Tovek Presentation 3 by Livio Costantini
•Download as PPT, PDF•
0 likes•313 views
The document discusses various features of the Tovek software including descriptors that can be used as input queries, an index manager tool for creating and managing document collections, a connection chart showing relationships between queries and documents, a cross matrix visualizing document matches between query permutations, and a summary graph visualizing query results combined with different fields. It also discusses extracting subject area expert knowledge to design topic trees for searching, data mining, and taxonomy classification, including defining relationships between keywords and rules for evaluating documents.
Report
Share
Report
Share
Recommended
IS411 Research Training 2011
This document provides guidance on how to research the topic of collaboration tools in the government sector. It outlines a step-by-step search strategy process including analyzing the topic, using Boolean operators like AND and OR, truncation, and searching databases like SMU PYXIS, e-journals, and other sources for relevant articles and books. Specific databases mentioned include ACM Digital Library, IEEE Computer Society Digital Library, and SpringerLink.
Aggregation for searching complex information spaces
The diversity and complexity of contents available on the web have dramatically increased in recent years. Multimedia content such as images, videos, maps, voice recordings has been published more often than before. Document genres have also been diversified, for instance, news, blogs, FAQs, wiki. These diversified information sources are often dealt with in a separated way. For example, in web search, users have to switch between search verticals to access different sources. Recently, there has been a growing interest in finding effective ways to aggregate these information sources so that to hide the complexity of the information spaces to users searching for relevant information. For example, so-called aggregated search investigated by the major search engine companies will provide search results from several sources in a single result page. Aggregation itself is not a new paradigm; for instance, aggregate operators are common in database technology.
This talk presents the challenges faced by the like of web search engines and digital libraries in providing the means to aggregate information from several and complex information spaces in a way that helps users in their information seeking tasks. It also discusses how other disciplines including databases, artificial intelligence, and cognitive science can be brought into building effective and efficient aggregated search systems.
Data Dictionary in System Analysis and Design
Data Dictionary
Use of Data Dictionary
Elements of Data Dictionary
Data Dictionary Analysis
Importance of Data Dictionary
Data dictionary
The document discusses concepts related to data dictionaries, including defining data flows, structures, elements, and stores. It provides examples of how each component would be defined in a data dictionary, including the level of detail needed for accurate documentation and analysis. Specific symbols and notations are presented for representing data structures algebraically and defining element attributes like name, length, type, validation rules, and more. The data dictionary is described as a key tool for analyzing a system's data and ensuring consistency across users and applications.
Final
This document discusses analyzing systems using data dictionaries. It defines key concepts like data flows, structures, elements and stores. It provides examples of how to define each of these components in a data dictionary, including describing data flows, structures, elements and stores. The purpose of a data dictionary is to document the data in a system to aid in analysis and development.
Text Indexing and Retrieval
This document discusses information retrieval systems and indexing processes. It describes the differences between IR systems and database management systems, as well as the basic indexing and boolean retrieval processes. Vector space, probabilistic, and cluster-based retrieval models are also introduced. The document provides details on indexing terms, inverted files, weighting formulas and automatic indexing. Relevance feedback techniques and performance measurement in IR are also summarized.
Open Conceptual Data Models
The document discusses conceptual data models and how they can be realized through ontologies and linked data on the semantic web. It describes how conceptual models provide a more semantic description of a problem domain compared to logical or physical data models. RDF, RDFS and OWL allow conceptual models to be exposed as linked data, providing globally unique identifiers and enabling natural navigation between interconnected data items. This overcomes issues with traditional logical/relational models such as impedance mismatch and loss of semantics during development.
AIRDIP model overview
The document discusses requirements and approach for an AIRDIP shared catalogue data model to share metadata between subject catalogues and with Intute. The proposed model uses RLLOMAP as a superset of the Intute data model, with core bibliographic metadata shared across views and additional educational metadata that can differ between subject catalogues. Only the record owner can edit core metadata and is responsible for link checks and reviews.
Recommended
IS411 Research Training 2011
This document provides guidance on how to research the topic of collaboration tools in the government sector. It outlines a step-by-step search strategy process including analyzing the topic, using Boolean operators like AND and OR, truncation, and searching databases like SMU PYXIS, e-journals, and other sources for relevant articles and books. Specific databases mentioned include ACM Digital Library, IEEE Computer Society Digital Library, and SpringerLink.
Aggregation for searching complex information spaces
The diversity and complexity of contents available on the web have dramatically increased in recent years. Multimedia content such as images, videos, maps, voice recordings has been published more often than before. Document genres have also been diversified, for instance, news, blogs, FAQs, wiki. These diversified information sources are often dealt with in a separated way. For example, in web search, users have to switch between search verticals to access different sources. Recently, there has been a growing interest in finding effective ways to aggregate these information sources so that to hide the complexity of the information spaces to users searching for relevant information. For example, so-called aggregated search investigated by the major search engine companies will provide search results from several sources in a single result page. Aggregation itself is not a new paradigm; for instance, aggregate operators are common in database technology.
