A Query-Context oriented Approach to Semantic Search on Web

Vikas Jindal, Seema Bawa, Shalini Batra

Abstract


With ever increasing information available on Web, it is becoming increasingly difficult to find desired information on the Web. It is very common that even most renowned search engines return result sets with not so useful pages to the user. A large pool of information is returned by such search systems in response to the queries especially when queries are ambiguous in nature. The resulting information overload problem has accelerated the development of new Web search technologies. Though the keyword based approach to searching has provided the user with a mean to accessing the Web yet it is limited and less efficient to bridge the gap between the user and relevant information available on the Web. One of the possible options to overcome this problem is to use semantics based search which will provide software agents a more efficient way of finding what users are searching for, within the open source of information on Web. This work proposes a new contextual paradigm for semantically searching the Web with respect to query providing even novice users with highly relevant search results. This context oriented semantic search approach involves generation of more satisfying expansion features addressing various query aspects. Based on the query category entered by the user, the set of expansion features are used for generating new, refined and augmented query. The latter can be submitted to a prevalent search engine to present contextually guided more relevant search results even with less sufficient expression of information need.


Keywords


Information storage and Retrieval; Computing Methodologies

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