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Natural Language Processing with Java

You're reading from   Natural Language Processing with Java Techniques for building machine learning and neural network models for NLP

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Product type Paperback
Published in Jul 2018
Publisher
ISBN-13 9781788993494
Length 318 pages
Edition 2nd Edition
Languages
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Author (1):
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Richard M. Reese Richard M. Reese
Author Profile Icon Richard M. Reese
Richard M. Reese
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Toc

Table of Contents (19) Chapters Close

Title Page
Dedication
Packt Upsell
Contributors
Preface
1. Introduction to NLP FREE CHAPTER 2. Finding Parts of Text 3. Finding Sentences 4. Finding People and Things 5. Detecting Part of Speech 6. Representing Text with Features 7. Information Retrieval 8. Classifying Texts and Documents 9. Topic Modeling 10. Using Parsers to Extract Relationships 11. Combined Pipeline 12. Creating a Chatbot 1. Other Books You May Enjoy Index

Evaluation of information retrieval systems


To evaluate an information retrieval system the standard way, a test collection is needed, which should have the following:

  • A collection of documents
  • Test query set for the required information
  • Binary assessment of relevant or not relevant

The documents in collections are classified using two categories, relevant and not relevant. The test document collection should be of a reasonable size, so the test can have reasonable scope to find the average performance. Relevance of output is always assessed relative to information required, and not on the basis of a query. In other words, having a query word in the results does not mean that it is relevant. For example, if the search term or query is for "Python," the results may show the Python programming language or a pet python; both the results contain the query term, but whether it is relevant to the user is the important factor. If the system contains a parameterized index, then it can be tuned for better...

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