JU_CSE_NLP: multi-grade classification of semantic similarity between text pairs

  • Authors:
  • Snehasis Neogi;Partha Pakray;Sivaji Bandyopadhyay;Alexander Gelbukh

  • Affiliations:
  • Jadavpur University, Kolkata, India;Jadavpur University, Kolkata, India and Intern at Xerox Research Centre Europe Grenoble, France;Jadavpur University, Kolkata, India;National Polytechnic Institute Mexico City, Mexico

  • Venue:
  • SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
  • Year:
  • 2012

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Abstract

This article presents the experiments carried out at Jadavpur University as part of the participation in Semantic Textual Similarity (STS) of Task 6 @ Semantic Evaluation Exercises (SemEval-2012). Task-6 of SemEval- 2012 focused on semantic relations of text pair. Task-6 provides five different text pair files to compare different semantic relations and judge these relations through a similarity and confidence score. Similarity score is one kind of multi way classification in the form of grade between 0 to 5. We have submitted one run for the STS task. Our system has two basic modules - one deals with lexical relations and another deals with dependency based syntactic relations of the text pair. Similarity score given to a pair is the average of the scores of the above-mentioned modules. The scores from each module are identified using rule based techniques. The Pearson Correlation of our system in the task is 0.3880.