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Knowl. Discov. Data"],"published-print":{"date-parts":[[2023,6,30]]},"abstract":"<jats:p>Despite substantial interest in applications of neural networks to information retrieval, neural ranking models have mostly been applied to conventional ad-hoc retrieval tasks over web pages and newswire articles. This article proposes a concept-enhanced pre-training model for microblog retrieval task, leveraging Semantic Matching Model (SMM) objective and Concept Correlation Model (CCM) objective. The proposed model is a novel neural ranking model specifically designed for ranking short-text microblog, which could merge the advantage of pre-training methodology for generating valid contextualized embedding with the superiority of the prior lexical knowledge (e.g., concept knowledge) for understanding short-text language semantic. We conduct experiments on widely used real-world datasets, and the experimental results demonstrate the efficiency of the proposed model, even compared with latest state-of-the-art neural-based models and pre-training based models.<\/jats:p>","DOI":"10.1145\/3552311","type":"journal-article","created":{"date-parts":[[2022,8,2]],"date-time":"2022-08-02T11:18:00Z","timestamp":1659439080000},"page":"1-32","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Microblog Retrieval Based on Concept-Enhanced Pre-Training Model"],"prefix":"10.1145","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9414-4985","authenticated-orcid":false,"given":"Yashen","family":"Wang","sequence":"first","affiliation":[{"name":"National Engineering Laboratory for Risk Perception and Prevention (RPP), China Academy of Electronics and Information Technology of CETC and Key Laboratory of Cognition and Intelligence Technology (CIT), Information Science Academy of CETC, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9883-5521","authenticated-orcid":false,"given":"Zhaoyu","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information Sciences, University of Illinois at Urbana-Champaign, Urbana, IL"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7757-0173","authenticated-orcid":false,"given":"Huanhuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"National Engineering Laboratory for Risk Perception and Prevention (RPP), China Academy of Electronics and Information Technology of CETC, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3389-6627","authenticated-orcid":false,"given":"Zhirun","family":"Liu","sequence":"additional","affiliation":[{"name":"Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications, School of Computer, Beijing Institute of Technology, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,2,22]]},"reference":[{"key":"e_1_3_2_2_2","first-page":"98","volume-title":"Proceedings of the IEEE\/WIC\/ACM International Conference on Web Intelligence and Intelligent Agent Technology","author":"Albishre Khaled","year":"2016","unstructured":"Khaled Albishre, Mubarak Albathan, and Yuefeng Li. 2016. 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