A Probabilistic Model for Information Retrieval by Mining User Behaviors

作者：Cai, Fei^*; Chen, Honghui

来源：Cognitive Computation, 2016, 8(3): 494-504.

DOI：10.1007/s12559-015-9377-1

• Probabilistic model
• Information retrieval
• Information access
• User behavior analysis

A query submitted to a search engine provides limited information about the searcher's real search intent. Alternatively, other information from user's historical behaviors, e.g., clicks and dwell time, can provide a strong clue to identify the search purpose. In this paper, we: (1) investigate the impact of distributions of users and queries on reranking documents that are initially returned by a search engine; (2) perform tests for all users, i.e., both seen and unseen users in the training period. For unseen users, we explore the knowledge from their similar users seen in the training period. Our experiments show that integration of information from user behavior and document with an optimal weight outperforms combinations with a fixed tradeoff. On average, our model achieves near 3 % improvements than the best baseline approach in terms of metrics, e.g., MAP, P@K and NDCG@K.

• 出版日期2016-6
• 单位中国人民解放军国防科学技术大学