Abstract

To improve the information retrieval system for user, programmers have to learn a user's preferences accurately. In order to optimize retrieval accuracy, modeling the users appropriately based on their preferences and personalizing search according to each individual user are important. Implicit feedback information improves the user modeling process. The advantage of implicit modeling is effectively improving the user model without extra effort of user. Several implicit feedback features are used to develop user modeling process. We present a new model to find a user's preferences from click through behavior and using the exposed preferences to adapt the search engine's ranking function for improving search service. In this proposed model, the combination of viewed and stored document summaries is used.

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