With the rapid growth of web search in recent years the problem of modeling its users has
started to attract more and more attention of the information retrieval community. This has …

Prior research on exposure fairness in the context of recommender systems has focused
mostly on disparities in the exposure of individual or groups of items to individual users of …

Recommender Systems have been playing essential roles in e-commerce portals. Existing
recommendation algorithms usually learn the ranking scores of items by optimizing a single …

Understanding user browsing behavior in web search is key to improving web search
effectiveness. Many click models have been proposed to explain or predict user clicks on …

Online evaluation is one of the most common approaches to measure the effectiveness of an
information retrieval system. It involves fielding the information retrieval system to real users …

The ability to make accurate predictions relating to consumer preferences is a key factor of a
digital firm's success. Examples include targeted advertisements and, more broadly …

Search engine retrieval effectiveness studies are usually small scale, using only limited
query samples. Furthermore, queries are selected by the researchers. We address these …

Click signal has been widely used for designing and evaluating interactive information
systems, which is taken as the indicator of user preference. However, click signal does not …

Many web systems rank and present a list of items to users, from recommender systems to
search and advertising. An important problem in practice is to evaluate new ranking policies …

Search engines are widely used in our daily life. Batch evaluation of the performance of
search systems to their users has always been an essential issue in the field of information …