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Building Search Applications Lucene LingPipe and Gate 1st Edition by Manu Konchady ISBN 0615204252 9780615204253

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Building Search Applications Lucene LingPipe and Gate First Edition Manu Konchady Digital Instant Download

Author(s): Manu Konchady
ISBN(s): 9780615204253, 0615204252
Edition: First
File Details: PDF, 2.77 MB
Year: 2008
Language: english
SKU: EB-1807082 Category: Tag:

Building Search Applications Lucene LingPipe and Gate 1st Edition by Manu Konchady – Ebook PDF Instant Download/Delivery: 0615204252, 9780615204253
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ISBN 10: 0615204252 
ISBN 13: 9780615204253
Author: Manu Konchady

Lucene, 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.

Building Search Applications Lucene LingPipe and Gate 1st Table of contents:

Part I: Foundations of Search Applications

Chapter 1: Introduction to Information Retrieval

  • 1.1 Principles of Search and Indexing

  • 1.2 Boolean, Vector Space, and Probabilistic Models

  • 1.3 Evaluation Metrics: Precision, Recall, and F-Measure

Chapter 2: Text Processing and Natural Language Techniques

  • 2.1 Tokenization, Stemming, and Lemmatization

  • 2.2 Part-of-Speech Tagging and Named Entity Recognition

  • 2.3 Handling Stop Words, Noise, and Ambiguity

Part II: Lucene – Indexing and Searching

Chapter 3: Introduction to Lucene

  • 3.1 Architecture and Core Components

  • 3.2 Index Creation and Management

  • 3.3 Querying and Retrieval Mechanisms

Chapter 4: Advanced Lucene Techniques

  • 4.1 Ranking, Scoring, and Relevance

  • 4.2 Handling Large-Scale Data

  • 4.3 Custom Analyzers and Token Filters

Part III: LingPipe – Natural Language Processing

Chapter 5: Introduction to LingPipe

  • 5.1 Overview and Capabilities

  • 5.2 Named Entity Recognition (NER)

  • 5.3 Text Classification and Clustering

Chapter 6: Practical NLP with LingPipe

  • 6.1 Sentiment Analysis

  • 6.2 Language Modeling and Pattern Matching

  • 6.3 Integrating LingPipe with Lucene for Search

Part IV: GATE – Text Engineering Framework

Chapter 7: Introduction to GATE

  • 7.1 Architecture and Components

  • 7.2 Processing Resources and Language Resources

  • 7.3 Annotation and Corpus Management

Chapter 8: Building Applications with GATE

  • 8.1 Information Extraction Systems

  • 8.2 Rule-Based and Machine Learning Approaches

  • 8.3 Integration with Lucene and LingPipe

Part V: Putting It All Together

Chapter 9: Designing a Complete Search Application

  • 9.1 Combining Indexing, NLP, and Annotation

  • 9.2 Workflow and Pipeline Design

  • 9.3 Case Study: Enterprise Search Application

Chapter 10: Evaluation, Optimization, and Future Trends

  • 10.1 Performance Tuning

  • 10.2 Evaluating Accuracy and User Experience

  • 10.3 Emerging Trends in Search and Text Analytics

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Tags: Manu Konchady, Lucene LingPipe, Gate