Scalable Internet resource discovery: research problems and approaches
Communications of the ACM
Map displays for information retrieval
Journal of the American Society for Information Science
A smart itsy bitsy spider for the web
Journal of the American Society for Information Science - Special topic issue: artificial intelligence techniques for emerging information systems applications
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
MetaSpider: meta-searching and categorization on the Web
Journal of the American Society for Information Science and Technology
Mining a web citation database for author co-citation analysis
Information Processing and Management: an International Journal
Automatic Topic Identification Using Webpage Clustering
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
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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.