement using
• Weakness Metadata unvalidated data (i.e. name) which can lead to SQL Injection
- High severity
- Data exposure and system access
- Recommend using parameterized
Program Comprehension - An Evaluation of the Strategies of Sorting, Filtering...ICSM 2011
Paper: An Evaluation of the Strategies of Sorting, Filtering, and Grouping API Methods for Code Completion
Authors: Daqing Hou and Dave Pletcher
Session: Research Track Session 8 -Program Comprehension
This document provides an overview of integrated digital marketing and marketing communications at the University of Calgary. It discusses how traditional marketing is being replaced by new approaches that are integrated, measurable, media agnostic, and user-focused. Various digital marketing tactics are mentioned such as web development, email, mobile, SEO, gamification, and social media. The importance of integration and evaluating the full digital marketing strategy is emphasized. Suggested readings on digital marketing strategy, social media, user experience design, and form design are also provided.
This document summarizes a presentation about simplifying secure code reviews. It discusses defining an effective security code review process, including reconnaissance, threat modeling, automation, manual review, confirmation, and reporting. It also discusses using the OWASP Top 10 list to focus code reviews, and defining trust boundaries to identify areas of code to review for specific vulnerabilities. The goal is to introduce a simplified process that can help development teams integrate security code reviews into their workflow.
Student POST Database processing models showcase the logical s.docxorlandov3
Student POST:
Database processing models showcase the logical structure of a database. The most commonly used model is the Relational database model that sorts the data in a table that consist of rows and columns. The column holds the attributes of the entity and rows hold the data of a particular instance of the entities. The major advantage of the Relational model is that it is in the table form and hence easier for users to understand, manage and work with the data. And, with the primary key and foreign key concepts, the data can be uniquely identified, stored in different entities and retrieved effectively with the relationships. The other advantage is that with the relational model, SQL language can be used to work with the data which is simple to understand and most widely used. The disadvantage of relational model could be the financial cost that is higher in comparison as the specific software needs to be in place and the regular maintenance needs to be performed that requires highly skilled manpower. And, the complexity of the database can be further increased when the volume of the data keep in increasing. Also, there is the limitation in the length of fields stored as different data types in relational model (Joseph & Paul, 2009).
The other processing model is the Object-oriented model that depicts database as the collection of objects. The advantage of this model is that it is compatible to work with complex data sets with the use of Object IDs and object-oriented programming. It’s disadvantage is that object databases are not commonly used and the complexity can hamper the performance of database. The other type of database model is the Entity-Relationship model which is mostly used for the conceptual design of database. It pictures the entities, several attributes that falls within the domain of that entity and the cardinality of relationship between them. It’s advantage is that the E-R diagram is easily understandable by the users at the first glance and thus can effectively work with the data in no time and can point out the discrepancies in the data. The other advantage is that it can be easily converted to other models if required by the business. The disadvantage of Entity-Relationship is that the industry standard notations for the diagram is not defined and thus can create confusion to the users. This model is only suitable for high-level database design (S.J.D.,2020).
2Nd Student POST :
Database models or commonly referred to as schemas help represent the structure of a database and its format which is run by a DBMS. Database model uses vary depending on user specifications.
Types of database models
1.
Network model
This network model uses a structure similar to that of a hierarchical model. The model permits multiple parents, which is a tree-like structure model. This model emphasizes two basic concepts; records and sets. Records hold file hierarchy and sets define the many-to-many relationship .
Information residing in relational databases and delimited file systems are inadequate for reuse and sharing over the web. These file systems do not adhere to commonly set principles for maintaining data harmony. Due to these reasons, the resources have been suffering from lack of uniformity, heterogeneity as well as redundancy throughout the web. Ontologies have been widely used for solving such type of problems, as they help in extracting knowledge out of any information system. In this article, we focus on extracting concepts and their relations from a set of CSV files. These files are served as individual concepts and grouped into a particular domain, called the domain ontology. Furthermore, this domain ontology is used for capturing CSV data and represented in RDF format retaining links among files or concepts. Datatype and object properties are automatically detected from header fields. This reduces the task of user involvement in generating mapping files. The detail analysis has been performed on Baseball tabular data and the result shows a rich set of semantic information.
