{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,20]],"date-time":"2025-07-20T03:29:28Z","timestamp":1752982168861,"version":"3.37.3"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"15","license":[{"start":{"date-parts":[[2022,4,10]],"date-time":"2022-04-10T00:00:00Z","timestamp":1649548800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,4,10]],"date-time":"2022-04-10T00:00:00Z","timestamp":1649548800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"natural science foundation of china","doi-asserted-by":"crossref","award":["61672022","U1904186"],"award-info":[{"award-number":["61672022","U1904186"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"key disciplines of software engineering of shanghai polytechnic university","award":["XXKZD1604"],"award-info":[{"award-number":["XXKZD1604"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2022,12]]},"DOI":"10.1007\/s10489-022-03500-9","type":"journal-article","created":{"date-parts":[[2022,4,9]],"date-time":"2022-04-09T23:03:30Z","timestamp":1649545410000},"page":"18187-18200","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["CS-BTM: a semantics-based hot topic detection method for social network"],"prefix":"10.1007","volume":"52","author":[{"given":"Weinan","family":"Niu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenan","family":"Tan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Jia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,4,10]]},"reference":[{"issue":"2","key":"3500_CR1","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1080\/01638539809545028","volume":"25","author":"TK Landauer","year":"1998","unstructured":"Landauer TK, Foltz PW, Laham D (1998) Taylor, and Francis, online: an introduction to latent semantic analysis - discourse processes. Discourse Process 25(2):259\u2013284","journal-title":"Discourse Process"},{"key":"3500_CR2","first-page":"993","volume":"3","author":"DM Blei","year":"2012","unstructured":"Blei DM, Ng AY, Jordan MI, Lafferty J (2012) Latent Dirichlet allocation. J Mach Learn Res 3:993\u20131022","journal-title":"J Mach Learn Res"},{"key":"3500_CR3","doi-asserted-by":"crossref","unstructured":"Yan X, Guo J, Lan Y, et al (2013) A biterm topic model for short texts[C]. Proceedings of the 22nd international conference on World Wide Web, pp 1445\u20131456","DOI":"10.1145\/2488388.2488514"},{"key":"3500_CR4","unstructured":"Devlin J, Chang M W, Lee K et al Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv:1810.04805"},{"issue":"1\u20132","key":"3500_CR5","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1023\/A:1007617005950","volume":"42","author":"T Hofmann","year":"2001","unstructured":"Hofmann T (2001) Unsupervised learning by probabilistic latent semantic analysis. Mach Learn 42(1\u20132):177\u2013196","journal-title":"Mach Learn"},{"key":"3500_CR6","doi-asserted-by":"publisher","first-page":"4018","DOI":"10.4028\/www.scientific.net\/AMM.556-562.4018","volume":"556\u2013562","author":"YC Zheng","year":"2014","unstructured":"Zheng YC (2014) Text segmentation based on the plsa-texttiling model. Appl Mech Mater 556\u2013562:4018\u20134022","journal-title":"Appl Mech Mater"},{"key":"3500_CR7","doi-asserted-by":"crossref","unstructured":"Rui Zhao KM (2015) Supervised adaptive-transfer plsa for cross-domain text classification. 2014 IEEE international conference on data 305mining workshop, pp 259\u2013266","DOI":"10.1109\/ICDMW.2014.163"},{"issue":"4","key":"3500_CR8","first-page":"620","volume":"31","author":"P Yali","year":"2008","unstructured":"Yali P, Jian Y, Shaopeng L, Le S (2008) Text classification based on labeled-LDA model. Chin J Comput 31(4):620\u2013627","journal-title":"Chin J Comput"},{"issue":"11","key":"3500_CR9","first-page":"33","volume":"31","author":"GJW Wankun","year":"2015","unstructured":"Wankun GJW, Qinglie W (2015) Hot topic extraction from e-commerce microblog based on em-LDA integrated mode. Data Analysis and Knowledge Discovery 31(11):33\u201340","journal-title":"Data Analysis and Knowledge Discovery"},{"key":"3500_CR10","doi-asserted-by":"crossref","unstructured":"Katyayani J (2020) Hot topic extraction from news websites. Advances in computational and bio-engineering, pp 297\u2013303","DOI":"10.1007\/978-3-030-46943-6_33"},{"issue":"10","key":"3500_CR11","first-page":"795","volume":"48","author":"Z Chenyi","year":"2011","unstructured":"Chenyi Z, Jianling S, Yiqun D (2011) Topic mining for microblog based on MB-LDA model. J