How Long to Read Graph-Theoretic Techniques for Web Content Mining

How Long Does it Take to Read Graph-Theoretic Techniques for Web Content Mining?

It takes the average reader 4 hours and 15 minutes to read Graph-Theoretic Techniques for Web Content Mining by Adam Schenker

Assuming a reading speed of 250 words per minute. Learn more

Description

This book describes exciting new opportunities for utilizing robust graph representations of data with common machine learning algorithms. Graphs can model additional information which is often not present in commonly used data representations, such as vectors. Through the use of graph distance — a relatively new approach for determining graph similarity — the authors show how well-known algorithms, such as k-means clustering and k-nearest neighbors classification, can be easily extended to work with graphs instead of vectors. This allows for the utilization of additional information found in graph representations, while at the same time employing well-known, proven algorithms. To demonstrate and investigate these novel techniques, the authors have selected the domain of web content mining, which involves the clustering and classification of web documents based on their textual substance. Several methods of representing web document content by graphs are introduced; an interesting feature of these representations is that they allow for a polynomial time distance computation, something which is typically an NP-complete problem when using graphs. Experimental results are reported for both clustering and classification in three web document collections using a variety of graph representations, distance measures, and algorithm parameters. In addition, this book describes several other related topics, many of which provide excellent starting points for researchers and students interested in exploring this new area of machine learning further. These topics include creating graph-based multiple classifier ensembles through random node selection and visualization of graph-based data using multidimensional scaling. Contents:Introduction to Web MiningGraph Similarity TechniquesGraph Models for Web DocumentsGraph-Based ClusteringGraph-Based ClassificationThe Graph Hierarchy Construction Algorithm for Web Search Clustering Readership: Researchers and graduate students who are interested in computer science, specifically machine learning. Also of interest to researchers in academia or industry in disciplines such as information science or information technology who are interested in text and web documents. Keywords:Graph;Machine Learning;Web Mining;Data Mining;Clustering;Classification;Graph Distance;Maximum Common SubgraphKey Features:Opens up exciting new possibilities for utilizing graphs in common machine learning algorithmsPresents experimental results comparing differing graph representations and graph distance measuresProvides a review of graph-theoretic similarity techniques

How long is Graph-Theoretic Techniques for Web Content Mining?

Graph-Theoretic Techniques for Web Content Mining by Adam Schenker is 248 pages long, and a total of 63,984 words.

This makes it 84% the length of the average book. It also has 78% more words than the average book.

How Long Does it Take to Read Graph-Theoretic Techniques for Web Content Mining Aloud?

The average oral reading speed is 183 words per minute. This means it takes 5 hours and 49 minutes to read Graph-Theoretic Techniques for Web Content Mining aloud.

What Reading Level is Graph-Theoretic Techniques for Web Content Mining?

Graph-Theoretic Techniques for Web Content Mining is suitable for students ages 12 and up.

Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.

When deciding what to show young students always use your best judgement and consult a professional.

Where Can I Buy Graph-Theoretic Techniques for Web Content Mining?

Graph-Theoretic Techniques for Web Content Mining by Adam Schenker is sold by several retailers and bookshops. However, Read Time works with Amazon to provide an easier way to purchase books.

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