{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,10]],"date-time":"2025-04-10T04:29:45Z","timestamp":1744259385011,"version":"3.37.3"},"reference-count":57,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2020,7,8]],"date-time":"2020-07-08T00:00:00Z","timestamp":1594166400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Tsinghua University Project of Volvo-supported Green Economy and Sustainable Development","award":["20153000181)"],"award-info":[{"award-number":["20153000181)"]}]},{"name":"UK\u2013China Industry Academia Partnership Program","award":["UK-CIAPP\/260"],"award-info":[{"award-number":["UK-CIAPP\/260"]}]},{"name":"Construction Project of China Knowledge Center for Engineering Sciences and Technology","award":["CKCEST-2020-2-5"],"award-info":[{"award-number":["CKCEST-2020-2-5"]}]},{"name":"MOE (Ministry of Education in China) Project of Humanities and Social Sciences","award":["16JDGC011"],"award-info":[{"award-number":["16JDGC011"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["71974107, 91646102, L1924058, L1824039, L1724034, L1724026"],"award-info":[{"award-number":["71974107, 91646102, L1924058, L1824039, L1724034, L1724026"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,3,14]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>The prevalence of short texts on the Web has made mining the latent topic structures of short texts a critical and fundamental task for many applications. However, due to the lack of word co-occurrence information induced by the content sparsity of short texts, it is challenging for traditional topic models like latent Dirichlet allocation (LDA) to extract coherent topic structures on short texts. Incorporating external semantic knowledge into the topic modeling process is an effective strategy to improve the coherence of inferred topics. In this paper, we develop a novel topic model\u2014called biterm correlation knowledge-based topic model (BCK-TM)\u2014to infer latent topics from short texts. Specifically, the proposed model mines biterm correlation knowledge automatically based on recent progress in word embedding, which can represent semantic information of words in a continuous vector space. To incorporate external knowledge, a knowledge incorporation mechanism is designed over the latent topic layer to regularize the topic assignment of each biterm during the topic sampling process. Experimental results on three public benchmark datasets illustrate the superior performance of the proposed approach over several state-of-the-art baseline models.<\/jats:p>","DOI":"10.1093\/comjnl\/bxaa079","type":"journal-article","created":{"date-parts":[[2020,6,4]],"date-time":"2020-06-04T19:10:53Z","timestamp":1591297853000},"page":"537-553","source":"Crossref","is-referenced-by-count":2,"title":["Incorporating Biterm Correlation Knowledge into Topic Modeling for Short Texts"],"prefix":"10.1093","volume":"65","author":[{"given":"Kai","family":"Zhang","sequence":"first","affiliation":[{"name":"National Numerical Control Systems Engineering Research Center, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, No. 1037, Luoyu Road, Hongshan District, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuan","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Public Policy and Management, Tsinghua University, No. 30, Shuangqing Road, Haidian District, Beijing 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zheng","family":"Chen","sequence":"additional","affiliation":[{"name":"National Numerical Control Systems Engineering Research Center, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, No. 1037, Luoyu Road, Hongshan District, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yufei","family":"Liu","sequence":"additional","affiliation":[{"name":"Center for Strategic Studies, Chinese Academy of Engineering, No. 2, Bingjiaokou Lane, Xicheng District, Beijing 100088, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhuo","family":"Tang","sequence":"additional","affiliation":[{"name":"College of Information Science and Engineering, Hunan University, and National Supercomputing Center, No. 2, Lushannan Road, Yuelu District, Changsha, 410082, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Yin","sequence":"additional","affiliation":[{"name":"National Numerical Control Systems Engineering Research Center, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, No. 1037, Luoyu Road, Hongshan District, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jihong","family":"Chen","sequence":"additional","affiliation":[{"name":"National Numerical Control Systems Engineering Research Center, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, No. 1037, Luoyu Road, Hongshan District, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2020,7,8]]},"reference":[{"key":"2022031814093057900_ref1","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.ins.2018.04.071","article-title":"Filtering out the noise in short text topic Modeling. 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