With the emergence of various information access systems exhibiting increasing complexity,
there is a critical need for sound and scalable means of automatic evaluation. To address …

Eye-tracking research is beneficial for better understanding user behaviour in search
engines. The present paper presents a comprehensive narrative literature review of eye …

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 …

Learning to rank with biased click data is a well-known challenge. A variety of methods has
been explored to debias click data for learning to rank such as click models, result …

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 …

How to obtain an unbiased ranking model by learning to rank with biased user feedback is
an important research question for IR. Existing work on unbiased learning to rank (ULTR) …

Rankings, especially those in search and recommendation systems, often determine how
people access information and how information is exposed to people. Therefore, how to …

This paper aims to propose a methodology for measuring user experience (UX) by using
artificial intelligence-aided design (AIAD) technology in mobile application design. Unlike …

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 …

Satisfaction prediction is one of the prime concerns in search performance evaluation. It is a
non-trivial task for two major reasons:(1) The definition of satisfaction is rather subjective and …