In this paper, we propose a semi-supervised learning approach for classifying program (bot) generated web search traffic from that of genuine human users. The work is motivated by...
Hongwen Kang, Kuansan Wang, David Soukal, Fritz Be...
In this paper, we propose to mine query hierarchies from clickthrough data, which is within the larger area of automatic acquisition of knowledge from the Web. When a user submits...
Dou Shen, Min Qin, Weizhu Chen, Qiang Yang, Zheng ...
In this paper, we study search bot traffic from search engine query logs at a large scale. Although bots that generate search traffic aggressively can be easily detected, a large ...
The paper proposes identifying relevant information sources from the history of combined searching and browsing behavior of many Web users. While it has been previously shown that...
This paper is concerned with actively predicting search intent from user browsing behavior data. In recent years, great attention has been paid to predicting user search intent. H...