Recommendation is a prevalent and critical service in information systems. To provide
personalized suggestions to users, industry players embrace machine learning, more …

The ubiquity of implicit feedback makes them the default choice to build online
recommender systems. While the large volume of implicit feedback alleviates the data …

Many internet companies, such as Yahoo, Facebook, Google and Twitter, rely on content
recommendation systems to deliver the most relevant content items to individual users …

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 explosive popularity of e-commerce sites has reshaped users» shop** habits and an
increasing number of users prefer to spend more time shop** online. This evolution …

In information retrieval, query auto completion (QAC), also known as typeahead [**ao et al.,
2013, Cai et al., 2014b] and auto-complete suggestion [Jain and Mishne, 2010], refers to the …

Voice-activated intelligent assistants, such as Siri, Google Now, and Cortana, are prevalent
on mobile devices. However, it is challenging to evaluate them due to the varied and …

Modeling user interest is critical for accurate news recommendation. Existing news
recommendation methods usually infer user interest from click behaviors on news. However …

User satisfaction depicts the effectiveness of a system from the user's perspective.
Understanding and predicting user satisfaction is vital for the design of user-oriented …

Search satisfaction is defined as the fulfillment of a user's information need. Characterizing
and predicting the satisfaction of search engine users is vital for improving ranking models …