This talk presents the challenges faced by the like of web search engines and digital libraries in providing the means to aggregate information from several and complex information spaces in a way that helps users in their information seeking tasks. It also discusses how other disciplines including databases, artificial intelligence, and cognitive science can be brought into building effective and efficient aggregated search systems.
Data Dictionary in System Analysis and Design
Data Dictionary
Use of Data Dictionary
Elements of Data Dictionary
Data Dictionary Analysis
Importance of Data Dictionary
Data dictionary
The document discusses concepts related to data dictionaries, including defining data flows, structures, elements, and stores. It provides examples of how each component would be defined in a data dictionary, including the level of detail needed for accurate documentation and analysis. Specific symbols and notations are presented for representing data structures algebraically and defining element attributes like name, length, type, validation rules, and more. The data dictionary is described as a key tool for analyzing a system's data and ensuring consistency across users and applications.
Final
This document discusses analyzing systems using data dictionaries. It defines key concepts like data flows, structures, elements and stores. It provides examples of how to define each of these components in a data dictionary, including describing data flows, structures, elements and stores. The purpose of a data dictionary is to document the data in a system to aid in analysis and development.
Text Indexing and Retrieval
This document discusses information retrieval systems and indexing processes. It describes the differences between IR systems and database management systems, as well as the basic indexing and boolean retrieval processes. Vector space, probabilistic, and cluster-based retrieval models are also introduced. The document provides details on indexing terms, inverted files, weighting formulas and automatic indexing. Relevance feedback techniques and performance measurement in IR are also summarized.
Open Conceptual Data Models
The document discusses conceptual data models and how they can be realized through ontologies and linked data on the semantic web. It describes how conceptual models provide a more semantic description of a problem domain compared to logical or physical data models. RDF, RDFS and OWL allow conceptual models to be exposed as linked data, providing globally unique identifiers and enabling natural navigation between interconnected data items. This overcomes issues with traditional logical/relational models such as impedance mismatch and loss of semantics during development.
AIRDIP model overview
The document discusses requirements and approach for an AIRDIP shared catalogue data model to share metadata between subject catalogues and with Intute. The proposed model uses RLLOMAP as a superset of the Intute data model, with core bibliographic metadata shared across views and additional educational metadata that can differ between subject catalogues. Only the record owner can edit core metadata and is responsible for link checks and reviews.
DITA introduction
This document provides an introduction to DITA (Darwin Information Type Architecture), an XML-based open-source framework for authoring and publishing technical documentation. It discusses what DITA is, why it is used, available tools, key concepts like topics, maps and specializations, best practices, and resources for learning more.
Metadata : Concentrating on the data, not on the scheme
Metadata : Concentrating on the data, not on the schemeAIMS (Agricultural Information Management Standards)
This document introduces LODE-BD (LOD-Enabled Bibliographic Data), a reference tool to help information professionals select appropriate encoding strategies for publishing bibliographic data as linked open data (LOD). LODE-BD provides decision trees to guide the selection of relevant metadata properties and terms from existing standards. It addresses key questions about encoding data for exchange and as LOD, and assists in choosing appropriate terms for different bibliographic properties and entities like titles, subjects, and responsible bodies. The goal is to promote standardized, interoperable LOD-ready bibliographic data.Automatic Metadata Generation Charles Duncan
Slides by Charles Duncan summarising the findings of the automatic metadata generation use cases project, see http://www.intrallect.com/wiki/index.php/AMG-UC
Metadata lecture(9 17-14)
The document discusses perspectives on metadata from web resources and database systems. It describes how metadata comes in many forms and serves various purposes, such as supporting discovery and identification of information resources on the web (resource metadata), and ensuring consistency and analysis of structured data in databases (metadata in database systems). Resource metadata commonly follows standards and is stored separately from the resources it describes, while database metadata includes both structural metadata describing data organization and content metadata in the form of data dictionaries.
How to build a data dictionary
This document discusses how to build a data dictionary. It defines a data dictionary as metadata that specifies tables, columns, attributes, and relationships in a database. It recommends including elements such as data types, constraints, ownership, and comments. An active data dictionary can be accessed directly from a database for automatic updates. Tools can help build and maintain data dictionaries. They are important for understanding, documenting, and sharing knowledge about an organization's data.
Bibliographic metadata (including citation)
This document summarizes a workshop on automatic bibliographic metadata extraction. It discusses the goals of metadata extraction, including improving efficiency of manual metadata creation and revision. Use cases presented include suggesting metadata to researchers during paper deposit and analyzing citations to assess research impact. Standards around document formats, metadata schemas, and citation styles were highlighted as important to metadata extraction. Existing tools for extracting metadata from various document formats were also presented. Issues around text accessibility, localization, and imperfect suggestions were noted. Recommendations included developing a customizable and retrainable system to simplify metadata operations and identification of incorrect records.
