{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T15:48:16Z","timestamp":1743004096763,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319992464"},{"type":"electronic","value":"9783319992471"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-99247-1_41","type":"book-chapter","created":{"date-parts":[[2018,8,10]],"date-time":"2018-08-10T10:26:21Z","timestamp":1533896781000},"page":"465-476","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Topic Extraction of Events on Social Media Using Reinforced Knowledge"],"prefix":"10.1007","author":[{"given":"Xuefei","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruifang","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,8,11]]},"reference":[{"key":"41_CR1","unstructured":"Agrawal, R., Srikant, R.: Fast algorithms for mining association rules in large databases. In: VLDB, pp. 487\u2013499 (1994)"},{"issue":"Jan","key":"41_CR2","first-page":"993","volume":"3","author":"DM Blei","year":"2003","unstructured":"Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent dirichlet allocation. J. Mach. Learn. Res. 3(Jan), 993\u20131022 (2003)","journal-title":"J. Mach. Learn. Res."},{"key":"41_CR3","unstructured":"Chang, J., Gerrish, S., Wang, C., Boyd-Graber, J.L., Blei, D.M.: Reading tea leaves: how humans interpret topic models. In: NIPS, pp. 288\u2013296 (2009)"},{"key":"41_CR4","unstructured":"Chen, Z., Liu, B.: Topic modeling using topics from many domains, lifelong learning and big data. In: ICML, pp. 703\u2013711 (2014)"},{"issue":"1","key":"41_CR5","doi-asserted-by":"publisher","first-page":"5228","DOI":"10.1073\/pnas.0307752101","volume":"101","author":"TL Griffiths","year":"2004","unstructured":"Griffiths, T.L., Steyvers, M.: Finding scientific topics. Proc. Natl. Acad. Sci. 101(1), 5228\u20135235 (2004)","journal-title":"Proc. Natl. Acad. Sci."},{"key":"41_CR6","doi-asserted-by":"crossref","unstructured":"Hong, L., Davison, B.D.: Empirical study of topic modeling in Twitter. In: Proceedings of the First Workshop on Social Media Analytics, pp. 80\u201388 (2010)","DOI":"10.1145\/1964858.1964870"},{"key":"41_CR7","doi-asserted-by":"crossref","unstructured":"Hu, W., Tsujii, J.: A latent concept topic model for robust topic inference using word embeddings. In: ACL, pp. 380\u2013386 (2016)","DOI":"10.18653\/v1\/P16-2062"},{"key":"41_CR8","doi-asserted-by":"crossref","unstructured":"Li, J., Liao, M., Gao, W., He, Y., Wong, K.F.: Topic extraction from microblog posts using conversation structures. In: ACL (2016)","DOI":"10.18653\/v1\/P16-1199"},{"key":"41_CR9","unstructured":"Li, Y., Liu, T., Jiang, J., Zhang, L.: Hashtag recommendation with topical attention-based LSTM. In: COLING (2016)"},{"key":"41_CR10","doi-asserted-by":"crossref","unstructured":"Mehrotra, R., Sanner, S., Buntine, W., Xie, L.: Improving LDA topic models for microblogs via tweet pooling and automatic labeling. In: SIGIR, pp. 889\u2013892 (2013)","DOI":"10.1145\/2484028.2484166"},{"key":"41_CR11","unstructured":"Mikolov, T., Yih, W.T., Zweig, G.: Linguistic regularities in continuous space word representations. In: NAACL, pp. 746\u2013751 (2013)"},{"key":"41_CR12","unstructured":"Mimno, D., Wallach, H.M., Talley, E., Leenders, M., McCallum, A.: Optimizing semantic coherence in topic models. In: EMNLP, pp. 262\u2013272 (2011)"},{"key":"41_CR13","unstructured":"Quan, X., Kit, C., Ge, Y., Pan, S.J.: Short and sparse text topic modeling via self-aggregation. In: IJCAI, pp. 2270\u20132276 (2015)"},{"key":"41_CR14","unstructured":"Sridhar, V.K.R.: Unsupervised topic modeling for short texts using distributed representations of words. In: NAACL, pp. 192\u2013200 (2015)"},{"key":"41_CR15","doi-asserted-by":"crossref","unstructured":"Tang, J., Zhang, M., Mei, Q.: One theme in all views: modeling consensus topics in multiple contexts. In: KDD, pp. 5\u201313 (2013)","DOI":"10.1145\/2487575.2487682"},{"key":"41_CR16","doi-asserted-by":"crossref","unstructured":"Xing, C., et al.: Topic aware neural response generation. In: AAAI, pp. 3351\u20133357 (2017)","DOI":"10.1609\/aaai.v31i1.10981"},{"key":"41_CR17","doi-asserted-by":"crossref","unstructured":"Yan, X., Guo, J., Lan, Y., Cheng, X.: A biterm topic model for short texts. In: WWW, pp. 1445\u20131456 (2013)","DOI":"10.1145\/2488388.2488514"},{"key":"41_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"338","DOI":"10.1007\/978-3-642-20161-5_34","volume-title":"Advances in Information Retrieval","author":"WX Zhao","year":"2011","unstructured":"Zhao, W.X., et al.: Comparing Twitter and traditional media using topic models. In: Clough, P., et al. (eds.) ECIR 2011. LNCS, vol. 6611, pp. 338\u2013349. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-20161-5_34"},{"key":"41_CR19","doi-asserted-by":"crossref","unstructured":"Zhuang, H., Rahman, R., Hu, X., Guo, T., Hui, P., Aberer, K.: Data summarization with social contexts. In: CIKM, pp. 397\u2013406 (2016)","DOI":"10.1145\/2983323.2983736"}],"container-title":["Lecture Notes in Computer Science","Knowledge Science, Engineering and Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-99247-1_41","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T08:39:47Z","timestamp":1710232787000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-99247-1_41"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319992464","9783319992471"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-99247-1_41","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"11 August 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"KSEM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Knowledge Science, Engineering and Management","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Changchun","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 August 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 August 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ksem2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/ksem2018.venue.link\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"262","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"62","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"26","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"24% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.1","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"10","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"We have 3 reviews for 235 submissions, 4 reviews for 25 submissions and 5 review for 2 submissions.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}