Optimized Mobile Search Engine Using Click-Through Data
Subtitle: ICIEMS 2014
Publisher: Association of Scientists, Developers and Faculties
Published: 2014
Place of publication: India
Language: eng
Format: Paperback
Number of pages: 487
ISBN-13: 9788192523330
Description: Data mining is a system employing for more computer learning technique to automatically analyse and extracting knowledge from data stored in the database. The goal of data mining is to extract hidden predictive information from database. This paper make use of data mining concept for collecting user’s multiple preference from click through data. we propose a personalized mobile search engine (PMSE) that captures the users’ preferences in the form of concepts by mining their click through data. Due to the importance of location information in mobile search, PMSE classifies these concepts into content concepts and location concepts. In addition, users’ locations (positioned by GPS) are used to represent the location concepts in PMSE. The user preferences are organized in an ontology-based, multi facet user profile, which are used to adapt a personalized ranking function for rank adaptation of future search results. To characterize the diversity of the concepts associated with a query and their relevance to the user’s need. based on the client-server model, we also present a detailed architecture and design for implementation of PMSE. In our design, the client collects and stores locally the click through data to protect privacy, whereas heavy tasks such as concept extraction, training, and reranking are performed at the PMSE server. Moreover, we prototype PMSE on the Google Android platform.