Ontology based search result optimisation using singular matrix

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    In recent era, today a many firms share their service/product descriptions. With that, many meaningful information  in the textual form is hidden under the unstructured text. Algorithms like information extraction enable the identification of structured relations and they does not produce an optimal result and it is much costlier to operate with headlines of a text which has no examples of the target structured information. We propose a new approach which facilitates the formation of a structured metadata by recognizing documents which are likely to have some type and this information is to be subsequently used for both segregation and search process. Our approach is based on an idea that some attributes of a text will match with the query object which acts as identifier both for segregation as well as for storage and retrieval. Our implementation results show that our approach provides some superior results than existing approaches which rely only on query content or on textual information, to discover the key attributes.


  • Keywords


    Semantic Analysis, Segregation Index Creation And Recommender System.

  • References


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Article ID: 8983
 
DOI: 10.14419/ijet.v7i1.3.8983




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