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Web Communities Analysis and Construction

51,99 €

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

08.12.2005

Abbildungen

28 schwarzweisse Abbildungen, IX, 28 illus.

Verlag

Springer Berlin

Seitenzahl

187

Maße (L/B/H)

24,1/16/1,7 cm

Gewicht

471 g

Auflage

2006

Sprache

Englisch

ISBN

978-3-540-27737-8

Beschreibung

Rezension

The book can be used by applied mathematicians, search industry professionals, and anyone who wants to learn more about how search engines work. I recommend it for any course on Web information retrieval. I firmly believe that this book and the book by Langville and Meyer are the top two books about the algorithmic aspects of modern search engines.
(Yannis Manolopoulos, Aristotle University, Thessaloniki, Greece in ACM REVIEWS)

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

08.12.2005

Abbildungen

28 schwarzweisse Abbildungen, IX, 28 illus.

Verlag

Springer Berlin

Seitenzahl

187

Maße (L/B/H)

24,1/16/1,7 cm

Gewicht

471 g

Auflage

2006

Sprache

Englisch

ISBN

978-3-540-27737-8

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Web Communities
  • Produktbild: Web Communities

  • Chapter 1: Introduction (10 pages) -- Web Search, -- Information Filtering -- Web Community Chapter 2: Preliminaries (30 pages) -- Statistics -- Similarity -- Markov Model -- Matrix Expression of Hyperlinks -- Eigenvector, Principle Engenvector, Secondary Engenvector -- Singular Value Decomposition (SVD) of Matrix -- Graph Theory Basis (Random walk) Chapter 3: HITS and Related Algorithms (50 pages) -- The Original HITS -- The Stability issues -- The Randomized HITS -- The Subspace HITS -- Weighted HITS -- Vector Space Model (VSM) -- Cover Density Ranking (CDR) -- The In-depth Analysis of the HITS -- HITS Improvement (a significant improvement to clever algorithm) -- Noise Page Elimination Algorithm Based on SVD -- The PHITS algorithm (probabilistic HITS) -- SALSA (Stochastic algorithm) -- Random Walks and the Kleinberg Algorithm Chapter 4: PageRank Related Algorithms (50 pages) -- The Original PageRank -- Probability Combination of Link and Content Information in PageRank -- Topic-Sensitve PageRank -- Search-Order: Breadth-First, Backlink, Random -- Quadratic Extrapolation -- Exporing the Block Structure of the Web for Computing PageRank -- Second Eignevalue of the Google Matrix -- A Latent Linkage Information (LLI) Algorithm -- WebPage Scoring Systems (WPSS) -- Rank Aggregation -- Random Suffer Method -- Voting Model -- SimRank (graph-based) -- When Experts Agree: Using Non-Affliated Experts to Rank Popular Topics -- PageRank, HITS and a Unified Framework for Link Analysis Chapter 5: Web Classification and Clustering (50 pages) -- Web Document Similarity Measurement -- Web Document Classification Based on Hyperlinks and Document Semantics -- Clustering Hypertext with Applications to Web Search -- Link-based Clustering to Improve Web Search Results -- Measure Similarity of Interest for Clustering Web-Users -- Clustering of Web Users Using Session-based Similarity Measures -- Scalable Techniques for Clustering the Web -- Clustering web surfers with mixtures of hidden Markov Models -- Clustering User Queries of a Search Engine -- Using Web Structure for Classifying and Describing Web Pages -- Matrix-Based Hierarchical Clustering Algorithms Chapter 6: Web Log/Content Mining for Web Community (50 pages) -- Cut-and-Pick Transactions for Proxy Log Mining -- Mining Web Logs to Improve Website Organization -- Extracting Large-Scale Knowledge Bases from the Web -- Mining the Space of Graph Properties -- Discovering Test Set Regularities in Relational Domains (classification) -- Enhanced Hypertext Categorization Using Hyperlinks -- The Structure of Broad Topics on the Web -- Discovering Unexpected Information from Your Competitors' Web Sites -- On Integrating Catalogs -- Web Community Mining and Web Log Mi