--- abstract: "Nowadays, there are so many increasing amount of information within world-wide web. For these increasing amounts of information, we need efficient and effective index structure when we have to find needed information. Most indexing techniques directly matched terms from the document and terms from query. But there is a problem when matching. That is most system doesn’t consider the meaning of the words. A word can have more than one meaning. But most systems didn’t consider the context (multiple meaning of a word). This paper presents how to construct an index structure using SSTC and context ontology that provides multiple meanings of a word. Context provides extra information to improve search result relevance. This paper produces context semantic cluster to provide indexing of search engine.\r\n" altloc: - http://gssrr.org/index.php?journal=InternationalJournalOfComputer&page=article&op=view&path%5B%5D=1109 - http://gssrr.org/index.php?journal=InternationalJournalOfComputer&page=article&op=view&path%5B%5D=1109&path%5B%5D=1096 chapter: ~ commentary: ~ commref: ~ confdates: ~ conference: ~ confloc: ~ contact_email: ~ creators_id: - atilaelci@yahoo.com creators_name: - family: lai given: 'thinn ' honourific: Dr lineage: '' date: 2013 date_type: published datestamp: 2013-11-18 21:09:53 department: ~ dir: disk0/00/00/91/01 edit_lock_since: ~ edit_lock_until: 0 edit_lock_user: ~ editors_id: [] editors_name: [] eprint_status: archive eprintid: 9101 fileinfo: /style/images/fileicons/application_pdf.png;/9101/1/1109-1923-1-PB.pdf full_text_status: public importid: ~ institution: ~ isbn: ~ ispublished: pub issn: ~ item_issues_comment: [] item_issues_count: ~ item_issues_description: [] item_issues_id: [] item_issues_reported_by: [] item_issues_resolved_by: [] item_issues_status: [] item_issues_timestamp: [] item_issues_type: [] keywords: "indexing, context ontology, semantic suffix tree clustering (SSTC)\r\n" lastmod: 2013-11-18 21:09:53 latitude: ~ longitude: ~ metadata_visibility: show note: ~ number: 1 pagerange: 1-6 pubdom: TRUE publication: International Journal of Computer (IJC) publisher: Global Society of Scientific Research and Researchers (GSSRR) refereed: TRUE referencetext: "Information Retrieval and Web Search (chapter 6) from Web Data Mining, Exploring Hyperlinks, Contents and Usage Data.\r\n\r\nGupta P., and Sharma A.K., \"Context based Indexing in Search Engines using Ontology\", International Journal of Computer Application, 2010.\r\n\r\nS. Deerwester, S.T. Dumais, G. W. Furnas, T. K. Landauer, and R. Harshman. Indexing by Latent Semantic Analysis. Journal of the American Society for Information Science, 1990.\r\n\r\nJanruang, J., Guha, S.: Semantic Suffix Tree Clustering. In: DEIT 2011, IEEE, Bali, Indonesia (2011).\r\n\r\nHaibo Jia, Julian Newman, Huaglory Tianfield \"A new Formal Concept Analysis based learning approach to Ontology building\"\r\n\r\nhttp://en.wikipedia.org/wiki/Ontology (information_science)\r\n\r\nJanruang, J., Guha, S., \"Applying Semantic Suffix Tree Clustering\"\r\n\r\nOren Zamir and Oren Etizioni, Web Document Clustering: A feasibility demonstration. In the proceedings of SIGR, 1998.\r\n\r\nC.Manning, P. Raghavan, and H.Schutze, \"An introduction to information retrieval, \"Cambridge, England: Cambridge University Press, 2009.\r\n\r\nMaxim Marynov, Boris Novikov, \"An Indexing Algorithm for Text Retrieval\", University of St.-Petersburg, Russia.\r\n\r\nE.W. Brown, J.P. Callan, W.B. Croft, and J.E.B. Moss. Supporting full-text information retrieval with a persistent object store,. In Proc. Intnl.Conf, on EDBT., 1994.\r\n\r\nSajendra Kuar, Ram Kumar Rana, Pawan Singh, \"A Semantic Query Transformation Approach Based on Ontology for Search Engine\", International Journal on Computer Science and Engineering (IJCSE), May 2012.\r\n\r\nR.Baeza-Yates and B.Ribeiro-Neto. Modern Information Retrieval. Addison Wesley, 1999.\r\n\r\nN Chen, Technical Report 2006-505 “A survey of Indexing and Retrieval of Multimodal Documents: Text and Images”.\r\n\r\nK. Kotis, G. A. Vouros, K. Stergiou, Department of Information and Communication System Engineering, “Towards Automatic Merging of Domain Ontology: The HCONE- mearge approach." relation_type: [] relation_uri: [] reportno: ~ rev_number: 8 series: ~ source: ~ status_changed: 2013-11-18 21:09:53 subjects: - comp-sci-art-intel succeeds: ~ suggestions: ~ sword_depositor: ~ sword_slug: ~ thesistype: ~ title: "SEMANTIC CLUSTERING WITH CONTEXT ONTOLOGY FOR INFORMATION RETRIEVAL SYSTEM\r\n" type: journalp userid: 21690 volume: 11