Metadata & controlled vocabulary
This document discusses metadata and controlled vocabularies. It defines metadata as structured data about an object that supports functions associated with that object. Metadata includes descriptive information about an object's content, context, and structure. Different types of metadata serve administrative, descriptive, preservation, technical, and use functions. Key metadata schemas discussed include Dublin Core, TEI, METS, and MODS. Controlled vocabularies are important for consistency, accuracy, and efficient searching when assigning subject terms in metadata. Quality metadata should be shareable, consistent, and conform to standards.
Annotating Search Results from Web Databases
Numero Uno Technologies, Final Year Project, Mumbai | Pune
www.nutsmumbai.co.in / www.simplyprojects.in
Arches Getty Brownbag Talk
Talk regarding some of the core concepts of the Arches Project (https://www.archesproject.org/) given as a Brown Bag Talk to internal staff.
Metadata Workshop - Utrecht - November 5, 2008
The document provides an overview of metadata standards and schemes, including their definitions, purposes, relationships and examples. It discusses key standards like MARC, MODS, ONIX, Dublin Core and XML, as well as conceptual models like FRBR that help organize bibliographic data. The goal of metadata is to improve discovery, management and use of resources through structured descriptive information.
Anypresence slides
The document provides an overview of the AnyPresence platform, which is an enterprise-class, cloud-based mobile platform that reduces the cost and complexity of developing mobile apps. It generates native mobile SDKs and integrates with source systems, providing capabilities like role-based access, authentication, and push notifications. The platform allows defining environments for testing and deployment. It supports connecting to various data sources and defining objects and their relationships to represent and access enterprise data.
Xml databases
This document discusses XML databases and effective search engines. It describes how XML is a self-describing format that can store data in a portable way. While XML lacks features of traditional databases like efficient storage and indexing, XML databases address these issues. The document outlines how XML databases can store, search, retrieve and display XML documents and compares them to relational databases. It also provides examples of technologies and modules that can be used to parse, insert, query and synchronize XML documents with databases.
Citation Analysis for the Free, Online Literature
1) The document discusses various services for open access literature including institutional archives, metadata harvesting through Celestial, and citation analysis services like Citebase.
2) It describes how Citebase extracts references from texts and stores them in a structured database to enable citation linking and navigation between cited and citing articles.
3) Early download frequency data from arXiv.org is shown to correlate with longer-term citation frequency, indicating web impact may predict future citation impact.
Introduction to persistency and Berkeley DB
This document discusses different data models for databases including hierarchical, relational, object-oriented, NoSQL, and object-relational models. It also covers the differences between client-server and embedded databases as well as introducing BerkeleyDB as an open source, embedded, non-relational database management system.
Price "KBART: improving the supply of data to link resolvers and knowledge ba...
Price "KBART: improving the supply of data to link resolvers and knowledge ba...National Information Standards Organization (NISO)
KBART is a collaborative project between UKSG and NISO to improve the transfer of accurate holdings data from content providers to knowledge bases and link resolvers. It aims to address problems caused by outdated, incorrect, or inconsistent data by developing guidelines around terminology, data formats, and responsibilities within the serials supply chain. The project representatives are working to define best practices over the next year to help ensure library patrons are directed to the most appropriate version of subscribed content.Jhu Week 6
This document discusses standards for cataloguing museum collections. It begins with definitions of key terms related to database schema and structure like data dictionary, data format, and authority controls. It explains that standards help ensure consistent data entry and effective information retrieval. Resources for cataloguing standards are provided, including websites from the Library of Congress, Getty Trust, and others. The document assignment is to create a data dictionary template for a fictional or personal museum collection to provide public online access to that collection's information and support meaningful interaction.
Chap 9 report (1st time upload/experiment)
This document discusses key concepts related to the internet and web technologies. It defines common web technologies like HTTP, URLs, web browsers and servers. It also describes static and dynamic web pages and how client-side and server-side scripts can make pages dynamic. Finally, it discusses markup languages like HTML, XML and related standards like DTDs, schemas, XSL and XQuery that help structure and present web content.
Evaluation criteria
This document outlines evaluation criteria for reference materials including scope, quality, authority, accuracy, currency, arrangement, format, usability of electronic resources, suitability to user needs, and cost. Scope refers to what topics are covered, dates, comprehensiveness, and international coverage. Quality means accurate, up-to-date, in-depth, and focused on the intended audience. Authority is based on the qualifications of authors and publishers as well as reputation. Accuracy and currency are important to compare to similar materials. Arrangement impacts easy access through organization, indexing, and cross-referencing. Format depends on patron preferences and library budgets. Usability of electronic resources considers search features, speed, and help options. Cost is also
Dats nih-dccpc-kc7-april2018-prs-uoxf
Doing for Data what Pubmed did for literature: DATS a model for dataset description datasets indexing and data discovery.
