{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T03:48:25Z","timestamp":1761709705706,"version":"3.37.3"},"reference-count":17,"publisher":"Wiley","license":[{"start":{"date-parts":[[2020,2,14]],"date-time":"2020-02-14T00:00:00Z","timestamp":1581638400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1936215","LY18F020033","61772026","61602412"],"award-info":[{"award-number":["U1936215","LY18F020033","61772026","61602412"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004731","name":"Natural Science Foundation of Zhejiang Province","doi-asserted-by":"publisher","award":["U1936215","LY18F020033","61772026","61602412"],"award-info":[{"award-number":["U1936215","LY18F020033","61772026","61602412"]}],"id":[{"id":"10.13039\/501100004731","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1936215","LY18F020033","61772026","61602412"],"award-info":[{"award-number":["U1936215","LY18F020033","61772026","61602412"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1936215","LY18F020033","61772026","61602412"],"award-info":[{"award-number":["U1936215","LY18F020033","61772026","61602412"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Mobile Information Systems"],"published-print":{"date-parts":[[2020,2,14]]},"abstract":"<jats:p>With the rapid growth of mobile Apps, it is necessary to classify the mobile Apps into predefined categories. However, there are two problems that make this task challenging. First, the name of a mobile App is usually short and ambiguous to reflect its real semantic meaning. Second, it is usually difficult to collect adequate labeled samples to train a good classifier when a customized taxonomy of mobile Apps is required. For the first problem, we leverage Web knowledge to enrich the textual information of mobile Apps. For the second problem, the mostly utilized approach is the semisupervised learning, which exploits unlabeled samples in a cotraining scheme. However, how to enhance the diversity between base learners to maximize the power of the cotraining scheme is still an open problem. Aiming at this problem, we exploit totally different machine learning paradigms (i.e., shallow learning and deep learning) to ensure a greater degree of diversity. To this end, this paper proposes Co-DSL, a collaborative deep and shallow semisupervised learning framework, for mobile App classification using only a few labeled samples and a large number of unlabeled samples. The experiment results demonstrate the effectiveness of Co-DSL, which could achieve over 85% classification accuracy by using only two labeled samples from each mobile App category.<\/jats:p>","DOI":"10.1155\/2020\/4521723","type":"journal-article","created":{"date-parts":[[2020,2,14]],"date-time":"2020-02-14T18:31:37Z","timestamp":1581705097000},"page":"1-12","source":"Crossref","is-referenced-by-count":1,"title":["A Collaborative Deep and Shallow Semisupervised Learning Framework for Mobile App Classification"],"prefix":"10.1155","volume":"2020","author":[{"given":"MingQi","family":"Lv","sequence":"first","affiliation":[{"name":"Department of Computer Technology, ZheJiang University of Technology, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chao","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Computer Technology, ZheJiang University of Technology, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4664-3311","authenticated-orcid":true,"given":"TieMing","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Computer Technology, ZheJiang University of Technology, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ting","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Computer Technology, ZheJiang University of Technology, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"4","doi-asserted-by":"publisher","DOI":"10.1145\/3017429"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1109\/tmc.2013.113"},{"first-page":"275","volume-title":"Wikipedia based short text classification method","year":"2017","key":"7"},{"first-page":"157","volume-title":"Improving short text classification using public search engines","year":"2013","key":"8"},{"year":"2006","key":"10"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-009-0209-z"},{"key":"19","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2016.02.002"},{"key":"20","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2015.09.037"},{"key":"21","doi-asserted-by":"publisher","DOI":"10.1023\/a:1007692713085"},{"key":"22","doi-asserted-by":"publisher","DOI":"10.1007\/s10844-011-0153-8"},{"key":"26","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2010.11.069"},{"first-page":"571","volume-title":"A mixture of experts classifier with learning based on both labelled and unlabelled data","year":"1997","key":"27"},{"key":"33","doi-asserted-by":"publisher","DOI":"10.1109\/tkde.2005.186"},{"key":"34","doi-asserted-by":"publisher","DOI":"10.1145\/1361684.1361686"},{"key":"35","doi-asserted-by":"publisher","DOI":"10.1109\/tkde.2010.27"},{"issue":"4-5","key":"36","first-page":"993","volume":"3","year":"2003","journal-title":"Journal of Machine Learning Research"},{"key":"39","doi-asserted-by":"publisher","DOI":"10.1109\/tmc.2018.2793913"}],"container-title":["Mobile Information Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/misy\/2020\/4521723.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/misy\/2020\/4521723.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/misy\/2020\/4521723.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,2,14]],"date-time":"2020-02-14T18:31:40Z","timestamp":1581705100000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/misy\/2020\/4521723\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,2,14]]},"references-count":17,"alternative-id":["4521723","4521723"],"URL":"https:\/\/doi.org\/10.1155\/2020\/4521723","relation":{},"ISSN":["1574-017X","1875-905X"],"issn-type":[{"type":"print","value":"1574-017X"},{"type":"electronic","value":"1875-905X"}],"subject":[],"published":{"date-parts":[[2020,2,14]]}}}