Open AccessAutomatic Query Reformulation Using Classification in Web Searching
Author(s) -
R. M. Suresh,
Kurmachalam Ajay Kumar
Publication year - 2012
Publication title -
international journal of computer science and informatics
Language(s) - English
Resource type - Journals
ISSN - 2231-5292
DOI - 10.47893/ijcsi.2012.1052
Subject(s) - web query classification , computer science , web search query , query expansion , query optimization , information retrieval , sargable , query language , spatial query , set (abstract data type) , class (philosophy) , rdf query language , task (project management) , result set , perspective (graphical) , search engine , data mining , artificial intelligence , management , economics , programming language
The search query is a set of words or phrases a user enters when looking for information on a specific topic or subject. Formulating a search query is a challenging task for most of users because they are required to express their anomalous states of knowledge. In the query reformulation stage, users modify their initial queries and submit new ones that more accurately reflect their information needs. Classification and Prediction are two forms of query analysis that can be used to extract models describing frequently used query classes or to predict the reformulation for the query.. An ideal solution might be that the system automatically generates a concise and informative summary for each perspective of the query. In our approach a model is constructed by analyzing queries described by the frequency of search, query is assumed to belong to a predefined class.