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etc

deep?

Sumin Lim 2015. 1. 8. 17:41
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=== New or Lately updated apporach ===


BLOG:

http://business.nikkeibp.co.jp/article/bigdata/20141110/273649/


패턴으로 문서 구조, 문단, 문장, 문법인식


http://www.moreagile.net/2014/11/word2vec.html?m=1


http://spark.apache.org/docs/latest/mllib-feature-extraction.html

http://deeplearning4j.org/word2vec.html


http://business.nikkeibp.co.jp/article/bigdata/20141110/273649/

http://business.nikkeibp.co.jp/article/bigdata/20150105/275819/


https://www.google.co.kr/search?q=Paragraph2Vec&oq=Paragraph2Vec&aqs=chrome..69i57&sourceid=chrome&es_sm=93&ie=UTF-8


http://mayo.hatenablog.com/entry/2014/07/11/111432

http://mayo.hatenablog.com/entry/2013/12/09/012939




http://business.nikkeibp.co.jp/article/bigdata/20141110/273649/




=== Traditional Approach ===



Topic Model

http://en.wikipedia.org/wiki/Topic_model


LDA

http://ko.wikipedia.org/wiki/%EC%9E%A0%EC%9E%AC_%EB%94%94%EB%A6%AC%ED%81%B4%EB%A0%88_%ED%95%A0%EB%8B%B9



Slide share : 

http://www.slideshare.net/unnonouno/20140206-statistical-semantics

(http://www.slideshare.net/shannon0118/savedfiles?s_title=20140206-statistical-semantics&user_login=unnonouno)


BLOG:

http://nghyun.blogspot.kr/2012/01/lda.html

http://www.4four.us/article/2010/11/lda-my-blog-topic-trend

http://www.4four.us/article/2010/11/latent-dirichlet-allocation-simply

(한글) http://nullmodel.egloos.com/1958448


비교하기
http://en.wikipedia.org/wiki/Latent_Dirichlet_allocation
http://en.wikipedia.org/wiki/Probabilistic_latent_semantic_analysis


1. https://www.lri.fr/~xlzhang/KAUST/CS229_slides/chapter18_RL.pdf

2. https://www.google.co.kr/search?q=Introduction+to+Machine+Learning+(Adaptive+Computation+and+Machine+Learning)+by+Ethem+Alpaydim+(MIT+Press)&oq=Introduction+to+Machine+Learning+(Adaptive+Computation+and+Machine+Learning)+by+Ethem+Alpaydim+(MIT+Press)&aqs=chrome..69i57.552j0j7&sourceid=chrome&es_sm=93&ie=UTF-8



Paper 

http://nlp.stanford.edu/pubs/llda-emnlp09.pdf




Source 

https://github.com/search?l=C%2B%2B&o=desc&p=1&q=LDA&ref=searchresults&s=stars&type=Repositories&utf8=%E2%9C%93




Library 


MLPack

etc




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