Subcategories under Lucene

Subcategories Topics Posts Last Post
Apache Lucene is a high-performance, full-featured text search engine library written entirely in Java. It is a technology suitable for nearly any application that requires full-text search, especially cross-platform.

If you have questions about using Lucene, please post them on the Java Users mailing list.  

(The Java Developer mailing list is for discussions about developing the internals of the Lucene and Solr libraries.)
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by Adrien Grand
The Apache Hadoop project develops open-source software for reliable, scalable, distributed computing.
Hadoop includes these subprojects: Hadoop Common (archive), Avro (archive), Chukwa (archive), HBase (archive), HDFS, Hive, MapReduce, Pig and ZooKeeper.
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by Steve Loughran (Jira...
Apache Solr is a search server focused on full-text search, relevancy, and performance. It builds on the Apache Lucene search library.
Sub-Forums: Solr - User Solr - Dev
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by Dmitri Maziuk
Apache Tika is a toolkit for detecting and extracting metadata and structured text content from various documents using existing parser libraries. 25018 34737
by GitBox
Nutch is web search software. It builds on the Apache Lucene search library, adding a crawler, web database (including full link graph), plugins for various document formats, user interface, etc. Nutch home is here. 31597 69166
by Steve Loughran (Jira...
The general@lucene mailing list is for discussions about the top level Lucene Apache project and matters that affect all subprojects.  It is also a suitable place to ask questions when you aren't sure which sub project would be most useful for addressing a particular problem or use case.

it is not an appropriate place to ask questions about using or developing code for any of the individual sub projects.
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by Kent Poots
Lucy will be a loose C port of the Java Lucene search engine library, with Perl and Ruby bindings.
Sub-Forums: lucy-user lucy dev
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by maamarazaq
Mahout's goal is to build scalable, Apache licensed machine learning libraries. Initially, we are interested in building out the ten machine learning libraries detailed in nips06-mapreducemulticore.pdf using Hadoop. While these algorithms are our initial focus, we welcome contributions of other machine learning approaches.

Interested in helping? See the Wiki or send us an email. Also note, we are just getting off the ground, so please be patient as we get the various infrastructure pieces in place.
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by maamarazaq
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by Rich Bowen-2
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by Rich Bowen-2