Comput Res Dev 48(10):795\u20131802","journal-title":"J Comput Res Dev"},{"issue":"01","key":"3500_CR12","first-page":"36","volume":"35","author":"L Zhenxing","year":"2016","unstructured":"Zhenxing L, Wang S (2016) Short text classification based on chi-square feature and btm. J Lanzhou Jiaotong Univ 35(01):36\u201341","journal-title":"J Lanzhou Jiaotong Univ"},{"issue":"001","key":"3500_CR13","first-page":"132","volume":"34","author":"L Lei","year":"2017","unstructured":"Lei L, Zhu Y, Huaji S (2017) Topic mining based on U_BTM model in social networks. Appl Res Comput 34(001):132\u2013135","journal-title":"Appl Res Comput"},{"issue":"005","key":"3500_CR14","first-page":"1258","volume":"38","author":"X Yang","year":"2017","unstructured":"Yang X, Yang W, Cheng Q (2017) Short-text clustering method combining how net with btm model. Comput Eng Design 38(005):1258\u20131263","journal-title":"Comput Eng Design"},{"key":"3500_CR15","doi-asserted-by":"publisher","first-page":"32215","DOI":"10.1109\/ACCESS.2020.2973430","volume":"8","author":"D Wu","year":"2020","unstructured":"Wu D, Zhang M, Shen C, Huang Z, Gu M (2020) Btm and glove similarity linear fusion-based short text clustering algorithm for microblog hot topic discovery. IEEE Access 8:32215\u201332225","journal-title":"IEEE Access"},{"key":"3500_CR16","first-page":"1","volume":"4","author":"Y Wang","year":"2020","unstructured":"Wang Y, Yunhua Z (2020) Research on btm topic model based on two-word meaning enhancement. Softw Eng 4:1\u20136","journal-title":"Softw Eng"},{"issue":"2","key":"3500_CR17","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1109\/TCSS.2019.2897641","volume":"6","author":"X Geng","year":"2019","unstructured":"Geng X, Zhang Y, Jiao Y, Mei Y (2019) A novel hybrid clustering algorithm for topic detection on Chinese microblogging. IEEE Trans Comput Social Syst 6(2):289\u2013300","journal-title":"IEEE Trans Comput Social Syst"},{"key":"3500_CR18","doi-asserted-by":"publisher","first-page":"115621","DOI":"10.1016\/j.eswa.2021.115621","volume":"185","author":"J\u00c1 Mart\u00ednez-Huertas","year":"2021","unstructured":"Mart\u00ednez-Huertas J\u00c1, Olmos R, Le\u00f3n JA (2021) Enhancing topic-detection in computerized assessments of constructed responses with distributional models of language. Expert Syst Appl 185:115621","journal-title":"Expert Syst Appl"},{"issue":"2","key":"3500_CR19","doi-asserted-by":"publisher","first-page":"101801","DOI":"10.1016\/j.is.2021.101801","volume":"101","author":"KE Daouadi","year":"2021","unstructured":"Daouadi KE, Reba RZ, Amous I (2021) Optimizing semantic deep Forest for tweet topic classification[J]. Inf Syst 101(2):101801","journal-title":"Inf Syst"},{"key":"3500_CR20","doi-asserted-by":"crossref","unstructured":"Li D, Zhou X, Xue A (2020) Open source threat intelligence discovery based on topic detection. 2020 29th international conference on computer communications and networks (ICCCN), pp 1\u20134","DOI":"10.1109\/ICCCN49398.2020.9209602"},{"issue":"4","key":"3500_CR21","first-page":"1","volume":"1","author":"Z Wang","year":"2017","unstructured":"Wang Z, Le X, He Y (2017) Recognizing core topic sentences with improved text rank algorithm based on wmd semantic similarity. Data Anal Knowl Discov 1(4):1\u20138","journal-title":"Data Anal Knowl Discov"},{"issue":"99","key":"3500_CR22","first-page":"1","volume":"99","author":"L Gui","year":"2020","unstructured":"Gui L, Jia L, Zhou J, Jia L (2020) Multi-task learning with mutual learning for joint sentiment classification and topic detection. IEEE Trans Knowl Data Eng 99(99):1\u20131","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"3500_CR23","doi-asserted-by":"publisher","first-page":"262","DOI":"10.1016\/j.ins.2021.04.029","volume":"570","author":"K Xiao","year":"2021","unstructured":"Xiao K, Qian Z, Qin B (2021) A graphical decomposition and similarity measurement approach for topic detection from online news[J]. Inf Sci 570:262\u2013277","journal-title":"Inf Sci"},{"issue":"5","key":"3500_CR24","doi-asserted-by":"publisher","first-page":"106391","DOI":"10.1016\/j.knosys.2020.106391","volume":"207","author":"F Xu","year":"2020","unstructured":"Xu F, Sheng VS, Wang M (2020) Near real-time topic-driven rumor detection in source microblogs. Knowl-Based Syst 207(5):106391","journal-title":"Knowl-Based Syst"},{"key":"3500_CR25","doi-asserted-by":"publisher","first-page":"3868C3881","DOI":"10.1007\/s10489-020-01779-0","volume":"50","author":"X