Ranking a set of retrieved documents according to their relevance to a given query has become a popular problem at the intersection of web search, machine learning, and informatio...
Two-sided markets arise when two different types of users may realize gains by interacting with one another through one or more platforms or mediators. We initiate a study of the...
Web search engines are traditionally evaluated in terms of the relevance of web pages to individual queries. However, relevance of web pages does not tell the complete picture, si...
Presence of duplicate documents in the World Wide Web adversely affects crawling, indexing and relevance, which are the core building blocks of web search. In this paper, we pres...
Hema Swetha Koppula, Krishna P. Leela, Amit Agarwa...
Recent advances in click model have positioned it as an attractive method for representing user preferences in web search and online advertising. Yet, most of the existing works f...
Zeyuan Allen Zhu, Weizhu Chen, Tom Minka, Chenguan...
As the Web provides rich data embedded in the immense contents inside pages, we witness many ad-hoc efforts for exploiting fine granularity information across Web text, such as We...
There has been a large amount of research on efficient document retrieval in both IR and web search areas. One important technique to improve retrieval efficiency is early termina...
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 ...
In information retrieval, relevance of documents with respect to queries is usually judged by humans, and used in evaluation and/or learning of ranking functions. Previous work ha...
Jingfang Xu, Chuanliang Chen, Gu Xu, Hang Li, Elbi...