Conversational Exploratory Search via Interactive Storytelling

Conversational interfaces are likely to become more efficient, intuitive and engaging way for human-computer interaction than today's text or touch-based interfaces. Current research efforts concerning conversational interfaces focus primarily on question answering functionality, thereby neglecting support for search activities beyond targeted information lookup. Users engage in exploratory search when they are unfamiliar with the domain of their goal, unsure about the ways to achieve their goals, or unsure about their goals in the first place. Exploratory search is often supported by approaches from information visualization. However, such approaches cannot be directly translated to the setting of conversational search. In this paper we investigate the affordances of interactive storytelling as a tool to enable exploratory search within the framework of a conversational interface. Interactive storytelling provides a way to navigate a document collection in the pace and order a user prefers. In our vision, interactive storytelling is to be coupled with a dialogue-based system that provides verbal explanations and responsive design. We discuss challenges and sketch the research agenda required to put this vision into life.

[1]  Boyang Li,et al.  Learning knowledge to support domain-independent narrative intelligence , 2015 .

[2]  Tsung-Hsien Wen,et al.  Neural Belief Tracker: Data-Driven Dialogue State Tracking , 2016, ACL.

[3]  Gary Marchionini,et al.  Exploratory search , 2006, Commun. ACM.

[4]  Sebastian Neumaier,et al.  Talking Open Data , 2017, ESWC.

[5]  Brendan T. O'Connor,et al.  Learning Latent Personas of Film Characters , 2013, ACL.

[6]  Mirella Lapata,et al.  Modeling Local Coherence: An Entity-Based Approach , 2005, ACL.

[7]  Jürgen Umbrich,et al.  Lifting Data Portals to the Web of Data , 2017, LDOW@WWW.

[8]  Mirella Lapata,et al.  Plot Induction and Evolutionary Search for Story Generation , 2010, ACL.

[9]  Mark O. Riedl Computational Narrative Intelligence: A Human-Centered Goal for Artificial Intelligence , 2016, ArXiv.

[10]  Vitobha Munigala,et al.  "Let me convince you to buy my product ... ": A Case Study of an Automated Persuasive System for Fashion Products , 2017, ArXiv.

[11]  M. de Rijke,et al.  Information Processing and Management Investigating Queries and Search Failures in Academic Search , 2022 .

[12]  Jason Weston,et al.  ParlAI: A Dialog Research Software Platform , 2017, EMNLP.

[13]  Antoine Raux,et al.  The Dialog State Tracking Challenge Series: A Review , 2016, Dialogue Discourse.

[14]  Jianfeng Gao,et al.  Towards End-to-End Reinforcement Learning of Dialogue Agents for Information Access , 2016, ACL.

[15]  Filip Radlinski,et al.  A Theoretical Framework for Conversational Search , 2017, CHIIR.

[16]  Mark Sanderson,et al.  How Do People Interact in Conversational Speech-Only Search Tasks: A Preliminary Analysis , 2017, CHIIR.

[17]  Francis Ferraro,et al.  Visual Storytelling , 2016, NAACL.

[18]  Workshop on Linked Data on the Web co-located with 26th International World Wide Web Conference (WWW 2017) , 2017, LDOW@WWW.

[19]  Jason Weston,et al.  Learning End-to-End Goal-Oriented Dialog , 2016, ICLR.

[20]  Ryen W. White Interactions with Search Systems , 2016 .

[21]  Ryen W. White,et al.  Exploratory Search: Beyond the Query-Response Paradigm , 2009, Exploratory Search: Beyond the Query-Response Paradigm.

[22]  Daniele Quercia,et al.  Auralist: introducing serendipity into music recommendation , 2012, WSDM '12.

[23]  Mark O. Riedl,et al.  Event Representations for Automated Story Generation with Deep Neural Nets , 2017, AAAI.

[24]  Marti A. Hearst Search User Interfaces , 2009 .

[25]  Daniel McDuff,et al.  MISC: A data set of information-seeking conversations , 2017 .

[26]  M. de Rijke,et al.  Evaluating Personal Assistants on Mobile devices , 2017, ArXiv.