Automated Answer Validation using Text Similarity

Balaji Ganesan; Arjun Ravikumar; Lakshay Piplani; Rini Bhaumik; Dhivya Padmanaban; Shwetha Narasimhamurthy; Chetan Adhikary; Subhash Deshapogu

Automated Answer Validation using Text Similarity

Balaji Ganesan, Arjun Ravikumar, Lakshay Piplani, Rini Bhaumik, Dhivya Padmanaban, Shwetha Narasimhamurthy, Chetan Adhikary, Subhash Deshapogu

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Abstract

Automated answer validation can help improve learning outcomes by providing appropriate feedback to learners, and by making question answering systems and online learning solutions more widely available. There have been some works in science question answering which show that information retrieval methods outperform neural methods, especially in the multiple choice version of this problem. We implement Siamese neural network models and produce a generalised solution to this problem. We compare our supervised model with other text similarity based solutions.

Anthology ID:: 2023.icon-1.83
Volume:: Proceedings of the 20th International Conference on Natural Language Processing (ICON)
Month:: December
Year:: 2023
Address:: Goa University, Goa, India
Editors:: Jyoti D. Pawar, Sobha Lalitha Devi
Venue:: ICON
SIG:: SIGLEX
Publisher:: NLP Association of India (NLPAI)
Note:
Pages:: 807–814
Language:
URL:: https://aclanthology.org/2023.icon-1.83/
DOI:
Bibkey:
Cite (ACL):: Balaji Ganesan, Arjun Ravikumar, Lakshay Piplani, Rini Bhaumik, Dhivya Padmanaban, Shwetha Narasimhamurthy, Chetan Adhikary, and Subhash Deshapogu. 2023. Automated Answer Validation using Text Similarity. In Proceedings of the 20th International Conference on Natural Language Processing (ICON), pages 807–814, Goa University, Goa, India. NLP Association of India (NLPAI).
Cite (Informal):: Automated Answer Validation using Text Similarity (Ganesan et al., ICON 2023)
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PDF:: https://aclanthology.org/2023.icon-1.83.pdf

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@inproceedings{balaji-etal-2023-automated,
    title = "Automated Answer Validation using Text Similarity",
    author = "Ganesan, Balaji  and
      Ravikumar, Arjun  and
      Piplani, Lakshay  and
      Bhaumik, Rini  and
      Padmanaban, Dhivya  and
      Narasimhamurthy, Shwetha  and
      Adhikary, Chetan  and
      Deshapogu, Subhash",
    editor = "D. Pawar, Jyoti  and
      Lalitha Devi, Sobha",
    booktitle = "Proceedings of the 20th International Conference on Natural Language Processing (ICON)",
    month = dec,
    year = "2023",
    address = "Goa University, Goa, India",
    publisher = "NLP Association of India (NLPAI)",
    url = "https://aclanthology.org/2023.icon-1.83/",
    pages = "807--814",
    abstract = "Automated answer validation can help improve learning outcomes by providing appropriate feedback to learners, and by making question answering systems and online learning solutions more widely available. There have been some works in science question answering which show that information retrieval methods outperform neural methods, especially in the multiple choice version of this problem. We implement Siamese neural network models and produce a generalised solution to this problem. We compare our supervised model with other text similarity based solutions."
}

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%0 Conference Proceedings
%T Automated Answer Validation using Text Similarity
%A Ganesan, Balaji
%A Ravikumar, Arjun
%A Piplani, Lakshay
%A Bhaumik, Rini
%A Padmanaban, Dhivya
%A Narasimhamurthy, Shwetha
%A Adhikary, Chetan
%A Deshapogu, Subhash
%Y D. Pawar, Jyoti
%Y Lalitha Devi, Sobha
%S Proceedings of the 20th International Conference on Natural Language Processing (ICON)
%D 2023
%8 December
%I NLP Association of India (NLPAI)
%C Goa University, Goa, India
%F balaji-etal-2023-automated
%X Automated answer validation can help improve learning outcomes by providing appropriate feedback to learners, and by making question answering systems and online learning solutions more widely available. There have been some works in science question answering which show that information retrieval methods outperform neural methods, especially in the multiple choice version of this problem. We implement Siamese neural network models and produce a generalised solution to this problem. We compare our supervised model with other text similarity based solutions.
%U https://aclanthology.org/2023.icon-1.83/
%P 807-814

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Markdown (Informal)

[Automated Answer Validation using Text Similarity](https://aclanthology.org/2023.icon-1.83/) (Ganesan et al., ICON 2023)

Automated Answer Validation using Text Similarity (Ganesan et al., ICON 2023)

ACL

Balaji Ganesan, Arjun Ravikumar, Lakshay Piplani, Rini Bhaumik, Dhivya Padmanaban, Shwetha Narasimhamurthy, Chetan Adhikary, and Subhash Deshapogu. 2023. Automated Answer Validation using Text Similarity. In Proceedings of the 20th International Conference on Natural Language Processing (ICON), pages 807–814, Goa University, Goa, India. NLP Association of India (NLPAI).