02630nab a22002777a 4500 OSt 20250205040358.0 250205b |||q||p| |||| 00| 0 eng d 1046-8188 JMCFI - Learning Resource Center Per. 005.3'050 As849 2017 No.3/ V35 Liu, Yiqun 9834 Time-awake click model / Yiqun Liu [and five others]. New York, NY : Association for Computing Machinery, 2017. volume 35, number 3, 16:1 - 16:14 pages ACM transaction on information systems. volume 35. Abstract : Click-through information is considered as a valuable source of users' implicit relevance feedback for commercial search engines. As existing studies have shown that the search result position in a search engine result page (SERP) has a very strong influence on users' examination behavior, most existing click models are position based, assuming that users examine results from top to bottom in a linear fashion. Although these click models have been successful, most do not take temporal information into account. As many existing studies have shown, click dwell time and click sequence information are strongly correlated with users' perceived relevance and search satisfaction. Incorporating temporal information may be important to improve performance of user click models for Web searches. In this article, we investigate the problem of properly incorporating temporal information into click models. We first carry out a laboratory eye-tracking study to analyze users' examination behavior in different click sequences and find that the user common examination path among adjacent clicks is linear. Next, we analyze the user dwell time distribution in different search logs and find that we cannot simply use a click dwell time threshold (e.g., 30 seconds) to distinguish relevant/irrelevant results. Finally, we propose a novel time-aware click model (TACM), which captures the temporal information of user behavior. We compare the TACM to several existing click models using two real-world search engine logs. Experimental results show that the TACM outperforms other click models in terms of both predicting click behavior (perplexity) and estimating result relevance (NDCG). Information systems Web searching and information discovery. 9835 Retrieval models and ranking. 9836 Xie, Xiaohui 9837 Wang, Chao 9838 Nie, Jan-Yun 9839 Zhang, Min 9840 Ma, Shaoping 9841 ddc PER. 0 3856 3856 0 0 ddc 0 1 REF JMC JMC Per. 2025-02-05 0 Per. 005.3'050 As849 2017 No.3/V35 Art00000001 2025-02-05 2025-02-05 PER.