Building Search Applications: Lucene, LingPipe, and Gate Review

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Building Search Applications: Lucene, LingPipe, and Gate ReviewUnfortunately, there are not too many books written on the subject of Information Retrieval as it relates to Java programming, and thankfully, Mr.Konchady's contribution is an excellent resource. It provides a nice balance between the discussion of the theory of Information Retrieval, and providing concrete examples in Java, using Lucene, LingPipe, and Gate (API's for Information Retrieval used in Java). I personally had only heard of Lucene before coming across this book, and was very thankful to learn of the other two (LingPipe, and Gate) afterwards. The book shows the user how to use the above API's together when building an application, which is a great learning opportunity for the reader, because most tutorials available for Lucene, LingPipe, or Gate that you'll find online show you how to use that particular API only, instead of showing you how to use it in conjunction with others to truly harness the power of Information Retrieval with Natural Language Processing, together. The other very nice thing about this book is that the author also introduces the reader to other tools (such as Nutch, WordNet, etc.) that allows the user to provide advanced functionality, without "re-inventing the wheel". This book is a must read for anyone who is serious about learning to develop applications involving Information Retrieval.Building Search Applications: Lucene, LingPipe, and Gate OverviewLucene, LingPipe, and Gate are popular open source tools to build powerful search applications. Building Search Applications describes functions from Lucene that include indexing, searching, ranking, and spelling correction to build search engines. With this book you will learn to: Extract tokens from text using custom tokenizers and analyzers from Lucene, LingPipe, and Gate. Construct a search engine index with an optional backend database to manage large document collections. Explore the wide range of Lucene queries to search an index, understand the ranking algorithm for a query, and suggest spelling corrections. Find the names of people, places, and other entities in text using LingPipe and Gate. Categorize documents by topic using classifiers and build groups of self-organized documents using clustering algorithms from LingPipe. Create a Web crawler to scan the Web, Intranet, or desktop using Nutch. Track the sentiment of articles published on the Web with LingPipe.

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