Mining long-term search history to improve search accuracy
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Evaluating the accuracy of implicit feedback from clicks and query reformulations in Web search
ACM Transactions on Information Systems (TOIS)
An experimental comparison of click position-bias models
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
A user browsing model to predict search engine click data from past observations.
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Efficient multiple-click models in web search
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Click chain model in web search
Proceedings of the 18th international conference on World wide web
Improving searcher models using mouse cursor activity
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
| Hi-index | 0.00 |
User click behaviors reflect his preference in Web search processing objectively, and it is very important to give a proper interpretation of user click for improving search results. Previous click models explore the relationship between user examines and latent clicks web document obtained by search result page via multiple-click model, such as the independent click model(ICM) or the dependent click model(DCM), which the examining-next probability only depends on the current click. However, user examination on a search result page is a continuous and relevant procedure. In this paper, we attempt to explore the historical clicked data using a probability click tracking model(PCTM). In our approach, the examine-next probability is decided by the click variables of each clicked result. We evaluate the proposed model on a real-world data set obtained from a commercial search engine. The experiment results illustrate that PCTM can achieve the competitive performance compared with the existing click models under standard metrics.