Metadata and Cooperative Knowledge ManagementRalf Klamma
This document discusses cooperative knowledge management and its implications for metadata and conceptual modeling. It argues that current approaches like UML and ERP systems do not fully address the "culture facet" of knowledge work practices. Three relevant theories are reviewed: 1) a cultural science theory that views knowledge creation as cultural discourse influenced by changing media, 2) an organizational behavior theory that describes extracting, manipulating, and applying knowledge to practice, and 3) an engineering theory emphasizing refining knowledge from failures through scenario management. The document advocates for additional research on metadata management and conceptual modeling to better support cooperative knowledge work practices.
USING ONTOLOGIES TO OVERCOMING DRAWBACKS OF DATABASES AND VICE VERSA: A SURVEYcseij
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The document discusses normal forms in database design and compares the Boyce-Codd normal form (BCNF) to third and fourth normal forms. It also covers semantic data modeling, object-oriented databases, and the differences between distributed and centralized databases. Specifically, it explains that BCNF extends third normal form by requiring that every determinant be a candidate key. It also notes that distributed databases allow data to be stored across multiple physical locations for improved performance and availability compared to centralized databases which store all data in one place.
International Journal of Computational Engineering Research(IJCER)ijceronline
This document summarizes a research paper on reengineering relational databases to object-oriented databases. It discusses developing an integrated environment that maps a relational schema to an object-oriented schema without modifying the existing relational schema. The proposed system architecture has two major components - one for mapping the relational schema to an object-oriented schema, and another for mapping relational data to objects. The schema mapping process is two-phased - the first phase transforms the relational schema, and the second phase extracts object-oriented structures. The system aims to allow existing applications and data in a relational database to be accessible from object-oriented programs.
Knowledge Graph and Similarity Based Retrieval Method for Query Answering SystemIRJET Journal
This document proposes a knowledge graph and question answering system to extract and analyze information from large volumes of unstructured data like annual reports. It discusses using natural language processing techniques like named entity recognition with spaCy and dependency parsing to extract entity-relation pairs from text and construct a knowledge graph. For question answering, it analyzes user queries with similar NLP approaches and then matches query triplets to the knowledge graph to retrieve answers, combining information retrieval and trained classifiers. The proposed system aims to provide faster understanding and analysis of complex, unstructured data for professionals.
This document provides a listing and brief descriptions of working papers from 2000. It includes 12 papers with titles and short 1-2 paragraph summaries of each paper's topic or focus. The papers cover a range of topics related to text mining, machine learning, data compression, knowledge discovery, and user interfaces for developing classifiers.
This document provides summaries of 12 working papers from 2000. The summaries are:
1. The paper discusses using compression models to identify acronyms in text.
2. The paper examines using compression models for text categorization to assign texts to predefined categories.
3. The paper is reserved for Sally Jo.
4. The paper explores letting users build classifiers through interactive machine learning.
That's a concise 3 sentence summary of the document that highlights the key information about 4 of the 12 working papers it describes.
This document provides a listing and brief descriptions of working papers from 2000. It includes 12 papers with titles and short 1-2 paragraph summaries of each paper's topic or focus. The papers cover a range of topics related to text mining, machine learning, data compression, knowledge discovery, and user interfaces for developing classifiers.
This document discusses using hidden Markov models to automatically discover the structure of clinical forms and annotate them with medical terminology. It presents a two-layer hidden Markov model approach to first assign tags like category and field to form elements, and then group related elements to identify form segments. The method was tested on 52 clinical forms and achieved over 95% accuracy in extracting the underlying structure of the forms in the form of trees. The ability to automatically understand form structure and annotate forms could enable more flexible design of electronic health records.
An approach for transforming of relational databases to owl ontologyIJwest
Rapid growth of documents, web pages, and other types of text content is a huge challenge for the modern content management systems. One of the problems in the areas of information storage and retrieval is the lacking of semantic data. Ontologies can present knowledge in sharable and repeatedly usable manner and provide an effective way to reduce the data volume overhead by encoding the structure of a particular domain. Metadata in relational databases can be used to extract ontology from database in a special domain. According to solve the problem of sharing and reusing of data, approaches based on transforming relational database to ontology are proposed. In this paper we propose a method for automatic ontology construction based on relational database. Mining and obtaining further components from relational database leads to obtain knowledge with high semantic power and more expressiveness. Triggers are one of the database components which could be transformed to the ontology model and increase the amount of power and expressiveness of knowledge by presenting part of the knowledge dynamically.
