Sandeep Mathias

@presidencyinversity.in

Assistant Professor, Department of Computer Science and Engineering
Presidency University



                          

https://researchid.co/lwsam

RESEARCH INTERESTS

Natural Language Processing

7

Scopus Publications

186

Scholar Citations

7

Scholar h-index

7

Scholar i10-index

Scopus Publications

  • Many Hands Make Light Work: Using Essay Traits to Automatically Score Essays


  • Can neural networks automatically score Essay Traits?


  • A survey on using gaze behaviour for natural language processing


  • ASAP++: Enriching the ASAP automated essay grading dataset with essay attribute scores


  • Thank “Goodness”! A Way to Measure Style in Student Essays


  • The whole is greater than the sum of its parts: Towards the effectiveness of voting ensemble classifiers for complex word identification


  • Eyes are the windows to the soul: Predicting the rating of text quality using gaze behaviour
    Sandeep Mathias, Diptesh Kanojia, Kevin Patel, Samarth Agrawal, Abhijit Mishra, and Pushpak Bhattacharyya

    Association for Computational Linguistics
    Predicting a reader’s rating of text quality is a challenging task that involves estimating different subjective aspects of the text, like structure, clarity, etc. Such subjective aspects are better handled using cognitive information. One such source of cognitive information is gaze behaviour. In this paper, we show that gaze behaviour does indeed help in effectively predicting the rating of text quality. To do this, we first we model text quality as a function of three properties - organization, coherence and cohesion. Then, we demonstrate how capturing gaze behaviour helps in predicting each of these properties, and hence the overall quality, by reporting improvements obtained by adding gaze features to traditional textual features for score prediction. We also hypothesize that if a reader has fully understood the text, the corresponding gaze behaviour would give a better indication of the assigned rating, as opposed to partial understanding. Our experiments validate this hypothesis by showing greater agreement between the given rating and the predicted rating when the reader has a full understanding of the text.

RECENT SCHOLAR PUBLICATIONS

  • PresiUniv at TSAR-2022 shared task: Generation and ranking of simplification substitutes of complex words in multiple languages
    P Whistely, S Mathias, G Poornima
    Proceedings of the Workshop on Text Simplification, Accessibility, and 2022

  • Many Hands Make Light Work: Using Essay Traits to Automatically Score Essays
    R Kumar, S Mathias, S Saha, P Bhattacharyya
    2022 Conference of the North American Chapter of the Association for 2022

  • Cognitively Aided Zero-Shot Automatic Essay Grading
    S Mathias, R Murthy, D Kanojia, P Bhattacharyya
    International Conference on Natural Language Processing, 175 - 180 2020

  • Happy Are Those Who Grade without Seeing: A Multi-Task Learning Approach to Grade Essays Using Gaze Behaviour
    S Mathias, R Murthy, D Kanojia, A Mishra, P Bhattacharyya
    1st Conference of the Asia-Pacific Chapter of the Association for 2020

  • Can Neural Networks Automatically Score Essay Traits?
    S Mathias, P Bhattacharyya
    15th Workshop on Innovative Use of NLP for Building Educational Applications 2020

  • A Survey on Using Gaze Behaviour for Natural Language Processing
    S Mathias, D Kanojia, A Mishra, P Bhattacharyya
    Twenty-Ninth International Joint Conference on Artificial Intelligence 2020

  • Eyes are the Windows to the Soul: Predicting the Rating of Text Quality Using Gaze Behaviour
    S Mathias, D Kanojia, K Patel, S Agrawal, A Mishra, P Bhattacharyya
    56th Annual Meeting of the Association for Computational Linguistics, 2352-2362 2018

  • Thank “goodness”! a way to measure style in student essays
    S Mathias, P Bhattacharyya
    Proceedings of the 5th Workshop on Natural Language Processing Techniques 2018

