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.
Weitere Kapitel dieses Buchs durch Wischen aufrufen
- Capturing Market Intelligence from Customer Feedback E-mails Using Self-enhancing Bolzmann Machine-Based Network of Knowledge Maps
N. Pradeep Kumar
- Springer Berlin Heidelberg
Neuer Inhalt/© ITandMEDIA