Hi Chris, Just an FYI.
NLP4L has a function that extracts document vectors (in libsvm format) from Lucene index. Spark MLlib can be used for executing LDA on it. We have a short tutorial about it. See "Clustering" section in "Working with Spark" chapter. http://nlp4l.github.io/tutorial.html#useWithSpark Koji On 2015/08/01 11:12, Mattmann, Chris A (3980) wrote:
Hey Folks, Does anyone know of a good ALv2 compatible approach to Lucene and to topic modeling? I’m looking to not have to do it post-facto e.g. with a specific library, but to actually perform topic modeling like LDA (or something else) while building the index. The topic modeling needs to be scalable and dynamic - e.g., if I change a query on years, the topics should be updated accordingly. Is this possible with Lucene? I’ve found this: https://github.com/stepthom/lucene-lda But it seems like it stopped short of the calls to actual topic modeling e.g., with MALLET, etc. Thanks for any help here. Cheers, Chris ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Chris Mattmann, Ph.D. Chief Architect Instrument Software and Science Data Systems Section (398) NASA Jet Propulsion Laboratory Pasadena, CA 91109 USA Office: 168-519, Mailstop: 168-527 Email: [email protected] WWW: http://sunset.usc.edu/~mattmann/ ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Adjunct Associate Professor, Computer Science Department University of Southern California, Los Angeles, CA 90089 USA ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
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