Location based Web Object Search using Probabilistic Classification Model.

Abstract

The classical Web search engines focus on satisfying the information need of the users by retrieving relevant Web documents corresponding to the user query. The Web document contains the information on different Web objects such as authors, automobiles, political parties e.t.c. The user might be accessing the Web document to procure information about a specific Web object, the remaining information in the Web object [2-6] becomes redundant specific to the user. If the size of Web documents is significantly large and the user information requirement is small fraction of the document, the user has to invest effort in locating the required information inside the document. It would be much more convenient if the user is provided with only the required Web object information located inside the Web documents. Web object search engines provide Web search facility through vertical search on Web objects. In this paper the main goal we considered is the objective information present in different documents is extracted and integrated into an object repository over which the Web object search facility is built.