Structural analysis of hypertexts: identifying hierarchies and useful metrics
ACM Transactions on Information Systems (TOIS)
Automatic structuring and retrieval of large text files
Communications of the ACM
Interactive clustering for navigating in hypermedia systems
ECHT '94 Proceedings of the 1994 ACM European conference on Hypermedia technology
HyPursuit: a hierarchical network search engine that exploits content-link hypertext clustering
Proceedings of the the seventh ACM conference on Hypertext
User-oriented document clustering: a framework for learning in information retrieval
Proceedings of the 9th annual international ACM SIGIR conference on Research and development in information retrieval
Cut as a querying unit for WWW, Netnews, and E-mail
Proceedings of the ninth ACM conference on Hypertext and hypermedia : links, objects, time and space---structure in hypermedia systems: links, objects, time and space---structure in hypermedia systems
Recent Studies in Automatic Text Analysis and Document Retrieval
Journal of the ACM (JACM)
Search and Ranking Algorithms for Locating Resources on the World Wide Web
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
A SOM-Based Information Organizer for Text and Video Data
Proceedings of the Fifth International Conference on Database Systems for Advanced Applications (DASFAA)
Defining logical domains in a web site
HYPERTEXT '00 Proceedings of the eleventh ACM on Hypertext and hypermedia
Text Retrieval Systems for the Web
Programming and Computing Software
Automating extraction of logical domains in a web site
Data & Knowledge Engineering
ADBIS-DASFAA '00 Proceedings of the East-European Conference on Advances in Databases and Information Systems Held Jointly with International Conference on Database Systems for Advanced Applications: Current Issues in Databases and Information Systems
Improving web search by the identification of contextual information
Intelligent exploration of the web
An extensive study on automated Dewey Decimal Classification
Journal of the American Society for Information Science and Technology
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In this paper, we propose an effective classification view mechanism for hypertext data such as web documents based on Kohonen's Self-Organizing Map (SOM) and search engines. Web documents collected by search engines are automatically classified by SOM and the obtained SOMs are incrementally modified according to the interaction between users and SOMs. At present, various search engines are designed to retrieve web documents. When we use search engines to retrieve web documents, we get a lot of answers as ever before, so we have a lot of labors to examine each web document. Therefore, in order to make up for search engines, we need a function to classify web document corresponding to the user's point of view and their purposes. Furthermore, we cannot retrieve pertinent web documents by conventional search engines when a specific topic is described by more than one web document. To solve these problems, we exploited a content-based clustering system for web documents. In this system, web documents are automatically clustered by their feature vectors produced from web documents or minimal subgraphs consisting of multiple web documents, and their overview maps are dynamically generated by SOM. Furthermore, we propose a method by which an obtained SOM is modified by user's interaction such as feedback operations. It is important to reflect the aim of classification and the purpose of retrieval to this system. In our research, we intend to solve these problems by providing a view mechanism in which the Basic Units for retrieval and clustering of Web Documents (BUWDs) are changeable by users and relevance feedback operations enable the generation of an overview map which reflects user needs.