This document discusses using machine learning models and DOM tree analysis to extract important content from news articles for the purpose of topic detection. Specifically, it proposes using a support vector machine (SVM) model with "leaf classification units" from the DOM tree to remove noise data like images, ads, and recommended articles. This approach is meant to generalize to different article structures compared to rule-based models. The document reviews related work using DOM trees and statistical data for web content extraction and visual wrappers. It also discusses using various kernel functions in SVMs for non-linearly separable data.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Topic Modeling : Clustering of Deep Webpagescsandit
The internet is comprised of massive amount of info
rmation in the form of zillions of web
pages.This information can be categorized into the
surface web and the deep web. The existing
search engines can effectively make use of surface
web information.But the deep web remains
unexploited yet. Machine learning techniques have b
een commonly employed to access deep
web content.
Under Machine Learning, topic models provide a simp
le way to analyze large volumes of
unlabeled text. A "topic" consists of a cluster of
words that frequently occur together. Using
contextual clues, topic models can connect words wi
th similar meanings and distinguish
between words with multiple meanings. Clustering is
one of the key solutions to organize the
deep web databases.In this paper, we cluster deep w
eb databases based on the relevance found
among deep web forms by employing a generative prob
abilistic model called Latent Dirichlet
Allocation(LDA) for modeling content representative
of deep web databases. This is
implemented after preprocessing the set of web page
s to extract page contents and form
contents.Further, we contrive the distribution of “
topics per document” and “words per topic”
using the technique of Gibbs sampling. Experimental
results show that the proposed method
clearly outperforms the existing clustering methods
.
Generic Algorithm based Data Retrieval Technique in Data MiningAM Publications,India
This system Hybrid extraction of robust model (GA), a dynamic XAML based mechanism for the adaptive management and reuse of e-learning resources in a distributed environment like the Web. This proposed system argues that to achieve the on-demand semantic-based resource management for Web-based e-learning, one should go beyond using domain ontology’s statically. So the propose XAML based matching process involves semantic mapping has done on both the open dataset and closed dataset mechanism to integrate e-learning databases by using ontology semantics. It defines context-specific portions from the whole ontology as optimized data and proposes an XAML based resource reuse approach by using an evolution algorithm. It explains the context aware based evolution algorithm for dynamic e-learning resource reuse in detail. This system is going to conduct a simulation experiment and evaluate the proposed approach with a xaml based e-learning scenario. The proposed approach for matching process in web cluster databases from different database servers can be easily integrated and deliver highly dimensional e-learning resource management and reuse is far from being mature. However, e-learning is also a widely open research area, and there is still much room for improvement on the method. This research mechanism includes 1) improving the proposed evolution approach by making use of and comparing different evolutionary algorithms, 2) applying the proposed approach to support more applications, and 3) extending to the situation with multiple e-learning systems or services.
This document discusses perspectives on big data applications for database engineers and IT students. It summarizes key concepts of big data and MongoDB, a popular NoSQL database for managing big data. It then demonstrates practical learning activities using MongoDB, such as installation, terminology, and basic syntax. The document concludes by emphasizing the importance of skills in big data and cloud computing for IT professionals and recommends further research on MongoDB security.
Comparative Study on Graph-based Information Retrieval: the Case of XML DocumentIJAEMSJORNAL
The processing of massive amounts of data has become indispensable especially with the potential proliferation of big data. The volume of information available nowadays makes it difficult for the user to find relevant information in a vast collection of documents. As a result, the exploitation of vast document collections necessitates the implementation of automated technologies that enable appropriate and effective retrieval. In this paper, we will examine the state of the art of IR in XML documents. We will also discuss some works that have used graphs to represent documents in the context of IR. In the same vein, the relationships between the components of a graph are the center of our attention.
