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Weekly Report - 12/6/15




Found a paper where they cluster event logs with word vector pairs; this approach compares each pair to each other pair in the supplied logs allowing it to cluster lines with similar parts. There is also a toolkit associated with the paper that allows you to specify the input files and the support for making a pair then outputs the clusters where the support is reached, the outlier clusters can also be outputted. This will need to be investigated further to see if it is a good possible solution.

Had a meeting with Antti Puurula about possible approaches, where we discussed outputting a ranking into lists of safe and unsafe events. It was discussed on how this could be evaluated with a Mean Average Precision measurement and then a few algorithms that could be used for scoring events like clustering if the feature space could be separated, supervised learning if all the data was tagged or his recommended a supervised learning where the user manually updates the list of safe/unsafe and the classifier updates iteratively.

Then non language features like time stamps were discussed on how to integrate them as well by having another algorithm like niavebayes handling continuous features. This way we could identify events happening within a certain time period of one another to tie events between files.