Du","year":"2020","unstructured":"Du X, Zhu R, Zhao F et al (2020) A deceptive detection model based on topic, sentiment, and sentence structure information. Appl Intell 50:3868C3881","journal-title":"Appl Intell"},{"issue":"8","key":"3500_CR26","doi-asserted-by":"publisher","first-page":"2216","DOI":"10.1109\/TKDE.2016.2556661","volume":"28","author":"W Xie","year":"2016","unstructured":"Xie W, Zhu F, Jiang J, Lim EP, Wang K (2016) Topicsketch: real-time bursty topic detection from twitter. IEEE Trans Knowl Data Eng 28(8):2216\u20132229","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"3500_CR27","doi-asserted-by":"publisher","first-page":"1798","DOI":"10.1109\/TPAMI.2013.50","volume":"35.8","author":"Y Bengio","year":"2013","unstructured":"Bengio Y, Courville A, Vincent P (2013) Representation learning: a review and new perspectives. IEEE Trans Pattern Anal Mach Intell 35.8:1798\u20131828","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"3500_CR28","unstructured":"Buckman J et al (2018) Thermometer encoding: one hot way to resist adversarial examples. International conference on learning representations"},{"key":"3500_CR29","unstructured":"Salton G, McGill M J (1983) Introduction to modern information retrieval. mcgraw-hill"},{"issue":"1","key":"3500_CR30","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1111\/j.1540-6261.2010.01625.x","volume":"66","author":"T Loughran","year":"2011","unstructured":"Loughran T, McDonald B (2011) When is a liability not a liability? Textual analysis, dictionaries, and 10-Ks. J Financ 66(1):35\u201365","journal-title":"J Financ"},{"key":"3500_CR31","unstructured":"Hinton GE (1986) Learning distributed representations of concepts. Proceedings of the eighth annual conference of the cognitive science society, 1, pp 145\u2013157"},{"key":"3500_CR32","unstructured":"Mikolov T, Le QV, Sutskever I (2013) Exploiting similarities among languages for machine translation[J], arXiv preprint arXiv:1309.4168"},{"key":"3500_CR33","doi-asserted-by":"crossref","unstructured":"Pennington J, Socher R, Manning CD (2014) Glove: global vectors for word representation. Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP), pp 1532\u20131543","DOI":"10.3115\/v1\/D14-1162"},{"key":"3500_CR34","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1016\/j.inffus.2017.10.006","volume":"42","author":"Q Zhang","year":"2018","unstructured":"Zhang Q, Yang LT, Chen Z et al (2018) A survey on deep learning for big data. Inf Fusion 42:146\u2013157","journal-title":"Inf Fusion"},{"key":"3500_CR35","unstructured":"Sutskever I, Vinyals O, Le QV (2014) Sequence to sequence learning with neural networks. Advances in neural information processing systems, pp 3104\u20133112"},{"key":"3500_CR36","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser L, Polosukhin I (2017) Attention is all you need. ICML, arXiv:1706.03762"},{"issue":"2","key":"3500_CR37","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1016\/S0031-3203(02)00060-2","volume":"36","author":"A Likas","year":"2003","unstructured":"Likas A, Vlassis N, Verbeek JJ (2003) The global k-means clustering algorithm. Pattern Recogn 36(2):451\u2013461","journal-title":"Pattern Recogn"},{"key":"3500_CR38","doi-asserted-by":"crossref","unstructured":"Papka R, Allan J (1998) On-line new event detection using single-pass clustering. In: Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval. Melbourne, pp 37\u201345","DOI":"10.1145\/290941.290954"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-022-03500-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-022-03500-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-022-03500-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,19]],"date-time":"2022-11-19T10:39:04Z","timestamp":1668854344000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-022-03500-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,10]]},"references-count":38,"journal-issue":{"issue":"15","published-print":{"date-parts":[[2022,12]]}},"alternative-id":["3500"],"URL":"https:\/\/doi.org\/10.1007\/s10489-022-03500-9","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"type":"print","value":"0924-669X"},{"type":"electronic","value":"1573-7497"}],"subject":[],"published":{"date-parts":[[2022,4,10]]},"assertion":[{"value":"10 March 2022","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 April 2022","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}