Abstract
With the proliferation of the Web, capture of market intelligence data has become more difficult in reality from the system’s point of view, as data sources on the web are voluminous, heterogeneous in terms of structures and semantics, and some part of it may be irrelevant to a specific organizations’ marketing decision making context, which is the primary premises of market intelligence (MI) systems. To address these requirements of MI, we are proposing a method for creating an MI network using customer feedback messages and e-mails as inputs. We have proposed the use of knowledge map (KM) method for representing textual and unstructured resources as a network using KMs and clustering and then incrementally enhance itself as the new customer e-mails keep coming. At last, we have proposed a self-enhancing network using Bolzmann Machines concept where the new messages are treated as new hypotheses, and they get absorbed into the MI network based on their similarity values.
An erratum to this chapter can be found at http://dx.doi.org/10.1007/11604655_68
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© 2005 Springer-Verlag Berlin Heidelberg
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Kumar, N.P., Bandopadhyay, T. (2005). Capturing Market Intelligence from Customer Feedback E-mails Using Self-enhancing Bolzmann Machine-Based Network of Knowledge Maps. In: Chakraborty, G. (eds) Distributed Computing and Internet Technology. ICDCIT 2005. Lecture Notes in Computer Science, vol 3816. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11604655_62
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DOI: https://doi.org/10.1007/11604655_62
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30999-4
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