ACM Transactions on Information Systems

Conversational information retrieval is a relatively new and fast-developing research area, but conversation itself has been well studied for decades. Researchers have analysed linguistic phenomena such as structure and semantics but also paralinguistic ...

Static recommendation methods like collaborative filtering suffer from the inherent limitation of performing real-time personalization for cold-start users. Online recommendation, e.g., multi-armed bandit approach, addresses this limitation by ...

Recent observational studies highlight the importance of considering the interactions between users in the group recommendation process, but to date their integration has been marginal. In this article, we propose a collaborative model based on the social ...

Chatbots or conversational recommenders have gained increasing popularity as a new paradigm for Recommender Systems (RS). Prior work on RS showed that providing explanations can improve transparency and trust, which are critical for the adoption of RS. ...

The consistency of a response to a given post at the semantic level and emotional level is essential for a dialogue system to deliver humanlike interactions. However, this challenge is not well addressed in the literature, since most of the approaches ...

Building an intelligent dialogue system with the ability to select a proper response according to a multi-turn context is challenging in three aspects: (1) the meaning of a context–response pair is built upon language units from multiple granularities (...

Existing multi-turn context-response matching methods mainly concentrate on obtaining multi-level and multi-dimension representations and better interactions between context utterances and response. However, in real-place conversation scenarios, whether a ...

In this article, we present MyrrorBot, a personal digital assistant implementing a natural language interface that allows the users to: (i) access online services, such as music, video, news, andfood recommendations, in a personalized way, by exploiting a ...

In this article, we address the problem of answering complex information needs by conducting conversations with search engines, in the sense that users can express their queries in natural language and directly receive the information they need from a ...

Conversational search plays a vital role in conversational information seeking. As queries in information seeking dialogues are ambiguous for traditional ad hoc information retrieval (IR) systems due to the coreference and omission resolution problems ...

Conversational search is a relatively young area of research that aims at automating an information-seeking dialogue. In this article, we help to position it with respect to other research areas within conversational artificial intelligence (AI) by ...

The exchange of meta-information has always formed part of information behavior. In this article, we show that this rule also extends to conversational search. Information about the user’s information need, their preferences, and the quality of search ...

As conversational agents like Siri and Alexa gain in popularity and use, conversation is becoming a more and more important mode of interaction for search. Conversational search shares some features with traditional search, but differs in some important ...

Conversational search systems, such as Google assistant and Microsoft Cortana, enable users to interact with search systems in multiple rounds through natural language dialogues. Evaluating such systems is very challenging, given that any natural language ...

In the Internet of Things era, users are willing to personalize the joint behavior of their connected entities, i.e., smart devices and online service, by means of trigger-action rules such as “IF the entrance Nest security camera detects a movement, THEN ...

Conversational systems now attract great attention due to their promising potential and commercial values. To build a conversational system with moderate intelligence is challenging and requires big (conversational) data, as well as interdisciplinary ...