Publication Type:

Conference Paper

Source:

CEUR Workshop Proceedings, CEUR-WS, Volume 1737, p.122-125 (2016)

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85006098483&partnerID=40&md5=39973dd3660772809bbfc79ee65bb35c

Keywords:

Artificial intelligence, Code-mixed script, Codes (symbols), Embeddings, Extracting features, Information Retrieval, Knowledge based systems, Knowledge-based methods, Learning systems, Logistic regressions, Question Answering, Question classification, Recurrent neural networks, Sentence level, Text processing

Abstract:

Question classification is a key task in many question answering applications. Nearly all previous work on question classification has used machine learning and knowledge-based methods. This working note presents an embedding based Bag-of-Words method and Recurrent Neural Network to achieve an automatic question classification in the code-mixed Bengali-English text. We build two systems that classify questions mostly at the sentence level. We used a recurrent neural network for extracting features from the questions and Logistic regression for classification. We conduct experiments on Mixed Script Information Retrieval (MSIR) Task 1 dataset at FIRE20161. The experimental result shows that the proposed method is appropriate for the question classification task.

Notes:

cited By 0; Conference of 2016 Forum for Information Retrieval Evaluation, FIRE 2016 ; Conference Date: 7 December 2016 Through 10 December 2016; Conference Code:125007

Cite this Research Publication

Dr. M. Anand Kumar, Dr. Soman K. P., and Dr. Soman K. P., “Amrita-CEN@MSIR-FIRE2016: Code-mixed question classification using BoWs and RNN Embeddings”, in CEUR Workshop Proceedings, 2016, vol. 1737, pp. 122-125.

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