Web Content Mining Based on Dom Intersection and Visual Features Conceptijceronline
Structured Data extraction from deep Web pages is a challenging task due to the underlying complex structures of such pages. Also website developer generally follows different web page design technique. Data extraction from webpage is highly useful to build our own database from number applications. A large number of techniques have been proposed to address this problem, but all of them have inherent limitations because they present different limitations and constraints for extracting data from such webpages. This paper presents two different approaches to get structured data extraction. The first approach is non-generic solution which is based on template detection using intersection of Document Object Model Tree of various webpages from the same website. This approach is giving better result in terms of efficiency and accurately locating the main data at the particular webpage. The second approach is based on partial tree alignment mechanism based on using important visual features such as length, size, and position of web table available on the webpages. This approach is a generic solution as it does not depend on one particular website and its webpage template. It is perfectly locating the multiple data regions, data records and data items within a given web page. We have compared our work's result with existing mechanism and found our result much better for number webpage
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Tinydb is a web service that allows users to shorten URLs and associate structured data with the shortened URLs. This allows social media users to include more information in messages that have character limits. The paper discusses how tinydb could be used with Twitter to include metadata and longer URLs in tweets. However, tinydb URLs raise privacy, security, and link rot issues that would need to be addressed before widespread adoption.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Topic Modeling : Clustering of Deep Webpagescsandit
The internet is comprised of massive amount of info
rmation in the form of zillions of web
pages.This information can be categorized into the
surface web and the deep web. The existing
search engines can effectively make use of surface
web information.But the deep web remains
unexploited yet. Machine learning techniques have b
een commonly employed to access deep
web content.
Under Machine Learning, topic models provide a simp
le way to analyze large volumes of
unlabeled text. A "topic" consists of a cluster of
words that frequently occur together. Using
contextual clues, topic models can connect words wi
th similar meanings and distinguish
between words with multiple meanings. Clustering is
one of the key solutions to organize the
deep web databases.In this paper, we cluster deep w
eb databases based on the relevance found
among deep web forms by employing a generative prob
abilistic model called Latent Dirichlet
Allocation(LDA) for modeling content representative
of deep web databases. This is
implemented after preprocessing the set of web page
s to extract page contents and form
contents.Further, we contrive the distribution of “
topics per document” and “words per topic”
using the technique of Gibbs sampling. Experimental
results show that the proposed method
clearly outperforms the existing clustering methods
.
Generic Algorithm based Data Retrieval Technique in Data MiningAM Publications,India
This system Hybrid extraction of robust model (GA), a dynamic XAML based mechanism for the adaptive management and reuse of e-learning resources in a distributed environment like the Web. This proposed system argues that to achieve the on-demand semantic-based resource management for Web-based e-learning, one should go beyond using domain ontology’s statically. So the propose XAML based matching process involves semantic mapping has done on both the open dataset and closed dataset mechanism to integrate e-learning databases by using ontology semantics. It defines context-specific portions from the whole ontology as optimized data and proposes an XAML based resource reuse approach by using an evolution algorithm. It explains the context aware based evolution algorithm for dynamic e-learning resource reuse in detail. This system is going to conduct a simulation experiment and evaluate the proposed approach with a xaml based e-learning scenario. The proposed approach for matching process in web cluster databases from different database servers can be easily integrated and deliver highly dimensional e-learning resource management and reuse is far from being mature. However, e-learning is also a widely open research area, and there is still much room for improvement on the method. This research mechanism includes 1) improving the proposed evolution approach by making use of and comparing different evolutionary algorithms, 2) applying the proposed approach to support more applications, and 3) extending to the situation with multiple e-learning systems or services.
This document discusses perspectives on big data applications for database engineers and IT students. It summarizes key concepts of big data and MongoDB, a popular NoSQL database for managing big data. It then demonstrates practical learning activities using MongoDB, such as installation, terminology, and basic syntax. The document concludes by emphasizing the importance of skills in big data and cloud computing for IT professionals and recommends further research on MongoDB security.