Towards Ontology Development Based on Relational Databaseijbuiiir1
Ontology is defined as the formal explicit specification of a shared conceptualization. It has been widely used in almost all fields especially artificial intelligence, data mining, and semantic web etc. It is constructed using various set of resources. Now it has become a very important task to improve the efficiency of ontology construction. In order to improve the efficiency, need an automated method of building ontology from database resource. Since manual construction is found to be erroneous and not up to the expectation, automatic construction of ontology from database is innovated. Then the construction rules for ontology building from relational data sources are put forward. Finally, ontology for �automated building of ontology from relational data sources� has been implemented
This dissertation proposal outlines a system that allows non-technical users to design and evolve databases by modeling their data needs through customizable forms. The key goals are to provide an easy-to-use interface for form design, and mapping algorithms that translate user-designed forms into high-quality databases. A preliminary evaluation with nurses found the form modeling interface effective and efficient. Mapping experiments successfully translated forms into databases that matched expert-designed standards. Future work includes usability studies varying form and database complexity, and exploring enhancements to mapping and merging algorithms.
CONTEXT-AWARE CLUSTERING USING GLOVE AND K-MEANSijseajournal
ABSTRACT
In this paper we propose a novel method to cluster categorical data while retaining their context. Typically, clustering is performed on numerical data. However it is often useful to cluster categorical data as well, especially when dealing with data in real-world contexts. Several methods exist which can cluster categorical data, but our approach is unique in that we use recent text-processing and machine learning advancements like GloVe and t- SNE to develop a a context-aware clustering approach (using pre-trained
word embeddings). We encode words or categorical data into numerical, context-aware, vectors that we use to cluster the data points using common clustering algorithms like K-means.
The document provides an overview of database management systems (DBMS). It discusses that a DBMS contains organized data about an enterprise. It offers advantages over file systems like avoiding data redundancy and inconsistencies. The document describes database applications, levels of abstraction in a DBMS, the relational data model using tables and SQL, and components of the database engine like storage management, query processing, and transaction management. It also provides a brief history of database systems from the 1950s to modern times.
This document discusses challenges and opportunities for integrating large, heterogeneous biological data sets. It outlines the types of analysis and discovery that could be enabled, such as comparing data across studies. Technical challenges include incompatible identifiers and schemas between data sources. Common solutions attempt standardization but have limitations. The document examines Amazon's approach as a model, with principles like exposing all data through programmatic interfaces. It argues for a "platform" approach and combining data-driven and model-driven analysis to gain new insights. Developing services with end users in mind could help maximize data reuse.
A semantic framework and software design to enable the transparent integratio...Patricia Tavares Boralli
This document proposes a conceptual framework to unify representations of natural systems knowledge. The framework is based on separating the ontological nature of an object of study from the context of its observation. Each object is associated with a concept defined in an ontology and an observation context describing aspects like location and time. Models and data are treated as generic knowledge sources with a semantic type and observation context. This allows flexible integration and calculation of states across heterogeneous sources by composing their observation contexts and resolving semantic compatibility. The framework aims to simplify knowledge representation by abstracting away complexity related to data format and scale.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
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Interested in deploying letter generation automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
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Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
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- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
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- Verstehen des DLAU-Tools und wie man es am besten nutzt
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- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
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Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
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The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
1. A Framework for Mapping
User-designed Forms
to Relational Databases
Dissertation Presentation
November 15 2011
Ritu Khare
COMMITTEE :
Dr. Yuan An (Chair)
Dr. Jiexun Jason Li
Dr. Il-Yeol Song
Dr. Min Song
Dr. Christopher C. Yang
1
2. Presentation Order
1. Motivation
2. Problems
3. Solutions
4. Evaluation
5. Final Remarks
2
4. General Motivation: Database Usability (Sawyer, 1995)
Enable users to SEARCH and Enable users to DESIGN
QUERY databases databases. (Jagadish et al. 2007)
Information Retrieval Form-based DIY and WYSIWYG
Techniques (Liu et al, 2006, Hristidis paradigms
et al., 2003, Catarci, 2000, Jayapandian FormAssembly, ZohoCreator,
and Jagadish, 2006) GoogleForms
Databases still remain unusable from the integration point of view
(Gurses et al., 2009)
4
5. Precise Motivation: Integration of New Needs
New
needs
related to 1) Building of new forms
patient’s
social 2) Integration of new form
habits into back-end
5
6. Research Objective
To develop a mechanism to automatically map
and integrate a user-designed form into
existing structured database.
