Alongside huge volumes of research on deep learning models in NLP in the recent years,
there has been much work on benchmark datasets needed to track modeling progress …

The advent of recent Natural Language Processing technology has led human and machine
interactions more toward conversation. In Conversational Search Systems (CSS) like …

Conversational information seeking (CIS) is concerned with a sequence of interactions
between one or more users and an information system. Interactions in CIS are primarily …

Recommender systems typically retrieve items from an item corpus for personalized
recommendations. However, such a retrieval-based recommender paradigm faces two …

Users often fail to formulate their complex information needs in a single query. As a
consequence, they may need to scan multiple result pages or reformulate their queries …

Ranking models lie at the heart of research on information retrieval (IR). During the past
decades, different techniques have been proposed for constructing ranking models, from …

In this paper, we survey the methods and concepts developed for the evaluation of dialogue
systems. Evaluation, in and of itself, is a crucial part during the development process. Often …

Search queries are often short, and the underlying user intent may be ambiguous. This
makes it challenging for search engines to predict possible intents, only one of which may …

Conversational search is an emerging topic in the information retrieval community. One of
the major challenges to multi-turn conversational search is to model the conversation history …

Conversational search is one of the ultimate goals of information retrieval. Recent research
approaches conversational search by simplified settings of response ranking and …