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Publication Type : Journal Article
Publisher : Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Source : Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Verlag, Volume 10478 LNCS, p.50-60 (2018)
ISBN : 9783319736051
Keywords : Classification (of information), Classification tasks, Concept-based, Data set, Information Retrieval, Research problems, Semantics, Text Analytics, Text classification, Text processing, Text representation, Vector space models, Vector spaces, Vectors
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking
Department : Computer Science, Electronics and Communication
Year : 2018
Abstract : This paper assesses the performance of frequency and concept based text representation in Mixed Script Information Retrieval and Classification tasks. In text analytics, representation serves as an unresolved research problem to progress further towards different applications. In this paper observations from different text representation methods in text classification and information retrieval are presented. The data set from the Mixed Script Information Retrieval shared task is used in this experiment and the performance of final submitted model is evaluated by task organizers. It is observed that distributional representation performs better than the frequency based text representation methods. The final system attained first place in task 2 and was 3.89% lesser than the top scored system in task 1. © Springer International Publishing AG. 2018.
Cite this Research Publication : H. B. Barathi Ganesh, M. Kumar, A., and Dr. Soman K. P., “From Vector Space Models to Vector Space Models of Semantics”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10478 LNCS, pp. 50-60, 2018.