Assume that a user-designed form is
already acquired
Seek a framework that
merges the semantically matching elements
between forms and databases.
creates new database elements corresponding to
the unmatched form elements.
6
8. A form template represents the
semantic intentions of the designer Problem #1 : Form Understanding
Existing Work
Focus on Search Forms
(Benslimane, et al. 2007, Kaljuviee
et al., 2001)
shorter and simpler than the
data-entry forms. (empirical
finding)
Rules and heuristics
(Zhang et al. 2004, He et al., 2007)
Automatic Extraction of the form semantics not likely to circumvent the
Machine can only read the syntactic patterns ever broadening varieties in
of form elements. A certain layout pattern form topologies
cannot be associated with a semantic
intention.
8
9. Problem#2: Correspondence Discovery
Existing Work
Schema and Ontology
Mapping (Madhavan et al., 2001,
Detect semantically matching Euzenat and Shvaiko, 2005, Rahm and
Bernstein, 2001, An et al. 2005, An et al. 2006)
elements between a form and Mostly semi-automatic
an existing database Not applicable to form to
Challenges database correspondence
discovery
Variety of terms to denote the Heterogeneity between forms and
same concepts. databases
Correspondences are to be used for
Variety of concepts denoted evolving the database; the discovery
process has to keep this requirement
by similar terms into consideration.
Identify and eliminate the
invalid correspondences.
9
10. Problem# 3: Form Integration
Problem#3a: Merging Existing Work
Merging into an existing Form integration (Yang et al.,
database so that the same 2008)
concept is not duplicated and largely manual
the database remains expose the users to the technical
compact. details of the underlying data
Merging increases the model.
potential of having NULL Database integration (Yang et al.
values, i.e., less optimized 2003)
database. provide guidelines.
Judicious Decisions
10
11. Problem# 3: Form Integration
Problem#3b: Birthing
Existing Work:
Extend the database for
Form-based database design
the unmatched form Several methods (Choobineh et al.
1988, Pavicevic et al, 2006, Choobeneh and
elements Venkatraman, 1992, Deklarit, 2008) and
commercial tools (Form assembly,
How to automatically google forms, zohocreator, wufoo)
No empirical evaluation of the
derive the functional resultant databases
dependencies among the Few focus on designing a database
with certain desirable properties,
form elements? e.g., expressiveness (Yang et al, 2008,
Choobineh et al., 1988, Lukovic, et al 2007).
How to translate the These properties do not reflect
complex form patterns? any compliance with the form
semantics and are inadequate
How to evaluate multiple for evaluating the mapping
process.
design alternatives &
pick one?
11
12. Research Questions and System Goals
1. Form Understanding
System Goals:
A model to capture the form 1. To evolve a DB that is high-
semantics quality and optimized as per
Extract this model from a given the form semantics, i.e.,
compliant to the principles
form (Wang and Strong, 1996,
Ramakrishnan and Gehrke, 2002,
2. Correspondence Discovery Silberschatz, et al., 2001, Batini and
Scannapieco, 2006):
Determine semantically
Completeness: All form
equivalent elements b/w form & elements represented in
database database
Incorporate DB evolution Correctness: Form
semantics retained:
requirement during discovery Compactness: Equivalent
process elements merged
3. Form Integration Normalization: 3NF w.r.t.
form’s functional
Resolve merging conflicts while dependencies
maintaining the original form Minimize NULL values in
semantics FKs and Descriptive
attributes
Given a form pattern, derive a
2. To ensure minimalism in the
relational database with required user intervention
12
“desirable” properties
14. Form Representation: Form Tree
The form tree accurately captures the designer's intentions, and
hence the semantic associations among the form elements.
