, Ruban ¹, Behin Sam ², Rakesh Kumar ³

Affiliations
1 Department of Computer Science, Bharathiar University, Tamil Nadu – 641046, IN
2 Department of Computer Science, Rajeswari Vedachalam Arts and Science College, Chengalpattu, Tamil Nadu – 603001, IN
3 Department of MCA, AIMIT, St. Aloysius College, Mangalore– 575022, IN

Abstract

Searching has become part and parcel of our human life. This has been possible because of the significant improvement that has happened in the field of information retrieval. Any Information Retrieval application can be considered as a collection of different components namely Query Interface where the user enters their information need, the document representation which is done using the indexing process, the matching process which compares the query and the document representation that is available in the index, and finally the ranking process which arranges the documents according to their user query relevance. Lot of work has been done by commercial search engine organizations to make searching a rewarding experience to the users. One such area is to know the user intention behind the queries that is being given in the query interface. Based on the user intention, user queries are being classified as informational, navigational and transactional queries. To make queries more responsive for Information Retrieval, Query Refinement can be done on the individual queries. In recent times ontology has been used in query refinement process and many studies in this area has shown considerable improvement with respect to the results retrieved. In this paper we would like to study the impact of Domain independent ontology in the query refinement process involving transactional queries.

Keywords

Searching has become part and parcel of our human life. This has been possible because of the significant improvement that has happened in the field of information retrieval. Any Information Retrieval application can be considered as a collection of different components namely Query Interface where the user enters their information need, the document representation which is done using the indexing process, the matching process which compares the query and the document representation that is available in the index, and finally the ranking process which arranges the documents according to their user query relevance. Lot of work has been done by commercial search engine organizations to make searching a rewarding experience to the users. One such area is to know the user intention behind the queries that is being given in the query interface. Bas

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Ruban ¹, Behin Sam ², Annapoorna Shetty ³

Affiliations
1 Department of Computer Science, Bharathiar University, Coimbatore - 641046, Tamil Nadu, IN
2 Department of Computer Science, Rajeswari Vedachalam Arts and Science College, Chengalpattu – 603001, Tamil Nadu, IN
3 Department of MCA, AIMIT, St Aloysius College, Mangalore – 575022, karnataka, IN

Abstract

The growth of the World Wide Web in the last two decades has posed a lot of challenges to the field of Information Retrieval. The way in which the information is collected, shared and searched is changed drastically. Searching information has never been so easy because of the search engines. Any Information Retrieval application has different components such as query handling where the user enters the user information need, Indexing part where the document representation is stored and maintained, the Ranking part which arranges the documents based on the relevance and the matching part which compares the query representation with the document representation. Most of the time since the user information need is not specified correctly, the documents that are retrieved may not be relevant or the relevant links may be less. Hence it is the challenge to be addressed by the search applications which can transform the original query into another representation which will be more responsive for the information retrieval. In this work we propose a hybrid framework which can be used to transform the original query representation to another representation which helps to retrieve more relevant results than the original representation. We further validate our point with an experiment we conducted.

Keywords

Information Retrieval, Ontology, Query Expansion, Query Refinement, Search Engine

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