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Interval Semi-supervised LDA: Classifying Needles in a Haystack

P. 265-274.
Bodrunova S., Koltsov S., Koltsova O., Nikolenko S. I., Shimorina A.

An important text mining problem is to fi nd, in a large collection of texts, documents related to speci c topics and then discern further structure among the found texts. This problem is especially important for social sciences, where the purpose is to nd the most representative documents for subsequent qualitative interpretation. To solve this problem, we propose an interval semi-supervised LDA approach, in which certain prede ned sets of keywords (that de ne the topics researchers are interested in) are restricted to speci c intervals of topic assignments. We present a case study on a Russian LiveJournal dataset aimed at ethnicity discourse analysis.

В книге

Prt. I: Advances in Artificial Intelligence and Its Applications. Berlin: Springer Verlag, 2013.