Temporal information retrieval has been a topic of great interest in recent years. Its purpose
is to improve the effectiveness of information retrieval methods by exploiting temporal …

Information seeking is a fundamental human activity. In the modern world, it is frequently
conducted through interactions with search systems. The retrieval and comprehension of …

The results of the learning to rank challenge showed that the quality of the predictions from
the top competitors are very close from each other. This raises a question: is learning to rank …

Over the past few years, major web search engines have introduced knowledge bases to
offer popular facts about people, places, and things on the entity pane next to regular search …

A large amount of social feedback expressed by social signals (eg like,+ 1, rating) are
assigned to web resources. These signals are often exploited as additional sources of …

In this paper, we extensively study the impact of social signals (users' actions) obtained from
several social networks on search ranking task. Social signals associated with web …

With the advent of Web search and the large amount of data published on the Web sphere, a
tremendous amount of documents become strongly time-dependent. In this respect, the time …

Traditional machine-learned ranking systems for Web search are often trained to capture
stationary relevance of documents to queries, which have limited ability to track …

Relevance estimation of a Web resource (document) can benefit from using social signals.
In this paper, we propose a language model document prior exploiting temporal …

A call to redirect the intellectual focus of information retrieval and science (IR&S) toward the
phenomenon of technology-mediated experience. In this book, Sachi Arafat and Elham …