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Interaction Mining: Making Business Sense of Customers Conversations through Semantic and Pragmatic Analysis
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Author(s): Vincenzo Pallotta (Webster University, Switzerland), Lammert Vrieling (Webster University, Switzerland)and Rodolfo Delmonte (Università “Ca Foscari”, Italy)
Copyright: 2012
Pages: 25
Source title:
Business Intelligence Applications and the Web: Models, Systems and Technologies
Source Author(s)/Editor(s): Marta E. Zorrilla (University of Cantabria, Spain), Jose-Norberto Mazón (University of Alicante, Spain), Óscar Ferrández (University of Alicante, Spain), Irene Garrigós (University of Alicante, Spain), Florian Daniel (University of Trento, Italy)and Juan Trujillo (University of Alicante, Spain)
DOI: 10.4018/978-1-61350-038-5.ch006
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Abstract
In this chapter we present the major challenges of a new trend in business analytics, namely Interaction Mining. With the proliferation of unstructured data as the result of people interacting with each other using digital networked devices, classical methods in text business analytics are no longer effective. We identified the causes of their failure as being related to the inadequacy of dealing with conversational data. We propose then to move from Text Mining towards Interaction Mining, and we make several cases for this transition in areas such as marketing research, social media analytics, and customer relationship management. We also propose a roadmap for the future development of Interaction Mining by challenging the current practices in business intelligence and information visualization.
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