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Senior lecturer Peter Shaw, IEEE Member, School of Computer and Mathematics of Massey University, Massey University, New Zealand (click) Research Area: computer science, artificial intelligence, big data, life science information analysis |
Title: Combinatorial Text Classification: the effect of multi-parameterized correlation clustering
Abstract: The report will demonstrate the potential of chaining two distinct methodologies in service of topic modelling. The first, as of recent years, is more-or-less standard natural language processing (NLP) with word2vec; the second is graph-theoretical or combinatorial algorithm. Together, we show how they may be used to help classify documents into distinct, but perhaps not disjointed classes. The procedure is demonstrated on a collection of Twitter feeds, or tweets. Heuristics is the basis for this procedure; it is not presumed to perfectly work in every situation, or for every input, and, in fact, it is believed that the procedure will yield better results in a more homogeneous corpora written in some standardized fashion, as written in, e.g.,legal or medical documents.