Comparative Study on Graph-based Information Retrieval: the Case of XML DocumentIJAEMSJORNAL
The processing of massive amounts of data has become indispensable especially with the potential proliferation of big data. The volume of information available nowadays makes it difficult for the user to find relevant information in a vast collection of documents. As a result, the exploitation of vast document collections necessitates the implementation of automated technologies that enable appropriate and effective retrieval. In this paper, we will examine the state of the art of IR in XML documents. We will also discuss some works that have used graphs to represent documents in the context of IR. In the same vein, the relationships between the components of a graph are the center of our attention.
Web Content Mining Based on Dom Intersection and Visual Features Conceptijceronline
Structured Data extraction from deep Web pages is a challenging task due to the underlying complex structures of such pages. Also website developer generally follows different web page design technique. Data extraction from webpage is highly useful to build our own database from number applications. A large number of techniques have been proposed to address this problem, but all of them have inherent limitations because they present different limitations and constraints for extracting data from such webpages. This paper presents two different approaches to get structured data extraction. The first approach is non-generic solution which is based on template detection using intersection of Document Object Model Tree of various webpages from the same website. This approach is giving better result in terms of efficiency and accurately locating the main data at the particular webpage. The second approach is based on partial tree alignment mechanism based on using important visual features such as length, size, and position of web table available on the webpages. This approach is a generic solution as it does not depend on one particular website and its webpage template. It is perfectly locating the multiple data regions, data records and data items within a given web page. We have compared our work's result with existing mechanism and found our result much better for number webpage
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Tinydb is a web service that allows users to shorten URLs and associate structured data with the shortened URLs. This allows social media users to include more information in messages that have character limits. The paper discusses how tinydb could be used with Twitter to include metadata and longer URLs in tweets. However, tinydb URLs raise privacy, security, and link rot issues that would need to be addressed before widespread adoption.
No other medium has taken a more meaningful place in our life in such a short time than the world wide largest data network, the World Wide Web. However, when searching for information in the data network, the user is constantly exposed to an ever growing ood of information. This is both a blessing and a curse at the same time. The explosive growth and popularity of the world wide web has resulted in a huge number of information sources on the Internet. As web sites are getting more complicated, the construction of web information extraction systems becomes more difficult and time consuming. So the scalable automatic Web Information Extraction WIE is also becoming high demand. There are four levels of information extraction from the World Wide Web such as free text level, record level, page level and site level. In this paper, the target extraction task is record level extraction. Nwe Nwe Hlaing | Thi Thi Soe Nyunt | Myat Thet Nyo "The Data Records Extraction from Web Pages" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd28010.pdfPaper URL: https://www.ijtsrd.com/computer-science/world-wide-web/28010/the-data-records-extraction-from-web-pages/nwe-nwe-hlaing
Vision Based Deep Web data Extraction on Nested Query Result RecordsIJMER
This document summarizes a research paper on vision-based deep web data extraction from nested query result records. It proposes a technique to extract data from web pages using different font styles, sizes, and cascading style sheets. The extracted data is then aligned into a table using alignment algorithms, including pair-wise, holistic, and nested-structure alignment. The goal is to remove immaterial information from query result pages to facilitate analysis of the extracted data.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
1. The document describes a search engine scraper that extracts data from websites, summarizes the extracted information, and converts it into a relevant result for users.
2. The search engine scraper works in three stages: extraction of data from website content, summarization of the extracted data using natural language processing techniques, and conversion of the summarized data into a meaningful format for users.
3. The summarization stage uses natural language toolkit processing libraries to determine sentence similarity, assign weights to sentences, and select sentences with higher ranks to include in the summary.
