Meeting support by visualizing discussion structure and semantics

Fujita, Kunihiko; Nishimoto, Katsutaro; Sumi, Y.; Kunifuji, Susumu; Mase, Kenji

doi:10.1109/kes.1998.725879

Cited by 4 publications

(1 citation statement)

References 4 publications

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“…Previous work on visualising argumentation has mainly been driven by the need for tools to improve the quality of discussions in real-time meetings (Fujita, Nishimoto, Sumi, Kunifuji and Mase 1998;Bachler, Shum, Roure, Michaelides and Page 2003;Rienks et al 2005;Buckingham Shum et al 2006;Michaelides et al 2006). Some research has also addressed the use of such visualisations for browsing past conversations, and end-user evaluations have been positive with respect to impact in retrieval effectiveness Ailomaa and Rajman 2009).…”

Section: Conversation Graphsmentioning

confidence: 99%

Automatic argumentative analysis for interaction mining

Pallotta¹,

Delmonte

2011

Argument & Computation

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Interaction mining is about discovering and extracting insightful information from digital conversations, namely those human-human information exchanges mediated by digital network technology. We present in this article a computational model of natural arguments and its implementation for the automatic argumentative analysis of digital conversations, which allows us to produce relevant information to build interaction business analytics applications overcoming the limitations of standard text mining and information retrieval technology. Applications include advanced visualisations and abstractive summaries.

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Section: Conversation Graphsmentioning

confidence: 99%