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Sep 05

Information retrieval, Search and recommendation engine:

Natural language processing:

https://class.coursera.org/nlp/lecture – Processing of texts written in ordinal languages
https://company.yandex.com/technologies/matrixnet.xml – search algorithm by Yandex
http://www.quora.com/What-is-the-search-algorithm-used-by-the-Google-search-engine-What-is-its-complexity

Information retrieval:

http://nlp.stanford.edu/IR-book/html/htmledition/irbook.html – Introduction to Information Retrieval, Cambridge
http://stackoverflow.com/questions/25803267/retrieve-topic-word-array-document-topic-array-from-lda-gensim
http://stats.stackexchange.com/questions/89356/document-similarity-gensim
http://machinelearning.wustl.edu/mlpapers/paper_files/BleiNJ03.pdf – Latent Dirichlet Allocation (LDA)
http://radar.oreilly.com/2015/02/topic-models-past-present-and-future.html
http://en.wikipedia.org/wiki/Topic_model

Few examples of applications for the above:

http://graus.nu/tag/gensim/
https://github.com/sandinmyjoints/gensimtalk/blob/master/gensim_example.py
http://stackoverflow.com/questions/27032517/what-does-the-output-vector-of-a-word-in-word2vec-represent
https://github.com/sandinmyjoints/gensimtalk/blob/master/gensim_example.py
http://stats.stackexchange.com/questions/89356/document-similarity-gensim
http://stackoverflow.com/questions/6486738/clustering-using-latent-dirichlet-allocation-algo-in-gensim

Recommender systems:

https://www.coursera.org/learn/recommender-systems/ – video lectures – 101 for Recommendation System
http://www.ibm.com/developerworks/library/os-recommender1/ – introduction to approach and algorithms
http://www.cs.bme.hu/nagyadat/Recommender_systems_handbook.pdf – “Encyclopedia” of recommender systems
http://www.slideshare.net/xamat/kdd-2014-tutorial-the-recommender-problem-revisited – overview of recommendation algorithms
http://www.machinelearning.org/proceedings/icml2007/papers/407.pdf – Restricted Boltzmann Machines for Collaborative Filtering
http://wiki.hsr.ch/Datenbanken/files/Recommender_System_for_Geo_MSE_DB_Seminar_HS2013_Senn_Paper_final.pdf

Ready for use recommendation engine:

https://cloud.google.com/prediction/ – Google recommendation engine
https://mahout.apache.org – Apache recommendation and general purpose machine learning framework

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