Googleslides [https://goo.gl/cd5KKa] or Slideshare [https://goo.gl/c8DH5N]
KBART Update ALA Annual 2008
KBART is a collaborative project between UKSG and NISO to improve the transfer of accurate journal holdings data from publishers and providers to knowledge bases and link resolvers. It aims to address problems like outdated or incorrect data that can cause links to full text articles to fail. The KBART working group, comprised of publishers, libraries, vendors and technical experts, is developing guidelines for terminology, data formats and best practices. Their goal is to finish the initial guidelines within a year to help ensure links between citations and available full text content work consistently for library users.
Using metadata repositories with search
The document discusses metadata repositories and their role in search and discovery. It provides examples of metadata repositories like library card catalogs and bibliographic databases. It describes how metadata repositories store metadata separately from content in order to standardize, share, and search metadata more easily. Commercial metadata repository products are also discussed, including their features and pricing.
Text data mining1
Text mining seeks to extract useful information from unstructured text documents. It involves preprocessing the text, identifying features, and applying techniques from data mining, machine learning and natural language processing to discover patterns. The core operations of text mining include analyzing distributions of concepts, identifying frequent concept sets and associations between concepts. Text mining systems aim to analyze document collections over time to identify trends, ephemeral relationships and anomalous patterns.
More Related Content
What's hot
DITA introduction
This document provides an introduction to DITA (Darwin Information Type Architecture), an XML-based open-source framework for authoring and publishing technical documentation. It discusses what DITA is, why it is used, available tools, key concepts like topics, maps and specializations, best practices, and resources for learning more.
Metadata : Concentrating on the data, not on the scheme
Metadata : Concentrating on the data, not on the schemeAIMS (Agricultural Information Management Standards)
This document introduces LODE-BD (LOD-Enabled Bibliographic Data), a reference tool to help information professionals select appropriate encoding strategies for publishing bibliographic data as linked open data (LOD). LODE-BD provides decision trees to guide the selection of relevant metadata properties and terms from existing standards. It addresses key questions about encoding data for exchange and as LOD, and assists in choosing appropriate terms for different bibliographic properties and entities like titles, subjects, and responsible bodies. The goal is to promote standardized, interoperable LOD-ready bibliographic data.Automatic Metadata Generation Charles Duncan
Slides by Charles Duncan summarising the findings of the automatic metadata generation use cases project, see http://www.intrallect.com/wiki/index.php/AMG-UC
Metadata lecture(9 17-14)
The document discusses perspectives on metadata from web resources and database systems. It describes how metadata comes in many forms and serves various purposes, such as supporting discovery and identification of information resources on the web (resource metadata), and ensuring consistency and analysis of structured data in databases (metadata in database systems). Resource metadata commonly follows standards and is stored separately from the resources it describes, while database metadata includes both structural metadata describing data organization and content metadata in the form of data dictionaries.
How to build a data dictionary
This document discusses how to build a data dictionary. It defines a data dictionary as metadata that specifies tables, columns, attributes, and relationships in a database. It recommends including elements such as data types, constraints, ownership, and comments. An active data dictionary can be accessed directly from a database for automatic updates. Tools can help build and maintain data dictionaries. They are important for understanding, documenting, and sharing knowledge about an organization's data.
Bibliographic metadata (including citation)
This document summarizes a workshop on automatic bibliographic metadata extraction. It discusses the goals of metadata extraction, including improving efficiency of manual metadata creation and revision. Use cases presented include suggesting metadata to researchers during paper deposit and analyzing citations to assess research impact. Standards around document formats, metadata schemas, and citation styles were highlighted as important to metadata extraction. Existing tools for extracting metadata from various document formats were also presented. Issues around text accessibility, localization, and imperfect suggestions were noted. Recommendations included developing a customizable and retrainable system to simplify metadata operations and identification of incorrect records.
Metadata & controlled vocabulary
This document discusses metadata and controlled vocabularies. It defines metadata as structured data about an object that supports functions associated with that object. Metadata includes descriptive information about an object's content, context, and structure. Different types of metadata serve administrative, descriptive, preservation, technical, and use functions. Key metadata schemas discussed include Dublin Core, TEI, METS, and MODS. Controlled vocabularies are important for consistency, accuracy, and efficient searching when assigning subject terms in metadata. Quality metadata should be shareable, consistent, and conform to standards.
Annotating Search Results from Web Databases
Numero Uno Technologies, Final Year Project, Mumbai | Pune
www.nutsmumbai.co.in / www.simplyprojects.in
Arches Getty Brownbag Talk
Talk regarding some of the core concepts of the Arches Project (https://www.archesproject.org/) given as a Brown Bag Talk to internal staff.
Metadata Workshop - Utrecht - November 5, 2008
The document provides an overview of metadata standards and schemes, including their definitions, purposes, relationships and examples. It discusses key standards like MARC, MODS, ONIX, Dublin Core and XML, as well as conceptual models like FRBR that help organize bibliographic data. The goal of metadata is to improve discovery, management and use of resources through structured descriptive information.
