![]() The quality of a search is typically described using precision and recall metrics. ![]() This means you can use Lucene to index and search data stored in files: web pages on remote web servers, documents stored in local file systems, in databases, simple text files, Microsoft Word documents, HTML or PDF files, or any other format from which you can extract textual information. ![]() 1 Table of Contents 1) Understanding Lucene 2) Lucene Indexingģ) Types of Fields in Lucene Index 4) An example of Lucene Index fields 5) Core Searching classes 6) Types of Queries 7) Incremental Indexing 8) Score Boosting and relevance ranking 9) Scoring Algorithm 10) Sorting search results 11) Handling multiple pages of search results 12) Examples of queries possible with Lucene 13) Abstract storage in Index 14) Security 15) Composition of Segments in Lucene Index 16) Debugging lucene indexing process 17) Lucene in Alfresco 18) Alfresco repository architecture 19) Why do we sometimes have redundant data in Index and Database 20) Caching 21) Experience of lucene implementation 22) Good articles on LuceneĢ Understanding Lucene There are two things we need to know to create a Lucene search database: How you are going to get information to spider, and What processing you are going to do on the text to increase the likelihood of a successful query Back to Content pageģ Understanding Lucene Lucene doesn’t care about the source of the data, its format, or even its language, as long as you can convert it to text. ![]()
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