A language independent web data extraction using vision based page segmentati...eSAT Journals
Abstract Web usage mining is a process of extracting useful information from server logs i.e. user’s history. Web usage mining is a process of finding out what users are looking for on the internet. Some users might be looking at only textual data, where as some others might be interested in multimedia data. One would retrieve the data by copying it and pasting it to the relevant document. But this is tedious and time consuming as well as difficult when the data to be retrieved is plenty. Extracting structured data from a web page is challenging problem due to complicated structured pages. Earlier they were used web page programming language dependent; the main problem is to analyze the html source code. In earlier they were considered the scripts such as java scripts and cascade styles in the html files. When it makes different for existing solutions to infer the regularity of the structure of the WebPages only by analyzing the tag structures. To overcome this problem we are using a new algorithm called VIPS algorithm i.e. independent language. This approach primary utilizes the visual features on the webpage to implement web data extraction. Keywords: Index terms-Web mining, Web data extraction.
A language independent web data extraction using vision based page segmentati...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Implementation of Sentimental Analysis of Social Media for Stock Prediction ...IRJET Journal
This document describes a framework for predicting future stock prices based on sentiment analysis of social media data from Twitter. The framework collects tweets related to Apple Inc. over 3 months, performs sentiment analysis to classify tweets as positive or negative, and uses an ARIMA model to predict stock prices based on the sentiment values and past stock price data. The results show that predictions using tweets containing the stock symbol were more accurate than those using just the company name. Factors like the training data, preprocessing techniques, and number of tweets per time period can impact prediction accuracy. While limitations remain, the analysis demonstrates a relationship between social media sentiment and stock market movements.
Web usage Mining Based on Request Dependency GraphIRJET Journal
This document discusses using request dependency graphs (RDGs) to model the dependency relationships between HTTP requests for web usage mining. RDGs can improve data quality and enhance network and web server performance. The authors evaluated their approach using a large real-world web access log and found that RDGs are a useful tool for web usage mining by extracting patterns from user access behaviors and decomposing websites.
IRJET- Development and Design of Recommendation System for User Interest Shop...IRJET Journal
This document presents a machine learning based recommendation system for recommending products to users based on their interests. It proposes a technique called Fidoop DP that uses Voronoi diagrams to partition user data across nodes in a Hadoop cluster in order to reduce network overhead. The system tracks users' social media activities to identify brands and products they like. These are used to rank and recommend products to users on a shopping site. It was found to significantly reduce loads on Hadoop cluster nodes. The authors believe this approach could be enhanced further using real machine learning algorithms and big data from actual social media and shopping applications.
Review on an automatic extraction of educational digital objects and metadata...IRJET Journal
This document reviews systems for automatically extracting educational digital objects (EDOs) and metadata from institutional websites. It discusses existing systems like Agathe, Crossmarc, and CiteSeerX that extract information from documents but not linked web pages. The proposed system would crawl a website, extract and classify EDOs into audio, video and text, and store them in a database along with automatically extracted metadata like title, category, author. This aims to assist repositories in identifying documents that could be uploaded along with their metadata.
IRJET- Recommendation System based on Graph Database TechniquesIRJET Journal
This document proposes a recommendation system based on graph database techniques. It uses Neo4j to develop a recommendation approach using content-based filtering, collaborative filtering, and hybrid filtering. The system recommends restaurants and meals to customers based on reviews and friend recommendations. It stores data about restaurants, meals, customers and their reviews in a graph database to allow for complex queries and recommendations. The implementation and results of the proposed recommendation system are also discussed.
IRJET- Towards Efficient Framework for Semantic Query Search Engine in Large-...IRJET Journal
The document proposes a new framework for efficient semantic search in large datasets. It aims to improve understanding of short texts by enriching them with concepts and related terms from a probabilistic knowledge base. A deep learning model using stacked autoencoders is designed to learn features from the enriched short texts and encode them into binary codes, allowing similarity searches. Experiments show the new approach captures semantics better than existing methods and enables applications like short text retrieval and classification.
An Overview of General Data Mining ToolsIRJET Journal
This document provides an overview of several popular general data mining tools: Weka, Rapid Miner, IBM SPSS, Tanagra, KNIME, Orange, and R. It describes the key characteristics of each tool, including their interfaces, available algorithms, licensing, community support, and abilities for workflows and big data processing. Overall, the document evaluates and compares the capabilities of these seven major data mining software platforms.
