- Full Description
Due to the lack of a uniform schema for Web documents and the sheer amount and dynamics of Web data, both the effectiveness and the efficiency of information management and retrieval of Web data is often unsatisfactory when using conventional data management techniques. Web community, defined as a set of Web-based documents with its own logical structure, is a flexible and efficient approach to support information retrieval and to implement various applications. Zhang and his co-authors explain how to construct and analyse Web communities based on information like Web document contents, hyperlinks, or user access logs. Their approaches combine results from Web search algorithms, Web clustering methods, and Web usage mining. They also detail the necessary preliminaries needed to understand the algorithms presented, and they discuss several successful existing applications. Researchers and students in information retrieval and Web search find in this all the necessary basics and methods to create and understand Web communities. Professionals developing Web applications will additionally benefit from the samples presented for their own designs and implementations.
- Table of Contents
Table of Contents
- HITS and Related Algorithms.
- Page Rank Related Algorithms.
- Web Clustering Approaches.
- Building Web Community.
- Web Community Related Techniques.
If you think that you've found an error in this book, please let us know by emailing to email@example.com . You will find any confirmed erratum below, so you can check if your concern has already been addressed. No errata are currently published