Semantic enrichment of building and construction knowledge sources using a domain ontology for classification

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The paper introduces a new conceptual framework for representation of knowledge sources (whether they are web pages or documents), where each knowledge source is semantically represented (within its domain of use) by a Semantic Vector (SV), which is enriched using the classical vector space model approach extended with ontological support, employing ontology concepts and their relations in the enrichment process. The test domain for the assessment of the approach is the Building and Construction, using an appropriate available Ontology. Preliminary results were collected using a clustering algorithm for document classification where documents were assigned into a pre-defined set of categories. Such results indicate that the proposed approach does improve the precision and recall of classifications.

Original languageEnglish
Title of host publication11th International Conference of Numerical Analysis and Applied Mathematics 2013, ICNAAM 2013
Pages1381-1384
Number of pages4
DOIs
Publication statusPublished - 2013
Event11th International Conference of Numerical Analysis and Applied Mathematics 2013, ICNAAM 2013 - Rhodes, Greece
Duration: 21 Sep 201327 Sep 2013

Publication series

NameAIP Conference Proceedings
Volume1558
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference11th International Conference of Numerical Analysis and Applied Mathematics 2013, ICNAAM 2013
Country/TerritoryGreece
CityRhodes
Period21/09/1327/09/13

Keywords

  • Ontology Engineering
  • Semantic Vectors
  • Unsupervised Document Classification
  • Vector Space Models

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