Anypresence slides
The document provides an overview of the AnyPresence platform, which is an enterprise-class, cloud-based mobile platform that reduces the cost and complexity of developing mobile apps. It generates native mobile SDKs and integrates with source systems, providing capabilities like role-based access, authentication, and push notifications. The platform allows defining environments for testing and deployment. It supports connecting to various data sources and defining objects and their relationships to represent and access enterprise data.
Xml databases
This document discusses XML databases and effective search engines. It describes how XML is a self-describing format that can store data in a portable way. While XML lacks features of traditional databases like efficient storage and indexing, XML databases address these issues. The document outlines how XML databases can store, search, retrieve and display XML documents and compares them to relational databases. It also provides examples of technologies and modules that can be used to parse, insert, query and synchronize XML documents with databases.
Citation Analysis for the Free, Online Literature
1) The document discusses various services for open access literature including institutional archives, metadata harvesting through Celestial, and citation analysis services like Citebase.
2) It describes how Citebase extracts references from texts and stores them in a structured database to enable citation linking and navigation between cited and citing articles.
3) Early download frequency data from arXiv.org is shown to correlate with longer-term citation frequency, indicating web impact may predict future citation impact.
Introduction to persistency and Berkeley DB
This document discusses different data models for databases including hierarchical, relational, object-oriented, NoSQL, and object-relational models. It also covers the differences between client-server and embedded databases as well as introducing BerkeleyDB as an open source, embedded, non-relational database management system.
Price "KBART: improving the supply of data to link resolvers and knowledge ba...
Price "KBART: improving the supply of data to link resolvers and knowledge ba...National Information Standards Organization (NISO)
KBART is a collaborative project between UKSG and NISO to improve the transfer of accurate holdings data from content providers to knowledge bases and link resolvers. It aims to address problems caused by outdated, incorrect, or inconsistent data by developing guidelines around terminology, data formats, and responsibilities within the serials supply chain. The project representatives are working to define best practices over the next year to help ensure library patrons are directed to the most appropriate version of subscribed content.Jhu Week 6
This document discusses standards for cataloguing museum collections. It begins with definitions of key terms related to database schema and structure like data dictionary, data format, and authority controls. It explains that standards help ensure consistent data entry and effective information retrieval. Resources for cataloguing standards are provided, including websites from the Library of Congress, Getty Trust, and others. The document assignment is to create a data dictionary template for a fictional or personal museum collection to provide public online access to that collection's information and support meaningful interaction.
Chap 9 report (1st time upload/experiment)
This document discusses key concepts related to the internet and web technologies. It defines common web technologies like HTTP, URLs, web browsers and servers. It also describes static and dynamic web pages and how client-side and server-side scripts can make pages dynamic. Finally, it discusses markup languages like HTML, XML and related standards like DTDs, schemas, XSL and XQuery that help structure and present web content.
Evaluation criteria
This document outlines evaluation criteria for reference materials including scope, quality, authority, accuracy, currency, arrangement, format, usability of electronic resources, suitability to user needs, and cost. Scope refers to what topics are covered, dates, comprehensiveness, and international coverage. Quality means accurate, up-to-date, in-depth, and focused on the intended audience. Authority is based on the qualifications of authors and publishers as well as reputation. Accuracy and currency are important to compare to similar materials. Arrangement impacts easy access through organization, indexing, and cross-referencing. Format depends on patron preferences and library budgets. Usability of electronic resources considers search features, speed, and help options. Cost is also
Dats nih-dccpc-kc7-april2018-prs-uoxf
Doing for Data what Pubmed did for literature: DATS a model for dataset description datasets indexing and data discovery.
Googleslides [https://goo.gl/cd5KKa] or Slideshare [https://goo.gl/c8DH5N]
KBART Update ALA Annual 2008
KBART is a collaborative project between UKSG and NISO to improve the transfer of accurate journal holdings data from publishers and providers to knowledge bases and link resolvers. It aims to address problems like outdated or incorrect data that can cause links to full text articles to fail. The KBART working group, comprised of publishers, libraries, vendors and technical experts, is developing guidelines for terminology, data formats and best practices. Their goal is to finish the initial guidelines within a year to help ensure links between citations and available full text content work consistently for library users.
What's hot (20)
Metadata : Concentrating on the data, not on the scheme
Metadata : Concentrating on the data, not on the scheme
Price "KBART: improving the supply of data to link resolvers and knowledge ba...
Price "KBART: improving the supply of data to link resolvers and knowledge ba...
Similar to Tovek Presentation 3 by Livio Costantini
Using metadata repositories with search
The document discusses metadata repositories and their role in search and discovery. It provides examples of metadata repositories like library card catalogs and bibliographic databases. It describes how metadata repositories store metadata separately from content in order to standardize, share, and search metadata more easily. Commercial metadata repository products are also discussed, including their features and pricing.
Text data mining1
Text mining seeks to extract useful information from unstructured text documents. It involves preprocessing the text, identifying features, and applying techniques from data mining, machine learning and natural language processing to discover patterns. The core operations of text mining include analyzing distributions of concepts, identifying frequent concept sets and associations between concepts. Text mining systems aim to analyze document collections over time to identify trends, ephemeral relationships and anomalous patterns.
Indexator_oct2022.pdf
Metadata management for data storage spaces :
INDEXATOR is a metadata management tool that addresses the problems of organising, documenting, storing and sharing data in a research unit or infrastructure, and fits perfectly into a data management plan of a collective.
The central idea is that the storage space becomes the data repository, so the metadata should go to the data and not the other way around.
Given the diversity of domains, the approach chosen is to be both as flexible and as pragmatic as possible by allowing each collective to choose its own (controlled) vocabulary corresponding to the reality of its field and activities. The main idea is to be able to "capture" the user's metadata as easily as possible using their vocabulary. It is possible to define the whole terminology using a spreadsheet.
The choice was made for the JSON format, which is very appropriate for describing metadata, readable by both humans and machines.
This tool is built around a web interface coupled with a MongoDB database. The web interface allows you to i) Describe a dataset using metadata of various types (Description), ii) Search datasets by their metadata (Accessibility).
Info 2402 irt-chapter_2
This document describes the basic architecture of a search engine, including its two main processes: indexing and query. The indexing process involves acquiring text from sources, transforming it by parsing, stemming, etc., and creating indexes for fast searching. The query process allows users to input queries, transform queries, rank and retrieve relevant documents from the indexes, and output search results. Key components described are crawlers, parsers, stemmers, inverted indexes, ranking algorithms, and query logs for evaluation.
Searching Repositories of Web Application Models
Project repositories are a central asset in software development, as they preserve the technical knowledge gathered in past development activities. However, locating relevant information in a vast project repository is problematic, because it requires manually tagging projects with accurate metadata, an activity which is time consuming and prone to errors and omissions. This paper investigates the use of classical Information Retrieval techniques for easing the discovery of useful information from past projects. Differently from approaches based on textual search over the source code of applications or on querying structured metadata, we propose to index and search the models of applications, which are available in companies applying Model-Driven Engineering practices. We contrast alternative index structures and result presentations, and evaluate a prototype implementation on real-world experimental data.
SharePoint Connections Coast to Coast Overview of Enterprise Content Management
This session walks you through some of the enterprise content management features in SharePoint 2010 such as metadata management, document sets, records management, search, and more. The demos will include declarative and programmatic creation of document sets and document ids, records management routing, and search
Swap For Dummies Rsp 2007 11 29
The document introduces the Scholarly Works Application Profile (SWAP), which is a Dublin Core application profile for describing scholarly works held in institutional repositories. SWAP defines a model for scholarly works and their relationships using entities like ScholarlyWork, Expression, Manifestation, and Copy. It also specifies a set of metadata properties and an XML format for encoding and sharing metadata records between systems according to this model. The document provides an example of using SWAP to describe a scholarly work with multiple expressions, manifestations, and copies.
TSPUG: Content Management in SharePoint 2010
This presentation was delivered at the Toronto SharePoint User Group's December 2009 meeting. Note that all slides containing graphics were aggregated from Microsoft decks presented during SPC 2009, corrections and text-only slides are original.
Red Hat Summit Connect 2023 - Redis Enterprise, the engine of Generative AI
Redis è conosciuto come un database in tempo reale che può essere utilizzato come cache, per memorizzare sessioni utente o immagazzinare token d’autenticazione, documenti JSON, per gestire inventari in tempo reale, dati geografici, come feature store in scenari di machine learning, gestione di code, broker, stream e molto altro. Ma non tutti sanno che Redis può memorizzare e indicizzare vettori di embeddings, ovvero quelle strutture dati che sono alla base di applicativi come ChatGPT. In questo talk, esploreremo come utilizzare Redis come un database vettoriale per implementare casi d’uso moderni.
Instant ECM with SharePoint 2010 - SPTechCon Boston 2011
This document discusses how SharePoint 2010 can provide instant enterprise content management (ECM) capabilities. It outlines various SharePoint features like versioning, ratings, managed metadata, and the document id service that help with ECM challenges like lack of time, cost and organization. Each feature is briefly described, including how it is configured and enabled for use. The document aims to demonstrate how SharePoint 2010 can help users better organize and manage their document libraries and content.
Xml
This document provides an introduction to XML, including:
- XML stands for eXtensible Markup Language and allows users to define their own tags to provide structure and meaning to data.
- XML documents use elements with start and end tags to organize content in a hierarchical, tree-like structure. Elements can contain text or other nested elements.
- Attributes within start tags provide additional metadata about elements. Well-formed XML documents must follow syntax rules to be valid.
Concept Based Search
The document compares and contrasts concept-based search using SySearch versus traditional keyword search. SySearch uses concepts extracted from documents and queries to understand information needs better than keyword matching alone. It ranks results by estimating the probability of relevance using a Bayesian approach rather than binary keyword matching. This allows it to better support natural language queries and retrieve more relevant results.
