MARS: Applying Multiplicative Adaptive User Preference Retrieval to Web Search

Mars: Multiplicative Adaptive Refinement Web Search

This chapter reports the project MARS (Multiplicative Adaptive Refinement Search), which applies a new multiplicative adaptive algorithm for user preference retrieval to Web search. The new algorithm uses a multiplicative query expansion strategy to adaptively improve and reformulate the query vector to learn users’ information preference. The algorithm has provable better performance than the ...

Multiplicative Adaptive Refinement Web Search

This chapter reports the project MARS (Multiplicative Adaptive Refinement Search), which applies a new multiplicative adaptive algorithm for user preference retrieval to Web searches. The new algorithm uses a multiplicative query expansion strategy to adaptively improve and reformulate the query vector to learn users’ information preference. The algorithm has provable better performance than th...

Personalized Information Retrieval by Using Adaptive User Profiling and Collaborative Filtering

Many search engines such as Yahoo, Google, MSN, and AltaVista, have been developed to meet various users’ search needs in real world. In general, because of the lack of the personal information such as hobby, preferences, and interests, these existing information retrieval systems are unsuitable to provide personalized search results to users. In this paper, we propose an adaptive user profilin...

Multiplicative Adaptive Algorithms for User Preference Retrieval

Managing XML Retrieval through Personalization Using Search Engine

The number of resources of information has increased significantly and Information Retrieval (IR) based on keyword in web has become very significant.XML has become the widely used format for sharing of information. As the number of resources of information has increased significantly and retrieval of correct data according to user preference may not be achieved efficiently. In order to improve...