Voice-controlled intelligent personal assistants, such as Cortana, Google Now, Siri and
Alexa, are increasingly becoming a part of users' daily lives, especially on mobile devices …

In learning-to-rank for information retrieval, a ranking model is automatically learned from
the data and then utilized to rank the sets of retrieved documents. Therefore, an ideal …

There is a rapid growth in the use of voice-controlled intelligent personal assistants on
mobile devices, such as Microsoft's Cortana, Google Now, and Apple's Siri. They …

While in a classification or a regression setting a label or a value is assigned to each
individual document, in a ranking setting we determine the relevance ordering of the entire …

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 …

Web Search Engine Result Pages (SERPs) are complex responses to queries, containing
many heterogeneous result elements (web results, advertisements, and specialised" …

The results of information retrieval (IR) are usually presented in the form of a ranking list of
candidate documents, such as web search for humans and retrieval-augmented generation …

Relevance is a fundamental concept in information retrieval (IR) studies. It is however often
observed that relevance as annotated by secondary assessors may not necessarily mean …

Understanding and estimating satisfaction with search engines is an important aspect of
evaluating retrieval performance. Research to date has modeled and predicted search …

Information retrieval systems aim to help users satisfy information needs. We argue that the
goal of the person using the system, and the pattern of behavior that they exhibit as they …