Identifying aggregates in hypertext structures
HYPERTEXT '91 Proceedings of the third annual ACM conference on Hypertext
HyPursuit: a hierarchical network search engine that exploits content-link hypertext clustering
Proceedings of the the seventh ACM conference on Hypertext
Focus+context views of World-Wide Web nodes
HYPERTEXT '97 Proceedings of the eighth ACM conference on Hypertext
Latent semantic indexing: a probabilistic analysis
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Improved algorithms for topic distillation in a hyperlinked environment
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Automatic resource compilation by analyzing hyperlink structure and associated text
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Finding related pages in the World Wide Web
WWW '99 Proceedings of the eighth international conference on World Wide Web
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Constructing good quality web page communities
ADC '02 Proceedings of the 13th Australasian database conference - Volume 5
Utilizing hyperlink transitivity to improve web page clustering
ADC '03 Proceedings of the 14th Australasian database conference - Volume 17
Effectively Finding Relevant Web Pages from Linkage Information
IEEE Transactions on Knowledge and Data Engineering
Efficiently Mining Gene Expression Data via a Novel Parameterless Clustering Method
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Hi-index | 0.00 |
The rapid development of network technologies has made the web a huge information source with its own characteristics. In most cases, traditional database-based technologies are no longer suitable for web information processing and management. For effectively processing and managing web information, it is necessary to reveal intrinsic relationships/structures among concerned web information objects such as web pages. In this work, a set of web pages that have their intrinsic relationships is called a web page community. This paper proposes a matrix-based model to describe relationships among concerned web pages. Based on this model, intrinsic relationships among pages could be revealed, and in turn a web page community could be constructed. The issues that are related to the application of the model are deeply investigated and studied. The concepts of community and intrinsic relationships, as well as the proposed matrix-based model, are then extended to other application areas such as biological data processing. Some application cases of the model in a broad range of areas are presented, demonstrating the potentials of this matrix-based model.