Affiliation:
1. University of Rome Tor Vergata, Roma (Italy)
Abstract
Finding threads in textual dialogs is emerging as a need to better organize stored knowledge. We capture this need by introducing the novel task of discovering ongoing conversations in scattered dialog blocks. Our aim in this article is twofold. First, we propose a publicly available testbed for the task by solving the insurmountable problem of privacy of Big Personal Data. In fact, we showed that personal dialogs can be surrogated with theatrical plays. Second, we propose a suite of computationally light learning models that can use syntactic and semantic features. With this suite, we showed that models for this challenging task should include features capturing shifts in language use and, possibly, modeling underlying scripts.
Publisher
Association for Computing Machinery (ACM)
Subject
Artificial Intelligence,Human-Computer Interaction
Reference57 articles.
1. Whatsapp, Skype, Wickr, Viber, Twitter and Blog are ready to asymptote globally from all corners during communications in latest fast life;Aal Limbesh B.;Research Journal of Science and Technology,2014
2. Who Sets E-Mail Style? Prescriptivism, Coping Strategies, and Democratizing Communication Access
3. Distributional Memory: A General Framework for Corpus-Based Semantics
4. Learning Deep Architectures for AI
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