Merge ~jac-karwowski/dpcs:clustering_a_16 into dpcs:master

[Jacek]

[Marek Bardoński (bdfhjk)]

It's a professional review of a current state-of-arts algorithms. Your ideas seems promising!

I think a good part of our job will be to implement constrained spectral clustering into a scikit-learn project. Let's think about it.

review: Approve

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+To solve our problem of classifying crashes, first we have to think how represent them in our machine learning algorithm. Server gets the report with several fields containing:
+1) The name and version of crashed application, along with exit code
+2) System version information (kernel and system version, installed modules)
+3) stderr output, consisting of several lines of text
+
+First two are easy to feed to the classifier, as they are primarily numbers or proper names (libraries and applications), but the third, as important as them, is just a variable length blob of text. This is where in my opinion paragraph2vec (extension of word2vec) algorithm comes to use.
+
+My idea is to use paragraph2vec algorithm on text data, then extend the vector using information from 1) and 2) and then use constrained spectral clustering to obtain labels. 
+
+ A comparison [3] shows that the spectral analysis is currently one of the best clustering algorithms, and with constrained SC [4] we can incorporate prior knowledge. Our data is high-dimensional, but due to the use of spectral clustering it shouldn't be much of a problem (PCA step). We will probably be forced to modify the original approach described in the paper, since our task will require providing “cannot-link constraints” (as opposed to “must-link constrains” described in [4], indicating that two elements are in the same cluster).
+
+Paragraph2vec (doc2vec) is already implemented in gensim package (python), I couldn't find any python constrained spectral clustering algorithm, so it is possible we'll have to implement it ourselves.   
+
+Links:
+
+Short explanation of spectral analysis: https://www.youtube.com/watch?v=P-LEH-AFovE
+Word2vec introduction paper http://arxiv.org/pdf/1411.2738v1.pdf
+Word2vec introduction ipython notebook https://github.com/fbkarsdorp/doc2vec/blob/master/doc2vec.ipynb
+
+[1] A p2v algorithm with w2v algorithm description http://arxiv.org/pdf/1405.4053v2.pdf
+[2] A comparison between p2v and other text analysis algorithms + an improvement idea for p2v http://arxiv.org/pdf/1507.07998v1.pdf
+[3] A comparison between different clustering algorithms http://arxiv.org/pdf/1511.09123v1.pdf
+[4] Constrained spectral clustering overview https://dl.acm.org/citation.cfm?id=1148241&dl=ACM&coll=DL&CFID=759388251&CFTOKEN=72271786
+
+
+