A Novel Approach for Keyword extraction in learning objects using text mining
Keyword extraction, concept finding are in learning objects is very important subject in today’s eLearning environment. Keywords are subset of words that contains the useful information about the content of the document. Keyword extraction is a process that is used to get the important keywords from documents. In this proposed System Decision tree algorithm is used for feature selection process using wordnet dictionary. WordNet is a lexical database of English which is used to find similarity from the candidate words. The words having highest similarity are taken as keywords.
Understanding Information Architecture
Presented at DocTrain East 2007 by Joe Gelb, Suite Solutions -- Designing, building and maintaining a coherent information architecture is critical to proper planning, creation, management and delivery of documentation and training content. This is especially true when your content is based on a modular or topic-based model such as DITA and SCORM or if you are migrating to such a model.
But where to start? Terms such as taxonomy, semantics, and ontology can be intimidating, and recognized standards like RDF, OWL, Topic Maps (XTM) and SKOS seem so abstract. This pragmatic workshop will provide an overview of the standards and concepts, and a chance to use them hands-on to turn the abstract into tangible skills. We will demonstrate how a well-designed information architecture facilitates reuse and how the information model is integrally connected to conditional and multi-purpose publishing.
We will introduce an innovative, comprehensive methodology for information modeling and content development called SOTA Solution Oriented Topic Architecture. SOTA does not aim to be yet another new standard, but rather a concrete methodology backed up with open-source and accessible tools for using existing standards. We will demonstrate ֖and practice—hands-on—how this powerful methodology can help you organize and express information, determine which content actually needs to be created or updated, and build documentation and training deliverables from your content based on the rules you define.
This workshop is essential for successfully implementing topic models like DITA and SCORM, multi-purpose conditional publishing, and successfully facilitating content reuse.
Tdm information retrieval
Information retrieval (IR) is the process of searching for and retrieving relevant documents from a large collection based on a user's query. Key aspects of IR include:
- Representing documents and queries in a way that allows measuring their similarity, such as the vector space model.
- Ranking retrieved documents by relevance to the query using factors like term frequency and inverse document frequency.
- Allowing for similarity-based retrieval where documents similar to a given document are retrieved.
Haystacks slides
his talk will feature some of my recent research into the alternative uses for Solr facets and facet metadata. I will develop the idea that facets can be used to discover similarities between items and attributes in a search index, and show some interesting applications of this idea. A common takeaway is that using facets and facet metadata in non-conventional ways enables the semantic context of a query to be automatically tuned. This has important implications for user-centric and semantically focused relevance.
Modular Documentation Joe Gelb Techshoret 2009
Designing, building and maintaining a coherent content model is critical to proper planning, creation, management and delivery of documentation and training content. This is especially true when implementing a modular or topic-based XML standard such as DITA, SCORM and S1000D, and is essential for successfully facilitating content reuse, multi-purpose conditional publishing and user-driven content.
During this presentation we will review basic concepts and methods for implementing information architecture. We will then introduce an innovative, comprehensive methodology for information modeling and content development that employs recognized XML standards for representation and interchange of knowledge, such as Topic Maps and SKOS. In this way, semantic technologies designed for taxonomy and ontology development can be brought to bear for creating and managing technical documentation and training content, and ultimately impacting the usability and findability of technical information.
How to Find a Needle in the Haystack
The document discusses various technologies for metasearching or cross-searching multiple databases at once, including Z39.50 for real-time searching, SRU/SRW web services, and OAI-PMH for metadata harvesting. It explains concepts like XML, web services, SOAP, and WSDL, and provides examples of how technologies like Z39.50, SRU, and OAI-PMH enable searching across different data sources.
Making IA Real: Planning an Information Architecture Strategy
Presented at Internet Librarian conference in 2001. Provides an introduction to what information architecture is and how you can use the methods to develop a good website.
Dublin Core In Practice
Part 4 of tutorials at DC2008, Berlin. (International Conference on Dublin Core and Metadata Applications). See also part 1-3 by Jane Greenberg, Pete Johnston, and Mikael Nilsson on DC history, concepts, and other schemas. This part focuses on practical issues.
Similar to Tovek Presentation 3 by Livio Costantini (20)
SharePoint Connections Coast to Coast Overview of Enterprise Content Management
SharePoint Connections Coast to Coast Overview of Enterprise Content Management
Red Hat Summit Connect 2023 - Redis Enterprise, the engine of Generative AI
Red Hat Summit Connect 2023 - Redis Enterprise, the engine of Generative AI
Instant ECM with SharePoint 2010 - SPTechCon Boston 2011
Instant ECM with SharePoint 2010 - SPTechCon Boston 2011
A Novel Approach for Keyword extraction in learning objects using text mining
A Novel Approach for Keyword extraction in learning objects using text mining
Making IA Real: Planning an Information Architecture Strategy
Making IA Real: Planning an Information Architecture Strategy
Recently uploaded
Choosing The Best AWS Service For Your Website + API.pptx
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
What is an RPA CoE? Session 1 – CoE Vision
In the first session, we will review the organization's vision and how this has an impact on the COE Structure.