Inspired by hierarchical modeling of forms in existing works
(Dragut et al. 2009, Wu et al. 2009)
14
15. Framework Outline
Form
Understanding Form Tree
and Semantics
Extraction
Correspondenc
Form Tree with e Discovery and
Discovered Validation
Correspondences
Database
Design and Database
Evolution
15
17. Method 1a: Form Tree Generation
I. Tag and 2. Derive Tree
Segment Phase Phase(5 rules)
The approach leverages the probabilistic nature of form design
and develops a 2-layered Hidden Markov Model (HMM)
based artificial designer that has the ability to understand the
semantics of any arbitrarily designed form.
T-HMM: Tagging HMM
S-HMM-Segmentation T-HMM
17
18. Method 1b: Form Term Annotation
Refine semantics by annotating terms
Systematized Nomenclature of Medicine Challenge: Same form term can be
Clinical Terms (SNOMED CT) comprising specified in multiple contexts, i.e.,
360,000 concepts belonging to various semantic categories. The key is to identify
semantic categories. the semantic category for a given term.
We hypothesize that the term context can
ConceptID Description Semantic Category be derived from the structure of the form
tree.
0231832 Respiratory Rate Observable Entity
362508001 Both eyes, entire Body Structure
18
19. Method 1b: Form term annotation
Form Tree
SNOMED CT Choose the
Form Structure Classification best match SNOMED
Term CT
Analyzer Model Semantic concept from
this category Concept
category
SNOMED CT search service
19
20. Method 2: Correspondence Discovery and Validation
Linguistic Exact Concept
Matching Matching
1
2
20
21. Total Heuristics = 4
Method 2: Validation Algorithm
Past Medical X
History History
X
Id HPI Medications SocialHistory
Family
Hx
History of
Meds
X
present
Illness
Oral
Hygiene Appetite
Id Options
radio 1 Good
2 Fair
good poor 3 Poor
Look-up table
21
23. Method 3a: Birthing Algorithm Total Patterns = 12
Principles: High Quality(Complete, Correct, Compact, Normalized) and
Optimization (minimize NULLs)
Traverses the form tree in depth first order
M:1
Tj.ID -> Tj.c
Radiobutton Pattern
Textbox Pattern
Category/subcategory
Pattern Extended RB
Pattern
23
26. Tot. merging scenarios = 8
Method 3b: Merging Algorithm
Compactness Factor(CF): A
Each merger involves a trade-off
configurable value (0,1) that indicates
between compactness and the weightage given to compactness
optimization (min. NULL values)
Null Value Ratio(NVR): A calculated
principles.
value that indicates the potential of
having NULL values in a given table.
New DB Existing DB
NVR = 2/5=0.4
Case a: CF=0.5 Case b: CF=0.3
Final DB
(CF>NVR) (CF<=NVR)
26
More Compact More Optimized
28. System Goals: Principle Compliance & Min. Interventions
Evaluation Goals: Java, Tomcat,
A. How well the system meets the goals? MySQL Server,
yFiles, JSP
B. Impact of framework in accomplishing the goals ?
EM & Viterbi,
cross-
HMM-based tree validation
extraction
SNOMED CT Form Tree
Term Annotation Linguistic
Naïve Bayes Classifier, Similarity
Top-4 classes, SnAPI, =Lucene’s Default
Cross-validation per Corr. Settings
Form Tree with dataset Discovery
Discovered Validation
Correspondences Algorithm
Birthing
Algorithm Database
Merging
28 Algorithm CF=0.7
29. Data
(52 real world forms from 6 medical institutions)
Healthcare : Forms are prevalent, and Information systems are unusable and inflexible.