Quality of Groundwater in Lingala Mandal of YSR Kadapa District, Andhraprades...IRJET Journal
This document provides an overview of several popular general data mining tools: Weka, Rapid Miner, IBM SPSS, Tanagra, KNIME, Orange, and R. It describes the key characteristics of each tool, including their interfaces, available algorithms, licensing, community support, and abilities for workflows and big data processing. Overall, the document finds that while each tool has strengths in different areas, Weka, Rapid Miner, IBM SPSS, KNIME, and Orange provide robust functionality for a wide range of general data mining tasks through their graphical user interfaces and available algorithms.
Journal of Physics Conference SeriesPAPER • OPEN ACCESS.docxLaticiaGrissomzz
Journal of Physics: Conference Series
PAPER • OPEN ACCESS
The methodology of database design in
organization management systems
To cite this article: I L Chudinov et al 2017 J. Phys.: Conf. Ser. 803 012030
View the article online for updates and enhancements.
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The methodology of database design in organization
management systems
I L Chudinov, V V Osipova, Y V Bobrova
Tomsk Polytechnic University, 30, Lenina ave., Tomsk, 634050, Russia
E-mail: [email protected]
Abstract. The paper describes the unified methodology of database design for management
information systems. Designing the conceptual information model for the domain area is the
most important and labor-intensive stage in database design. Basing on the proposed integrated
approach to design, the conceptual information model, the main principles of developing the
relation databases are provided and user’s information needs are considered. According to the
methodology, the process of designing the conceptual information model includes three basic
stages, which are defined in detail. Finally, the article describes the process of performing the
results of analyzing user’s information needs and the rationale for use of classifiers.
1. Introduction
Management information systems are among the most important components of information
technologies (IT), used in a company. They are usually classified by the functions into the following
systems: Manufacturing Execution Systems (MES), Human Resource Management (HRM), Enterprise
Content Management (ECM), Customer Relationship Management (CRM), etc. [1]. Such systems are
used a special structured database and are required for reengineering of the whole enterprise
management system, while the integration makes it difficult to use them. These systems are expensive
enough and particularly devel.
This document discusses extracting main content from deep web pages that contain multiple data regions. It proposes a hybrid approach with two steps: 1) Using visual features to identify the different data regions in the DOM tree. 2) Independently mining positive data records and data items from each data region using vision-based page segmentation. Related work on single-region deep web page extraction is also reviewed. The technique aims to automatically extract information from complex pages containing multiple, independent data listings.
IRJET - Cloud Computing Over Traditional ComputingIRJET Journal
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IRJET- A Novel Framework for Three Level Isolation in Cloud System based ...IRJET Journal
This document proposes a novel three-level isolation framework for cloud storage based on fog computing. The framework aims to address privacy and security issues in cloud storage by distributing user data across three layers - cloud servers, fog servers, and local machines. It uses a hash-Solomon encoding algorithm to split user data into multiple shares and store each share in a different layer. This provides three-way redundancy to protect against data loss and enhances security by isolating data across multiple environments. Theoretical analysis and experimental evaluation demonstrate the feasibility and security improvements of the proposed three-level isolation framework compared to existing cloud storage schemes.
Business Intelligence Solution Using Search Engineankur881120
The document describes a business intelligence solution that uses a search engine to index and search web pages. It discusses using crawlers to index web pages and store them in a repository. An indexer then generates an inverted index from the repository to support keyword searches. The system architecture includes the repository, indexer, and search functionality. It also describes the database structure used to store crawled URLs, the index, and search results. The project aims to build a basic search engine to demonstrate the proposed business intelligence solution.
