{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T15:31:09Z","timestamp":1781105469122,"version":"3.54.1"},"reference-count":0,"publisher":"IGI Global Scientific Publishing","issue":"3","license":[{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/deed.en_US"},{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"am","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/deed.en_US"},{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/deed.en_US"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,7,1]]},"abstract":"<p>Community question answering has become increasingly important as they are practical for seeking and sharing information. Applying deep learning models often leads to good performance, but it requires an extensive amount of annotated data, a problem exacerbated for languages suffering a scarcity of resources. Contextualized language representation models have gained success due to promising results obtained on a wide array of downstream natural language processing tasks such as text classification, textual entailment, and paraphrase identification. This paper presents a novel approach by fine-tuning contextualized embeddings for a medical domain community question answering task. The authors propose an architecture combining two neural models powered by pre-trained contextual embeddings to learn a sentence representation and thereafter fine-tuned on the task to compute a score used for both ranking and classification. The experimental results on SemEval Task 3 CQA show that the model significantly outperforms the state-of-the-art models by almost 2% for the '16 edition and 1% for the '17 edition.<\/p>","DOI":"10.4018\/ijiit.2021070102","type":"journal-article","created":{"date-parts":[[2021,8,9]],"date-time":"2021-08-09T11:35:18Z","timestamp":1628508918000},"page":"1-17","source":"Crossref","is-referenced-by-count":1,"title":["Arabic Biomedical Community Question Answering Based on Contextualized Embeddings"],"prefix":"10.4018","volume":"17","author":[{"given":"Yassine","family":"El Adlouni","sequence":"first","affiliation":[{"name":"LISAC Laboratory, Sidi Mohamed Ben Abdellah University, Fez, Morocco"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1641-1501","authenticated-orcid":true,"given":"Noureddine En","family":"Nahnahi","sequence":"additional","affiliation":[{"name":"LISAC Laboratory, Sidi Mohamed Ben Abdellah University, Fez, Morocco"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Said Ouatik","family":"El Alaoui","sequence":"additional","affiliation":[{"name":"Laboratory of Engeneering Sciences, National School of Applied Sciences, Ibn Tofail University, Keni, Morocco"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammed","family":"Meknassi","sequence":"additional","affiliation":[{"name":"LISAC Laboratory, Sidi Mohamed Ben Abdellah University, Fez, Morocco"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Horacio","family":"Rodr\u00edguez","sequence":"additional","affiliation":[{"name":"Universitat Polit\u00e8cnica de Catalunya, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nabil","family":"Alami","sequence":"additional","affiliation":[{"name":"LISAC Laboratory, Sidi Mohamed Ben Abdellah University, Fez, Morocco"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","container-title":["International Journal of Intelligent Information Technologies"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=286622","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,24]],"date-time":"2024-01-24T16:10:47Z","timestamp":1706112647000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/IJIIT.2021070102"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2021,7,1]]},"references-count":0,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2021,7]]}},"URL":"https:\/\/doi.org\/10.4018\/ijiit.2021070102","relation":{},"ISSN":["1548-3657","1548-3665"],"issn-type":[{"value":"1548-3657","type":"print"},{"value":"1548-3665","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,1]]}}}