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Applying semantically adapted vector space model to enhance information retrieval
Tetovo State University, Makedonien.ORCID iD: 0000-0001-7520-695x
Tirana University, Albanien.
Tetovo State University, Makedonien.
2012 (English)In: ICT Innovations 2012 Web Proceedings: Poster Session / [ed] S. Markovski, M. Gusev, Ohrid: ICT ACT , 2012, p. 573-575Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

Abstract. While most enterprise data is unstructured and file based, the need for access to structured data is increasing. In order to reduce the cost for finding information and achieve relevant results there is a need to build a very complex query which indeed is a serious challenge. Data volumes are growing at 60% annually and up to 80% of this data in any organization can be unstructured. In this paper we focus on describing the evolution of some modern ontology-based information retrieval systems. Further, we will provide a brief overview of the key advances in the field of semantic information retrieval from heterogeneous information sources, and a description of where the state-of-the-art is at in the field. Finally, we present and propose a novel use of semantic retrieval model based on the vector space model for the exploitation of KB (Knowledge Base) to enhance and support searching over robust and heterogeneous environments.

Place, publisher, year, edition, pages
Ohrid: ICT ACT , 2012. p. 573-575
National Category
Computer Sciences
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
URN: urn:nbn:se:lnu:diva-67854OAI: oai:DiVA.org:lnu-67854DiVA, id: diva2:1139280
Conference
ICT Innovations Conference 2012, Ohrid, Macedonia
Available from: 2017-09-07 Created: 2017-09-07 Last updated: 2018-01-13Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf