{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T19:31:17Z","timestamp":1774121477764,"version":"3.50.1"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783031230271","type":"print"},{"value":"9783031230288","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-23028-8_8","type":"book-chapter","created":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T02:36:12Z","timestamp":1672540572000},"page":"74-83","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Sentiment Analysis from\u00a0User Reviews Using a\u00a0Hybrid Generative-Discriminative HMM-SVM Approach"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6149-1742","authenticated-orcid":false,"given":"Rim","family":"Nasfi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7224-7940","authenticated-orcid":false,"given":"Nizar","family":"Bouguila","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,1,1]]},"reference":[{"issue":"2","key":"8_CR1","doi-asserted-by":"publisher","first-page":"450","DOI":"10.1109\/TCSS.2019.2956957","volume":"7","author":"K Chakraborty","year":"2020","unstructured":"Chakraborty, K., Bhattacharyya, S., Bag, R.: A survey of sentiment analysis from social media data. IEEE Trans. Comput. Soc. Syst. 7(2), 450\u2013464 (2020)","journal-title":"IEEE Trans. Comput. Soc. Syst."},{"key":"8_CR2","doi-asserted-by":"crossref","unstructured":"Liu, B.: Sentiment analysis: mining opinions, sentiments, and emotions. Cambridge University Press, (2020)","DOI":"10.1017\/9781108639286"},{"key":"8_CR3","unstructured":"Wang, Y., Pal, A.: Detecting emotions in social media: a constrained optimization approach, In: Proceedings of the 24th International Conference on Artificial Intelligence, ser. IJCAI\u201915. AAAI Press, pp. 996\u20131002 (2015)"},{"issue":"3","key":"8_CR4","doi-asserted-by":"publisher","first-page":"963","DOI":"10.1007\/s40815-019-00606-0","volume":"21","author":"R Liang","year":"2019","unstructured":"Liang, R., Wang, J.-Q.: A linguistic intuitionistic cloud decision support model with sentiment analysis for product selection in e-commerce. Int. J. Fuzzy Syst. 21(3), 963\u2013977 (2019)","journal-title":"Int. J. Fuzzy Syst."},{"issue":"1","key":"8_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-031-02145-9","volume":"5","author":"B Liu","year":"2012","unstructured":"Liu, B.: Sentiment analysis and opinion mining. synth. lect. hum. lang. technol. 5(1), 1\u2013167 (2012)","journal-title":"synth. lect. hum. lang. technol."},{"key":"8_CR6","unstructured":"Cortis, K., Davis, B.: Over a decade of social opinion mining, arXiv e-prints, pp. arXiv-2012, (2020)"},{"key":"8_CR7","doi-asserted-by":"publisher","first-page":"116","DOI":"10.1016\/j.ins.2020.03.028","volume":"524","author":"N Zamzami","year":"2020","unstructured":"Zamzami, N., Bouguila, N.: High-dimensional count data clustering based on an exponential approximation to the multinomial beta-liouville distribution. Inf. Sci. 524, 116\u2013135 (2020)","journal-title":"Inf. Sci."},{"key":"8_CR8","unstructured":"Rubinstein, Y. D., Hastie, T., et al.: Discriminative vs informative learning. in KDD, vol. 5, pp. 49\u201353 (1997)"},{"key":"8_CR9","doi-asserted-by":"crossref","unstructured":"Perikos, I., Kardakis, S., Paraskevas, M., Hatzilygeroudis, I.: Hidden markov models for sentiment analysis in social media, In: 2019 IEEE International Conference on Big Data, Cloud Computing, Data Science Engineering (BCD), pp. 130\u2013135 (2019)","DOI":"10.1109\/BCD.2019.8885272"},{"key":"8_CR10","doi-asserted-by":"publisher","unstructured":"Nasfi, R.,Bouguila , N.: Online learning of inverted beta-Liouville HMMs for anomaly detection in crowd scenes, In: Hidden Markov Models and Applications. Springer, 2022, pp. 177\u2013198 https:\/\/doi.org\/10.1007\/978-3-030-99142-5_7","DOI":"10.1007\/978-3-030-99142-5_7"},{"issue":"5","key":"8_CR11","doi-asserted-by":"publisher","first-page":"1443","DOI":"10.1007\/s00521-012-1094-z","volume":"23","author":"T Bdiri","year":"2013","unstructured":"Bdiri, T., Bouguila, N.: Bayesian learning of inverted dirichlet mixtures for svm kernels generation. Neural Comput. Appl. 23(5), 1443\u20131458 (2013)","journal-title":"Neural Comput. Appl."},{"key":"8_CR12","doi-asserted-by":"crossref","unstructured":"Wang, C., Zhao, X., Wu, Z., Liu, Y.: Motion pattern analysis in crowded scenes based on hybrid generative-discriminative feature maps, In 2013 IEEE International Conference on Image Processing. IEEE, pp. 2837\u20132841 (2013)","DOI":"10.1109\/ICIP.2013.6738584"},{"issue":"4","key":"8_CR13","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1145\/2436256.2436274","volume":"56","author":"R Feldman","year":"2013","unstructured":"Feldman, R.: Techniques and applications for sentiment analysis. Commun. ACM 56(4), 82\u201389 (2013)","journal-title":"Commun. ACM"},{"key":"8_CR14","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1016\/j.neucom.2020.02.018","volume":"395","author":"N Liu","year":"2020","unstructured":"Liu, N., Shen, B.: Rememnn: a novel memory neural network for powerful interaction in aspect-based sentiment analysis. Neurocomputing 395, 66\u201377 (2020)","journal-title":"Neurocomputing"},{"key":"8_CR15","doi-asserted-by":"crossref","unstructured":"G. Gautam, G., Yadav, D.: Sentiment analysis of twitter data using machine learning approaches and semantic analysis, In: 2014 Seventh International Conference on Contemporary Computing (IC3), pp. 437\u2013442 (2014)","DOI":"10.1109\/IC3.2014.6897213"},{"issue":"2","key":"8_CR16","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1109\/5.18626","volume":"77","author":"L Rabiner","year":"1989","unstructured":"Rabiner, L.: A tutorial on hidden markov models and selected applications in speech recognition. Proc. IEEE 77(2), 257\u2013286 (1989)","journal-title":"Proc. IEEE"},{"key":"8_CR17","doi-asserted-by":"publisher","unstructured":"Jin, W., Ho, H. H., Srihari, R. K.: Opinionminer: a novel machine learning system for web opinion mining and extraction, In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ser. KDD \u201909. New York, NY, USA: Association for Computing Machinery, pp. 1195\u20131204. (2009) https:\/\/doi.org\/10.1145\/1557019.1557148","DOI":"10.1145\/1557019.1557148"},{"key":"8_CR18","doi-asserted-by":"crossref","unstructured":"Rabiner, L., Juang, B.: An introduction to hidden markov models, IEEE assp magazine, 3(1), pp. 4\u201316 (1986)","DOI":"10.1109\/MASSP.1986.1165342"},{"issue":"3","key":"8_CR19","first-page":"423","volume":"9","author":"G Lingappaiah","year":"1976","unstructured":"Lingappaiah, G.: On the generalised inverted dirichlet distribution. Demostratio Math. 9(3), 423\u2013433 (1976)","journal-title":"Demostratio Math."},{"issue":"2\u20133","key":"8_CR20","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1080\/00437956.1954.11659520","volume":"10","author":"ZS Harris","year":"1954","unstructured":"Harris, Z.S.: Distributional structure. Word 10(2\u20133), 146\u2013162 (1954)","journal-title":"Word"},{"key":"8_CR21","doi-asserted-by":"crossref","unstructured":"McAuley, J., Leskovec, J.: Hidden factors and hidden topics: understanding rating dimensions with review text, In: Proceedings of the 7th ACM Conference on Recommender Systems, ser. RecSys \u201913. Association for Computing Machinery, pp. 165\u2013172 (2013)","DOI":"10.1145\/2507157.2507163"},{"key":"8_CR22","unstructured":"Maas, A.L., Daly, R.E., Pham, P.T., Huang, D., Ng, A.Y., Potts, C.: Learning word vectors for sentiment analysis, In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies Portland, Oregon, USA: Association for Computational Linguistics, pp. 142\u2013150 June 2011 http:\/\/www.aclweb.org\/anthology\/P11-1015"}],"container-title":["Lecture Notes in Computer Science","Structural, Syntactic, and Statistical Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-23028-8_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T02:54:28Z","timestamp":1672541668000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-23028-8_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031230271","9783031230288"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-23028-8_8","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"1 January 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"S+SSPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Montreal, QC","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 August 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 August 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"sspr2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/sspr2022.encs.concordia.ca\/","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":"50","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":"32","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":"0","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":"64% - 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","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":"2","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}