Semantic Web and Web Page Clustering Algorithms: A Landscape View
The major evolution of the semantic web has become exchanging data between applications in all domains of activities. Based on this vision, different applications in recent days, e.g. in the fields of community web portals, social networking, e-learning, multimedia retrieval, etc. have been designe...
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| Format: | Article |
| Language: | English |
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European Alliance for Innovation (EAI)
2020-11-01
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| Series: | EAI Endorsed Transactions on Energy Web |
| Subjects: | |
| Online Access: | https://publications.eai.eu/index.php/ew/article/view/803 |
| _version_ | 1797989937754144768 |
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| author | Ahmed J. Obaid Tanusree Chatterjee Abhishek Bhattacharya |
| author_facet | Ahmed J. Obaid Tanusree Chatterjee Abhishek Bhattacharya |
| author_sort | Ahmed J. Obaid |
| collection | DOAJ |
| description |
The major evolution of the semantic web has become exchanging data between applications in all domains of activities. Based on this vision, different applications in recent days, e.g. in the fields of community web portals, social networking, e-learning, multimedia retrieval, etc. have been designed. Due to growing number of web services, clustering of web resources becomes a valuable tool for semantic web mining. Clustering of internet objects like Internet web pages’ intimate new methods for grouping correlated content for better understanding and satisfies massive user query results in web pages’ search. Hence, web pages clustering algorithms should be able to handle massive irregular content and discover knowledge regardless of the web page complexity. These algorithms vary depending on the characteristics and data types. So, choosing the most appropriate algorithm is not an easy process as it should be accurate in terms of time and space complexity. Therefore, this paper rigorously surveys the most important algorithms of different types used for web page clustering. In addition, a comparative analysis of all such algorithms are provided in terms of several parameters. Finally, a brief discussion is provided on why web page clustering isimportant in emerging era of Semantic Web of Thing (SWoT) applications.
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| first_indexed | 2024-04-11T08:28:31Z |
| format | Article |
| id | doaj.art-f8eaeeab5aa345239336a83376422cc2 |
| institution | Directory Open Access Journal |
| issn | 2032-944X |
| language | English |
| last_indexed | 2024-04-11T08:28:31Z |
| publishDate | 2020-11-01 |
| publisher | European Alliance for Innovation (EAI) |
| record_format | Article |
| series | EAI Endorsed Transactions on Energy Web |
| spelling | doaj.art-f8eaeeab5aa345239336a83376422cc22022-12-22T04:34:39ZengEuropean Alliance for Innovation (EAI)EAI Endorsed Transactions on Energy Web2032-944X2020-11-0183310.4108/eai.18-11-2020.167099Semantic Web and Web Page Clustering Algorithms: A Landscape ViewAhmed J. Obaid0Tanusree Chatterjee1Abhishek Bhattacharya2University of Kufa Newton International School Institute of Engineering and Management The major evolution of the semantic web has become exchanging data between applications in all domains of activities. Based on this vision, different applications in recent days, e.g. in the fields of community web portals, social networking, e-learning, multimedia retrieval, etc. have been designed. Due to growing number of web services, clustering of web resources becomes a valuable tool for semantic web mining. Clustering of internet objects like Internet web pages’ intimate new methods for grouping correlated content for better understanding and satisfies massive user query results in web pages’ search. Hence, web pages clustering algorithms should be able to handle massive irregular content and discover knowledge regardless of the web page complexity. These algorithms vary depending on the characteristics and data types. So, choosing the most appropriate algorithm is not an easy process as it should be accurate in terms of time and space complexity. Therefore, this paper rigorously surveys the most important algorithms of different types used for web page clustering. In addition, a comparative analysis of all such algorithms are provided in terms of several parameters. Finally, a brief discussion is provided on why web page clustering isimportant in emerging era of Semantic Web of Thing (SWoT) applications. https://publications.eai.eu/index.php/ew/article/view/803Semantic webweb page clusteringcluster analysisclustering algorithms |
| spellingShingle | Ahmed J. Obaid Tanusree Chatterjee Abhishek Bhattacharya Semantic Web and Web Page Clustering Algorithms: A Landscape View EAI Endorsed Transactions on Energy Web Semantic web web page clustering cluster analysis clustering algorithms |
| title | Semantic Web and Web Page Clustering Algorithms: A Landscape View |
| title_full | Semantic Web and Web Page Clustering Algorithms: A Landscape View |
| title_fullStr | Semantic Web and Web Page Clustering Algorithms: A Landscape View |
| title_full_unstemmed | Semantic Web and Web Page Clustering Algorithms: A Landscape View |
| title_short | Semantic Web and Web Page Clustering Algorithms: A Landscape View |
| title_sort | semantic web and web page clustering algorithms a landscape view |
| topic | Semantic web web page clustering cluster analysis clustering algorithms |
| url | https://publications.eai.eu/index.php/ew/article/view/803 |
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