Dataset Avg. Avg. SNOMED
Terms Inputs CT
Mappability
1 Walk in clinic encounter 32.33 49.33 75.77 %
forms (3 forms) Gold Benchmarks
2 Nursing patient 17.17 33 63.98% 52 Gold Std Trees
admission forms (6 (using a DIY interface that
forms) captures designers’ on-
the-fly semantic decisions)
3 Labor & delivery DB data- 16.14 37.29 58.8 %
entry forms (7 forms) Gold Std Annotations
(4235 form terms were
4 Adult visit encounter 47.83 65.22 56.2% manually studied & 2506
forms (59%) had corr. concept in
SNOMED CT)
(18 forms)
5 Family practice forms 82.61 100.46 59.38% 3 pairs of Gold DBs
(3 datasets were given to
(13 forms) 2 experts. Each expert
6 Child visit encounter 53 67.4 62.21% manually derived the 3
forms databases)
29 (5 forms)
30. Experiment 1: Form Tree
Extraction
97.85% of parent child semantic
associations captured correctly
An average tree with 135 edges
gets generated in 0.08 seconds.
Dataset1 Dataset2 Dataset3 Dataset4 Dataset5 Dataset6
Total Edges 272 362 461 2606 2674 644
Accuracy 95.22% 97.51% 100% 97.58% 98.46% 96.11%
Inaccuracies because of more hierarchical
complexity, i.e., semantic grouping and sub-
grouping.
30
32. Avg time(s)/form
Exp. 2: Form Term Annotation 1.28, 1.77, 2.31,
10.29, 8.12, 3.44
Enhanced all versions by adding
term processing: remove special
character, clinical acronyms
expansion.
Precision only slightly improved
(3-5%)
Recall majorly improved (25%).
Final Precision =0.89, Recall
=0.76
Baseline to Hybrid
Avg. precision Improved by 26%.
Recall no specific pattern
Hybrid to Hybrid++
Avg. Precision improved by 13%
Avg. Recall improved by 17%
Hybrid++: precision 0.86, recall 0.6
Structural knowledge can improve the overall performance.
32 Linguistic Techniques can only impact the recall.
33. Experiment 3: Form to Database Mapping
3a.Linguistic-based 3b. Concept-based 3c. Hybrid
Discovery Discovery Discovery
33
34. Exp 3: Description of evolved databases.
(35 to 450 tables), (Linguistic-based Discovery) (x:element-type
y:# elements)
Mapping Duration
per form:
few ms. to 200s.
34
35. Exp 3: Comparison with Gold Datasets
With Gold 1
With Gold 2 74%(avg.) of the system generated
tables “perfectly match" with the
tables in the gold databases.
Based on the principles of quality
and optimization, the mismatches
could be divided into: Negative and
Positive
System
A Gold DB
Form Pattern Generated DB
Positive
Mismatch
Negative
Mismatch
35
36. Correctness. Completeness,
Exp. 3: Measuring Principle Compliance Normalization, Optimization,
Compactness.
An approx. universal set of merging situations
3a : Linguistic Discovery
DB1 DB2 DB3 DB4 DB5 DB6
> =75% compactness in 4
Linguistic databases.
Discovery
Databases 4, 6: >=20%
rejected due of form features
Concept
Discovery Datasets 4 and 6
Format Diversity: Gender (textbox,
Hybrid radiobuttons - M, F); DOB (single vs.
Discovery multiple textboxes)
Section Scattering
3b: Concept-based 3c: Hybrid
Discovery Discovery
>= 70% compactness in 3 >= 80%
databases. compactness in 4
Datasets 5 & 6: >=33% databases.
undetected
36
38. Results Summary & Implications
Exp3:
Exp1: Form tree Interventions
Form to DB Mapping
generation (6 DBs: 35 to 450 Intervention red. 61%
Accuracy = 0.98
(52 forms) tables, Intervention/form:
0.08s/tree few ms to 200s) ling.:10, con. : 8,
•Supervised Hyb.:13
•Intervention 10/tree for Hybrid approach
cardinality improves scenario Avg. screen rel. =50%
disambiguation identification (19%)
Validation
compactness (13%) Principle Compliance
Algorithm
over pure approaches. 84.5% identical, or
But performs less in Birthing superior to gold DBs
Improve precision terms of interventions & Algorithm
74% compact(hybrid)
(43%) and recall screen relevance. Merging
(29%) over baseline Algorithm
Exp2: Form term
•Tune validation/merging based on form
annotation
Precision= 0.89 features.
(2500 forms)
1 to 11s/form Recall = 0.76 •Birthing algorithm can be refined as per
gold std.
