Jincy B. Chrystal's scientific contributions
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Publications (2)
Most of the text classification problems are associated with multiple class labels and hence automatic text
classification is one of the most challenging and prominent research area. Text classification is the
problem of categorizing text documents into different classes. In the multi-label classification scenario,
each document is associated may h...
Text mining and Text classification are the two prominent and challenging tasks in the field of
Machine learning. Text mining refers to the process of deriving high quality and relevant
information from text, while Text classification deals with the categorization of text documents
into different classes. The real challenge in these areas is to add...
Citations
... Digital platforms have contributed to the growth of large scale data in both structured and unstructured data [1]. The extensive distribution of information increases high interest in exploring and handling textual unstructured data with using new methods, like text mining, corpus-based computational linguistics, sentiment analysis, and others, which are very useful to gain new insights in managing business policymaking [2, 3,4,5]. Virtual data grow rapidly during the digital era, so these unstructured data can be found on various platforms, such as social media, webpages, and electronic documents. ...
... MMAC [12] is another method which follows the model where in classification rule sets are developed using association rule mining. Jincy and Stephy [13] proposed a ranking algorithm for multi-label classification. This algorithm uses support vector machines which is a linear model that minimizes the objective function (ex: Ranking loss) by preserving a large margin. ...
Reference: 2. NCACTA 2019-SCOPUS PAPER
