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To address this issue, this work proposes the model for discovering the semantic similarity among the cQA questions. We followed two approaches (i) Feature-based: the question embedding is created using four forms of word embeddings and an ensemble of all four. Then Siamese LSTM (sLSTM) is used to find the semantic similarity among the questions. (ii) Fine-tuning: we fine-tuned BERT model on STS and SNLI data, which employs Siamese network architectures to generate semantically meaningful sentence embeddings. Then sBERT is used to assess the similarity between the questions. Experiments were carried out on Quora (QQP) and Stack Exchange cQA dataset with training sets of different sizes and word vectors of different dimensionalities. The model shows significant improvement over the state-of-the-artwork on sentence similarity tasks.<\/jats:p>","DOI":"10.1093\/comjnl\/bxac003","type":"journal-article","created":{"date-parts":[[2022,1,28]],"date-time":"2022-01-28T12:09:42Z","timestamp":1643371782000},"page":"1139-1155","source":"Crossref","is-referenced-by-count":2,"title":["A Transformer Based Encodings for Detection of Semantically Equivalent Questions in cQA"],"prefix":"10.1093","volume":"66","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0037-7951","authenticated-orcid":false,"given":"Shobhan","family":"Kumar","sequence":"first","affiliation":[{"name":"Computer Science and Engineering , , Karnataka 580009 , India"},{"name":"IIIT Dharwad , , Karnataka 580009 , India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0327-7254","authenticated-orcid":false,"given":"Arun","family":"Chauhan","sequence":"additional","affiliation":[{"name":"Computer Science and Engineering , , Karnataka 580009 , India"},{"name":"IIIT Dharwad , , Karnataka 580009 , India"},{"name":"Computer Science and Engineering , , Dehradun 580009 , India"},{"name":"Graphic Era University , , Dehradun 580009 , India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2022,2,22]]},"reference":[{"key":"2023052000434069800_ref1","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1145\/1099554.1099572","volume-title":"Proceedings of the 14th ACM International Conference on Information and Knowledge Management","author":"Jeon","year":"2005"},{"key":"2023052000434069800_ref2","first-page":"2239","volume-title":"Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence","author":"Zhou","year":"2013"},{"key":"2023052000434069800_ref3","first-page":"2139","volume-title":"Proceedings the 22nd ACM International Conference on Information and Knowledge Management","author":"Chen","year":"2013"},{"key":"2023052000434069800_ref4","doi-asserted-by":"crossref","first-page":"123","DOI":"10.18653\/v1\/K15-1013","volume-title":"Proceedings of the Nineteenth Conference on Computational Natural Language Learning","author":"Bogdanova","year":"2015"},{"key":"2023052000434069800_ref5","first-page":"726","volume-title":"Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics (ACL)","author":"Bonadiman","year":"2017"},{"key":"2023052000434069800_ref6","doi-asserted-by":"crossref","first-page":"707","DOI":"10.1109\/TENCON.2019.8929272","volume-title":"Proceedings of the TENCON 2019\u20132019 IEEE Region 10 Conference (TENCON)","author":"Kumar","year":"2019"},{"key":"2023052000434069800_ref7","doi-asserted-by":"crossref","first-page":"729","DOI":"10.1007\/978-3-319-30671-1_60","volume-title":"Advances in Information Retrieval","author":"Musto","year":"2016"},{"key":"2023052000434069800_ref8","first-page":"434","volume-title":"Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics","author":"Qiu","year":"2013"},{"key":"2023052000434069800_ref9","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.patrec.2016.06.012","article-title":"Representation learning for very short texts using weighted word embedding aggregation","volume":"80","author":"De Boom","year":"2016","journal-title":"Pattern Recogn. 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