  • The whole is greater than the sum of its parts: Towards the effectiveness of voting ensemble classifiers for complex word identification
    N Wani, S Mathias, JA Gajjam, P Bhattacharyya
    Proceedings of the thirteenth workshop on innovative use of NLP for building 2018

  • ASAP++: Enriching the ASAP automated essay grading dataset with essay attribute scores
    S Mathias, P Bhattacharyya
    Proceedings of the eleventh international conference on language resources 2018

  • Using Machine Translation Evaluation Techniques to Evaluate Text Simplification Systems
    S Mathias, P Bhattacharyya
    Proceedings of the Quality Assessment for Text Simplification (QATS), 38-41 2016

  • How Hard Can it Be? The E-Score - A Scoring Metric to Assess the Complexity of Text
    S Mathias, P Bhattacharyya
    Proceedings of the Quality Assessment for Text Simplification (QATS), 10-14 2016

  • Cognitively aided automatic essay grading
    SA Mathias
    Mumbai

MOST CITED SCHOLAR PUBLICATIONS

  • ASAP++: Enriching the ASAP automated essay grading dataset with essay attribute scores
    S Mathias, P Bhattacharyya
    Proceedings of the eleventh international conference on language resources 2018
    Citations: 54

  • Can Neural Networks Automatically Score Essay Traits?
    S Mathias, P Bhattacharyya
    15th Workshop on Innovative Use of NLP for Building Educational Applications 2020
    Citations: 33

  • A Survey on Using Gaze Behaviour for Natural Language Processing
    S Mathias, D Kanojia, A Mishra, P Bhattacharyya
    Twenty-Ninth International Joint Conference on Artificial Intelligence 2020
    Citations: 27

  • Eyes are the Windows to the Soul: Predicting the Rating of Text Quality Using Gaze Behaviour
    S Mathias, D Kanojia, K Patel, S Agrawal, A Mishra, P Bhattacharyya
    56th Annual Meeting of the Association for Computational Linguistics, 2352-2362 2018
    Citations: 17

  • Many Hands Make Light Work: Using Essay Traits to Automatically Score Essays
    R Kumar, S Mathias, S Saha, P Bhattacharyya
    2022 Conference of the North American Chapter of the Association for 2022
    Citations: 14

  • The whole is greater than the sum of its parts: Towards the effectiveness of voting ensemble classifiers for complex word identification
    N Wani, S Mathias, JA Gajjam, P Bhattacharyya
    Proceedings of the thirteenth workshop on innovative use of NLP for building 2018
    Citations: 13

  • Thank “goodness”! a way to measure style in student essays
    S Mathias, P Bhattacharyya
    Proceedings of the 5th Workshop on Natural Language Processing Techniques 2018
    Citations: 10

  • PresiUniv at TSAR-2022 shared task: Generation and ranking of simplification substitutes of complex words in multiple languages
    P Whistely, S Mathias, G Poornima
    Proceedings of the Workshop on Text Simplification, Accessibility, and 2022
    Citations: 6

  • Happy Are Those Who Grade without Seeing: A Multi-Task Learning Approach to Grade Essays Using Gaze Behaviour
    S Mathias, R Murthy, D Kanojia, A Mishra, P Bhattacharyya
    1st Conference of the Asia-Pacific Chapter of the Association for 2020
    Citations: 6

  • Cognitively Aided Zero-Shot Automatic Essay Grading
    S Mathias, R Murthy, D Kanojia, P Bhattacharyya
    International Conference on Natural Language Processing, 175 - 180 2020
    Citations: 3

  • Using Machine Translation Evaluation Techniques to Evaluate Text Simplification Systems
    S Mathias, P Bhattacharyya
    Proceedings of the Quality Assessment for Text Simplification (QATS), 38-41 2016
    Citations: 2

  • How Hard Can it Be? The E-Score - A Scoring Metric to Assess the Complexity of Text
    S Mathias, P Bhattacharyya
    Proceedings of the Quality Assessment for Text Simplification (QATS), 10-14 2016
    Citations: 1