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 on-going conversations in scattered dialog blocks. Our aim in this paper 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.

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.

Zanzotto, F.m., & Ferrone, L. (2017). Have you lost the thread? Discovering ongoing conversations in scattered dialog blocks. ACM TRANSACTIONS ON INTERACTIVE INTELLIGENT SYSTEMS, 7(2) [10.1145/2885501].

Have you lost the thread? Discovering ongoing conversations in scattered dialog blocks

ZANZOTTO, FABIO MASSIMO;FERRONE, LORENZO
2017

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 on-going conversations in scattered dialog blocks. Our aim in this paper 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.
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore INF/01 - Informatica
Settore ING-INF/05 - Sistemi di Elaborazione delle Informazioni
English
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.
Big Personal Data; Provacy;
http://tiis.acm.org/
Zanzotto, F.m., & Ferrone, L. (2017). Have you lost the thread? Discovering ongoing conversations in scattered dialog blocks. ACM TRANSACTIONS ON INTERACTIVE INTELLIGENT SYSTEMS, 7(2) [10.1145/2885501].
Zanzotto, Fm; Ferrone, L
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2108/159326
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