Most click models focus on user behaviors towards a single list. However, with the
development of user interface (UI) design, the layout of displayed items on a result page …

Context such as the user's search history, demographics, devices, and surroundings, has
become prevalent in various domains of information seeking and retrieval such as mobile …

Users' click-through behavior is considered as a valuable yet noisy source of implicit
relevance feedback for web search engines. A series of click models have therefore been …

Click behavior is a typical user behavior in the web search. How to capture and model users'
click behavior has always been a common research topic. However, there are few review …

This chapter introduces, in Sect. 1.1, the area of research and development of Mobile
Information Retrieval. In Sect. 1.2 it gives the motivation for this review and explains briefly …

A series of click models has been proposed to extract accurate and unbiased relevance
feedback from valuable yet noisy click-through data in search logs. Previous works have …

Reading is a vital and complex cognitive activity during users' information-seeking process.
Several studies have focused on understanding users' reading behavior in desktop search …

The existing evaluation approaches for search engines usually measure and estimate the
utility or usefulness of search results by either the explicit relevance annotations from …

Relevance judgments are essential for designing information retrieval systems. Traditionally,
judgments have been gathered via desktop interfaces. However, with the rise in popularity of …

Crowdsourcing has become an alternative approach to collect relevance judgments at large
scale. In this thesis, we focus on some specific aspects related to time, scale, and …