Topics covered:
• The role of a steering committee
• How do the organization’s priorities determine CoE Structure?
Speaker:
Chris Bolin, Senior Intelligent Automation Architect Anika Systems
HCL Notes and Domino License Cost Reduction in the World of DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
"Choosing proper type of scaling", Olena Syrota
Imagine an IoT processing system that is already quite mature and production-ready and for which client coverage is growing and scaling and performance aspects are life and death questions. The system has Redis, MongoDB, and stream processing based on ksqldb. In this talk, firstly, we will analyze scaling approaches and then select the proper ones for our system.
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Building Production Ready Search Pipelines with Spark and Milvus
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Fueling AI with Great Data with Airbyte Webinar
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
“How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-eff...
“How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-eff...Edge AI and Vision Alliance
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/how-axelera-ai-uses-digital-compute-in-memory-to-deliver-fast-and-energy-efficient-computer-vision-a-presentation-from-axelera-ai/
Bram Verhoef, Head of Machine Learning at Axelera AI, presents the “How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-efficient Computer Vision” tutorial at the May 2024 Embedded Vision Summit.
As artificial intelligence inference transitions from cloud environments to edge locations, computer vision applications achieve heightened responsiveness, reliability and privacy. This migration, however, introduces the challenge of operating within the stringent confines of resource constraints typical at the edge, including small form factors, low energy budgets and diminished memory and computational capacities. Axelera AI addresses these challenges through an innovative approach of performing digital computations within memory itself. This technique facilitates the realization of high-performance, energy-efficient and cost-effective computer vision capabilities at the thin and thick edge, extending the frontier of what is achievable with current technologies.
In this presentation, Verhoef unveils his company’s pioneering chip technology and demonstrates its capacity to deliver exceptional frames-per-second performance across a range of standard computer vision networks typical of applications in security, surveillance and the industrial sector. This shows that advanced computer vision can be accessible and efficient, even at the very edge of our technological ecosystem.Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
Dmitrii Kamaev, PhD
Senior Product Owner - QIAGEN
Best 20 SEO Techniques To Improve Website Visibility In SERP
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
Digital Marketing Trends in 2024 | Guide for Staying Ahead
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
GNSS spoofing via SDR (Criptored Talks 2024)
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Introduction of Cybersecurity with OSS at Code Europe 2024
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
GraphRAG for LifeSciences Hands-On with the Clinical Knowledge Graph
Tomaz Bratanic
Graph ML and GenAI Expert - Neo4j
Recently uploaded (20)
WeTestAthens: Postman's AI & Automation Techniques
WeTestAthens: Postman's AI & Automation Techniques
Choosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptx
HCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAU
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Building Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and Milvus
“How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-eff...
“How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-eff...
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
Digital Marketing Trends in 2024 | Guide for Staying Ahead
Digital Marketing Trends in 2024 | Guide for Staying Ahead
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
Introduction of Cybersecurity with OSS at Code Europe 2024
Introduction of Cybersecurity with OSS at Code Europe 2024
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
GraphRAG for LifeSciences Hands-On with the Clinical Knowledge Graph
GraphRAG for LifeSciences Hands-On with the Clinical Knowledge Graph
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Tovek Presentation 3 by Livio Costantini
- 1. Descriptor “Temelin” and relation with partner words
- 2. Harvester
- 3. Visualization of a “Descriptor” - Temelin - and the relation with Partner words
- 4. Descriptors can be used as input query in concert with Tovek’s agent
- 5. Descriptors can be used as input query in concert with InfoRating
- 7. Connection Chart Relationships between queries and documents, together with their scores Possibility to add comments to the queries and/or documents Switches for the main pane Query pane Main pane Documents pane
- 8. Cross Matrix Upper panel - Number of documents matching all the possible permutations of two queries Lower panel – Documents matching the selected element of the Cross Matrix
- 9. Summary Graph Visualisation of the results of the queries in combination with different fields (Source or Date ) (e.g. queries within weeks)
- 10. Query-By-Example
- 11. Extracting knowledge from subject area experts Subject Area Expert Knowledge Engineer The Knowledge Engineer extracts and organizes the knowledge of the Subject-Area Expert and expresses it in a hierarchic format which can be used in a “Topic Tree” environment. Design a Topic Tree - Knowledge Elicitation Process
- 13. Topic Trees – A knowledge representation of “ Ferrari Concept ” Topic trees are predefined query in tree-like form that can be utilized for Searching, Mining and Taxonomy Classification
- 14. Tovek Agent Selecting Collections - Find documents that satisfy specific criteria e.g. Nuclear , test Documents fields or Metadata Selecting collections Documents found Total documents Result List Search Pane & Search Elements