•Sophisticated term
techniques •Interventions & screen relevance can be
•SNOMED CT relationships improved by enhancing validation
38 •Unsupervised learning algorithm
40. Thesis Contributions:
Mapping user-designed form to relational database. (NEW problem)
Form Understanding
New Solution: 2-layered HMM that encodes designers Merging Algorithm
knowledge. First work to apply HMMs on form understanding
Balance b/w compactness &
Highly accurate (98%) and efficient (0.08s per form) optimization
Merged =>70% semantically matching
Form Term Annotation (NEW Problem!) elements in 11/18 cases.
Context-based solution leveraging semantic structure
Key Recommendations
Promising (0.89 precision, 0.76 recall) and efficient (1-11s);
Improves over baseline by 43% in precision and 29% in recall For term annotations, design hybrid
approaches leveraging both linguistics
Correspondence Validation Algorithm and structural semantics.
Heuristic based solution relying on frequent observations For improving database quality, design
approaches leveraging both linguistic
Reduces interventions by avg. 61%. and semantic methods for
correspondence discovery.
Birthing Algorithm Birthing algorithm could be further
Intertwines quality and optimization principles refined in terms of handling radio-button
groups and extended check-boxes to
4 medium (<65 tables) & 2 large (<500 tables)-scale DBs improve database quality.
3 medium-scale DBs intersect(or superior) with gold by 84.5%.
Enhance validation algorithm to further
reduce user interventions and improve
40 screen relevance
41. Limitations – I
Techniques Technique Evaluation
Form Understanding Compare with other
Weak entities, part./card. learning models
constraints. SVM, conditional random
fields, Bayesian networks,
Form Term Annotations CAR
Post coordinated mapping Completeness and
Correspondence Discovery Correctness of Heuristics
Tree design rules, Heuristics
Concatenated matches
for validation and merging,
Merging Algorithm Birthing Form Patterns,
Classification attributes
Detect/eliminate circular
Assumptions
references in database.
Class conditional
independence, Correctness
of most linguistic matching
concept
41 Theoretical Validity of
Birthing Algorithm
42. Limitations - II
Study Experimental Design
Thorough User Studies Map and merge forms from
Can users understand/select
different sources
the right correspondences? Experiments involving both
automatic form tree extraction
Domain Expert Annotator
and term annotation methods.
Large Scale of Databases
Result Evaluation, Gold DB
Limited Time
Implementation
Experimentation
42
43. Future Directions
Electronic Health Record General
Can Clinicians
Turn into an API
Design Forms,
Understand/Identify Amazon SimpleDB
Correspondences
Google Datastore.
Does this framework improve
Data Quality, Patient Diagnosis Leveraging More Form-Related
Legal Perspective Information
HIPPA regulations, Proprietary Past Mappings
systems
Usage frequency
Customize for Form Categories
Designer’s/User’s Domain
Encounter, Walk-in, Regular
Visit, Data-entry Expertise
Use other UMLS terminologies Mapping Maintenance and
Record Conflict Resolution
43
44. Related Publications
Exploiting Semantic Structure for Mapping User-specified Form Terms to
SNOMED CT Concepts
Khare R., An Y., Li J., Song I-Y., Hu X. In the proceedings of 2nd International Health
Informatics Symposium (IHI 2012), Jan 28-30, 2012, Miami, FL, USA.
Automatically Mapping and Integrating Multiple Data Entry Forms into a
Database
An Y., Khare R., Song I-Y., Hu X. In the proceedings of 30th International Conference on
Conceptual Modeling (ER 2011), Oct 31-Nov 3, 2011, Brussels, Belgium.
Can Clinicians Create High-Quality Databases? A Study on A Flexible
Electronic Health Record (fEHR) System
Khare R., An Y., Song I-Y., Hu X., In the proceedings of 1st International Health Informatics
Symposium (IHI 2010), Nov 11-12, 2010, Arlington, VA, USA.
Understanding Deep Web Search Interfaces
Khare R., An Y., Song I-Y. Special Interest Group in Management of Data (SIGMOD) Record,
39(1):33-40, 2010.
An Empirical Study on using Hidden Markov Model for Search Interface
Segmentation
Khare R., and An Y., In the proceedings of 18th International Conference on Information and
Knowledge Management (CIKM 2009), Nov 3-5, 2009, Hong Kong.
