Journal Information
Journal of the Association for Information Science and Technology (JASIST)
http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2330-1643
Impact Factor:
2.322
Publisher:
John Wiley & Sons
ISSN:
2330-1643
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441
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Call For Papers
The Journal of the Association for Information Science and Technology (JASIST) is a leading international forum for peer-reviewed research in information science. For more than half a century, JASIST has provided intellectual leadership by publishing original research that focuses on the production, discovery, recording, storage, representation, retrieval, presentation, manipulation, dissemination, use, and evaluation of information and on the tools and techniques associated with these processes.

The Journal welcomes rigorous work of an empirical, experimental, ethnographic, conceptual, historical, socio-technical, policy-analytic, or critical-theoretical nature. JASIST also commissions in-depth review articles (“Advances in Information Science”) and reviews of print and other media.

Keywords

ASIST, Digital Library, information science, information technology, computer science, generation, recording, information distribution, information storage, information representation, information retrieval, information dissemination, text analysis.

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Last updated by Dou Sun in 2017-06-18
Special Issues
Special Issue on Conversational Approaches to Information Retrieval
Submission Date: 2018-02-23

Conversational search interfaces are increasingly common and include intelligent mobile assistants such as Cortana, Google Now, and Siri; intelligent home assistants such as Amazon Alexa and Google Home; and a myriad of different software agents (or Chatbots) that users can interact with inside messaging platforms such as Slack, Yammer, and Facebook Workplace. Conversational search systems are different from traditional search systems in several ways. First, at their core, conversational search systems aim to support multi-turn, user-machine dialogues for information access and retrieval. Second, some systems aim to engage users in more naturalistic interactions, for example, by supporting spoken, natural language information requests. Finally, some systems aim to support multi-modal interaction, for example by allowing either textual or verbal input and by balancing between screen and verbal output. Prior and current research in the fields of information retrieval, information science, and humancomputer interaction is certainly relevant to the design, development, and evaluation of conversational search systems. From the system side, for example, prior research has focused on improving voice query recognition and on automatically reducing verbose queries in order to improve retrieval performance. From the human side, prior research has focused on understanding voice query reformulations in response to a system error, understanding why and how users switch modalities (e.g., textual versus spoken input), and developing methods for intelligent assistant evaluation. While different aspects of conversational search systems have been investigated in prior work, many open questions remain. How can systems use dialogue to support information access and retrieval? How can existing technologies such as query suggestion, results clustering, and relevant facet prediction be used in conversational approaches to IR? What do users want from a conversational search interface? How can a system infer user satisfaction from conversational interactions? In this Special Issue, we invite submissions on all aspects of conversational approaches to information access and retrieval. We invite submissions addressing all modalities of conversation, including speechbased, text-based, and multimodal interaction. We also welcome studies of human-human interaction (e.g., collaborative search) that can inform the design of conversational search applications. Finally, we welcome research on methods for evaluation of conversational IR systems. Topics of Interests Query understanding and search process management ● Processing verbose natural language queries ● Processing noisy ASR queries ● Query intent disambiguation, clarification, confirmation ● Query suggestion ● Relevance feedback in conversational search ● Voice-based search engine operations ● Dialogue schema for conversational search Search result description (presentation) ● Audio-based search result presentation and summarization ● Conversational navigation of search results ● Knowledge graph presentation in conversational ● Search Advertisements in audio-based search result presentation Ranking algorithms ● Ad-hoc spoken search ● Spoken search in session ● Search result diversification Evaluation ● Building test collections for conversational search ● Development of new metrics to measure effectiveness, engagement, satisfaction of conversational search Applications ● Intelligent personal assistance ● Intelligent home assistance using voice /speech oriented devices ● Proactive search/Recommendation ● Collaborative search ● Hands free search (e.g., in car, kitchen) ● Search for visually impaired users ● Search for low literacy users ● Integration with existing technologies
Last updated by Dou Sun in 2017-09-23
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