Review of issues in automatic labelling of formatted document
Journal Title: International Journal of Advanced Research in Computer Engineering & Technology(IJARCET) - Year 2012, Vol 1, Issue 10
Abstract
The labelling framework, which is proposed to label topic models, essentially consists of a multinomial word distribution, a set of candidate labels, and a context collection. Thus it could be applied to any text mining problems, in which a multinomial distribution of word is involved. To generate labels that are understandable, semantically relevant, discriminative across topics, and of high coverage of each topic, first extract a set of understandable candidate labels in a pre-processing step, then design a relevance scoring function to measure the semantic similarity between a label and a topic, and finally propose label selection methods. This paper presents all such issues involved in the problem of knowledge discovery using text mining. Our paper aims to review various issues described or presented by various researchers in this area.
Authors and Affiliations
Pallavi Galgale , Priyanka Ahire , Snehal Ingavale , Dr. R. S. Prasad
Keywords
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