44
Form is designed for human consumption. Shorter 10 times – studied on 50 forms from both categories , simpler – hierarchical and repre of database tables (single vs multiple) Explain what is the problem and why its challenging? Syntactic means – formatting and sequence. Patters are infinite and design is so arbittrary that a certain pattern cant be associated with a certain semantic intention.These approaches rely on rendering engines (Gecko, Trident), which makes them browser dependent and inefficient.
to link these elements to the corresponding semantically matching elements of the existing hidden database.Form has values. And longer terms
Whether to merge or not to mergewhether the element in question becomes a new column in a new tablecorresponding to Diagnosis and link the column through foreign key, or do we duplicate this column into the new table and reduce the number of joins.
Make sure everything i.e. the rest of the presentation aligns with this. we seek the answers to these research questions through the development of a system that automatically maps a user-designed form to an existing database.
Prepare obvious answers – how is DOM tree different from semantic tree. Why we generate corres from form tree and then transfer to new database – so that users are presented corres. In terms of the form they had designed. DB-DB integration could be done – but here we leverage semantic form properties. As well.
The input form is represented as an equivalent semantic form tree using a form understandingalgorithm. We adopt a proactive approach to mapping in that we also standardize the formterms using an annotation technique focusing on the healthcare domain. Our solutions to theform understanding and the term annotation algorithms are described in Chapter 9.2. The generated semantic form tree is then studied with respect to the existing database; andthe semantic correspondences between the form tree and the existing database elements arediscovered and validated using user interventions and certain validation rules. This part isdescribed in Chapter 10.3. The form tree with discovered correspondences to the existing database elements is thenmapped and merged with the existing database. In particular, the matching elements aremerged to the target database elements and the new form elements are transformed into newdatabase elements and the existing database is extended using the new database elements.The database design and evolution algorithms are described in Chapter 11.
Approach identifies semantic grouping
the widely used medical terminology.
The HMMs are tailored for data-entry forms, and are aligned with the forms hierarchical complexity thereby providing a high extraction accuracy (Khare and An, 2009)
Who designed the forms? Why not other domains – which other domains? Possible. Have some idea. – opportunity to study whether systems can be improved.
Why does recall decrease – when number of correct predictions decrease on applying the hybrid method. Sometime linguitic approach returns more accurate result.
total number of screens wherein the user suggested to merge the elements over the total number of screens generated as a result of executing the validation algorithm.amount of redundancy minimization performed by the algorithm
Each area indicates the contribution of a form in generating the database elements.The peaks denote the general pattern of forms in a given dataset. Most of the datasets peak atcolumns, implying the most prevalence of textbox fields in the forms. The database 2 peaks atvalues implying the prevalence of select and radiobuttonelds in the forms. The database 5 peaksat foreign keys indicating the prevalence of categories and subcategories in the forms. The broad areas represent the presence of longer forms, and the narrower regions represent the presence ofshorter, or mergeable forms.This does not include the form tree generation time, user intervention time, or the execution of database DDL statements. The duration follows no fixed pattern. It depends multiple factors including the size ofthe form, and the size of the existing database. Lucene indexing helped in controlling the durationand it ranges from a few milliseconds to 200 seconds, even for the large-scale databases such as theones generated from the datasets 4 and 5.
We performed a table-level comparison, We manually analyzed the mismatched tables
At least 50% for all datasets. Huge reduction – many scenarios could be validated were found. 5 options per screen. Screen relevance – very low This denotes that most of the correspondences, identified using the linguistic matching method adopted by Lucene, were not semantically matching, and were hence rejected by the user. The screen relevance was particularly higher (94%) for the dataset 5 that represents the family practice forms. In these forms, the linguistically matching and yet semantically differing terms were not very prevalent. Approved merger for dataset 3, out of all the mergeable form elements, identified by the validation algorithm, 97.29% were merged to a semantically matching database element.
And did we reach all system goals? Specify again. Clearly. Did we reach the system goals?
Our experience of tagging 52 data-entry forms suggests that the training samples can be constructed quickly and easily, as compared to the construction of exhaustive set of rules or heuristicsTo further test the performance of the mapping framework in a heterogeneous environment,