Advance Frameworks for Hidden Web Retrieval Using Innovative Vision-Based Pag...IOSR Journals
The document proposes an innovative vision-based page segmentation (IVBPS) algorithm to improve hidden web content extraction. It aims to overcome limitations of existing approaches that rely heavily on HTML structure. IVBPS extracts blocks from the visual representation of a page and clusters them to segment the page semantically. It uses layout features like position and appearance to locate data regions and extract records. The algorithm analyzes the entire page structure rather than local regions, allowing it to retain content DOM tree methods may discard. This is expected to significantly improve hidden web extraction performance.
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1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
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No other medium has taken a more meaningful place in our life in such a short time than the world wide largest data network, the World Wide Web. However, when searching for information in the data network, the user is constantly exposed to an ever growing ood of information. This is both a blessing and a curse at the same time. The explosive growth and popularity of the world wide web has resulted in a huge number of information sources on the Internet. As web sites are getting more complicated, the construction of web information extraction systems becomes more difficult and time consuming. So the scalable automatic Web Information Extraction WIE is also becoming high demand. There are four levels of information extraction from the World Wide Web such as free text level, record level, page level and site level. In this paper, the target extraction task is record level extraction. Nwe Nwe Hlaing | Thi Thi Soe Nyunt | Myat Thet Nyo "The Data Records Extraction from Web Pages" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd28010.pdfPaper URL: https://www.ijtsrd.com/computer-science/world-wide-web/28010/the-data-records-extraction-from-web-pages/nwe-nwe-hlaing
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The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
1. The document describes a search engine scraper that extracts data from websites, summarizes the extracted information, and converts it into a relevant result for users.
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A language independent web data extraction using vision based page segmentati...eSAT Journals
Abstract Web usage mining is a process of extracting useful information from server logs i.e. user’s history. Web usage mining is a process of finding out what users are looking for on the internet. Some users might be looking at only textual data, where as some others might be interested in multimedia data. One would retrieve the data by copying it and pasting it to the relevant document. But this is tedious and time consuming as well as difficult when the data to be retrieved is plenty. Extracting structured data from a web page is challenging problem due to complicated structured pages. Earlier they were used web page programming language dependent; the main problem is to analyze the html source code. In earlier they were considered the scripts such as java scripts and cascade styles in the html files. When it makes different for existing solutions to infer the regularity of the structure of the WebPages only by analyzing the tag structures. To overcome this problem we are using a new algorithm called VIPS algorithm i.e. independent language. This approach primary utilizes the visual features on the webpage to implement web data extraction. Keywords: Index terms-Web mining, Web data extraction.
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IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
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Journal of Physics Conference SeriesPAPER • OPEN ACCESS.docxLaticiaGrissomzz
Journal of Physics: Conference Series
PAPER • OPEN ACCESS
The methodology of database design in
organization management systems
To cite this article: I L Chudinov et al 2017 J. Phys.: Conf. Ser. 803 012030
View the article online for updates and enhancements.
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The methodology of database design in organization
management systems
I L Chudinov, V V Osipova, Y V Bobrova
Tomsk Polytechnic University, 30, Lenina ave., Tomsk, 634050, Russia
E-mail: [email protected]
Abstract. The paper describes the unified methodology of database design for management
information systems. Designing the conceptual information model for the domain area is the
most important and labor-intensive stage in database design. Basing on the proposed integrated
approach to design, the conceptual information model, the main principles of developing the
relation databases are provided and user’s information needs are considered. According to the
methodology, the process of designing the conceptual information model includes three basic
stages, which are defined in detail. Finally, the article describes the process of performing the
results of analyzing user’s information needs and the rationale for use of classifiers.
1. Introduction
Management information systems are among the most important components of information
technologies (IT), used in a company. They are usually classified by the functions into the following
systems: Manufacturing Execution Systems (MES), Human Resource Management (HRM), Enterprise
Content Management (ECM), Customer Relationship Management (CRM), etc. [1]. Such systems are
used a special structured database and are required for reengineering of the whole enterprise
management system, while the integration makes it difficult to use them. These systems are expensive
enough and particularly devel.
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- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
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Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)