{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,11]],"date-time":"2025-06-11T04:17:51Z","timestamp":1749615471189,"version":"3.41.0"},"publisher-location":"Cham","reference-count":44,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031880353"},{"type":"electronic","value":"9783031880360"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-3-031-88036-0_4","type":"book-chapter","created":{"date-parts":[[2025,4,14]],"date-time":"2025-04-14T08:09:15Z","timestamp":1744618155000},"page":"87-106","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Iterative Improvement of\u00a0an\u00a0Additively Regularized Topic Model"],"prefix":"10.1007","author":[{"given":"Alex","family":"Gorbulev","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7930-3650","authenticated-orcid":false,"given":"Vasiliy","family":"Alekseev","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4244-4270","authenticated-orcid":false,"given":"Konstantin","family":"Vorontsov","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,4,15]]},"reference":[{"key":"4_CR1","doi-asserted-by":"publisher","first-page":"102131","DOI":"10.1016\/j.is.2022.102131","volume":"112","author":"A Abdelrazek","year":"2023","unstructured":"Abdelrazek, A., Eid, Y., Gawish, E., Medhat, W., Hassan, A.: Topic modeling algorithms and applications: a survey. Inf. Syst. 112, 102131 (2023)","journal-title":"Inf. Syst."},{"key":"4_CR2","unstructured":"Alekseev, V., Bulatov, V., Vorontsov, K.: Intra-text coherence as a measure of topic models\u2019 interpretability. In: Computational Linguistics and Intellectual Technologies: Papers from the Annual International Conference Dialogue, pp. 1\u201313 (2018)"},{"key":"4_CR3","doi-asserted-by":"crossref","unstructured":"Alekseev, V., Egorov, E., Vorontsov, K., Goncharov, A., Nurumov, K., Buldybayev, T.: TopicBank: collection of coherent topics using multiple model training with their further use for topic model validation. Data Knowl. Eng. (2021)","DOI":"10.1016\/j.datak.2021.101921"},{"key":"4_CR4","doi-asserted-by":"publisher","unstructured":"Aqui, J., Hosein, M.: Mobile ad-hoc networks topic modelling and dataset querying. In: 2022 IEEE 2nd International Conference on Mobile Networks and Wireless Communications (ICMNWC), pp.\u00a01\u20136. IEEE (2022). https:\/\/doi.org\/10.1109\/ICMNWC56175.2022.10031921","DOI":"10.1109\/ICMNWC56175.2022.10031921"},{"key":"4_CR5","unstructured":"Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent Dirichlet allocation. J. Mach. Learn. Res. 3(Jan), 993\u20131022 (2003)"},{"key":"4_CR6","doi-asserted-by":"publisher","unstructured":"Bogovi\u0107, P.K., Me\u0161trovi\u0107, A., Beliga, S., Martin\u010di\u0107-Ip\u0161i\u0107, S.: Topic modelling of Croatian news during COVID-19 pandemic. In: 2021 44th International Convention on Information, Communication and Electronic Technology (MIPRO), pp. 1044\u20131051 (2021). https:\/\/doi.org\/10.23919\/MIPRO52101.2021.9597125","DOI":"10.23919\/MIPRO52101.2021.9597125"},{"key":"4_CR7","doi-asserted-by":"publisher","unstructured":"Bulatov, V., Alekseev, V., Vorontsov, K.: Determination of the number of topics intrinsically: Is it possible? In: Recent Trends in Analysis of Images, Social Networks and Texts, pp. 3\u201317. Springer, Cham (2024). https:\/\/doi.org\/10.1007\/978-3-031-67008-4_1","DOI":"10.1007\/978-3-031-67008-4_1"},{"key":"4_CR8","unstructured":"Bulatov, V., et al.: TopicNet: making additive regularisation for topic modelling accessible. In: Proceedings of The 12th Language Resources and Evaluation Conference, pp. 6745\u20136752 (2020)"},{"key":"4_CR9","doi-asserted-by":"crossref","unstructured":"Cao, J., Xia, T., Li, J., Zhang, Y., Tang, S.: A density-based method for adaptive LDA model selection. Neurocomputing (2009)","DOI":"10.1016\/j.neucom.2008.06.011"},{"key":"4_CR10","unstructured":"Chang, J., Gerrish, S., Wang, C., Boyd-Graber, J., Blei, D.: Reading tea leaves: How humans interpret topic models. In: NIPS 2009, vol. 22 (2009)"},{"issue":"1","key":"4_CR11","first-page":"22","volume":"16","author":"K Church","year":"1990","unstructured":"Church, K., Hanks, P.: Word association norms, mutual information, and lexicography. Comput. Linguist. 16(1), 22\u201329 (1990)","journal-title":"Comput. Linguist."},{"key":"4_CR12","doi-asserted-by":"crossref","unstructured":"Dagan, I., Marcus, S., Markovitch, S.: Contextual word similarity and estimation from sparse data. In: 31st Annual Meeting of the Association for Computational Linguistics, pp. 164\u2013171 (1993)","DOI":"10.3115\/981574.981596"},{"key":"4_CR13","doi-asserted-by":"crossref","unstructured":"Dai, S.C., Xiong, A., Ku, L.W.: LLM-in-the-loop: leveraging large language model for thematic analysis. arXiv preprint arXiv:2310.15100 (2023)","DOI":"10.18653\/v1\/2023.findings-emnlp.669"},{"key":"4_CR14","doi-asserted-by":"crossref","unstructured":"Deveaud, R., SanJuan, E., Bellot, P.: Accurate and effective latent concept modeling for ad hoc information retrieval. Document num\u00e9rique (2014)","DOI":"10.3166\/dn.17.1.61-84"},{"key":"4_CR15","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)"},{"key":"4_CR16","doi-asserted-by":"publisher","unstructured":"DiMaggio, P., Nag, M., Blei, D.: Exploiting affinities between topic modeling and the sociological perspective on culture: application to newspaper coverage of U.S. government arts funding. Poetics 41(6), 570\u2013606 (2013). https:\/\/doi.org\/10.1016\/j.poetic.2013.08.004","DOI":"10.1016\/j.poetic.2013.08.004"},{"key":"4_CR17","doi-asserted-by":"crossref","unstructured":"Egorov, E., Nikitin, F., Alekseev, V., Goncharov, A., Vorontsov, K.: Topic modelling for extracting behavioral patterns from transactions data. In: 2019 International Conference on Artificial Intelligence: Applications and Innovations (IC-AIAI), pp. 44\u2013444. IEEE (2019)","DOI":"10.1109\/IC-AIAI48757.2019.00015"},{"key":"4_CR18","unstructured":"Fano, R.M.: Transmission of Information: A Statistical Theory of Communications. MIT Press (1968)"},{"key":"4_CR19","doi-asserted-by":"crossref","unstructured":"Gerasimenko, N., Chernyavskiy, A., Nikiforova, M., Ianina, A., Vorontsov, K.: Incremental topic modeling for scientific trend topics extraction. In: Proceedings of the International Conference\u2014Dialogue (2023)","DOI":"10.28995\/2075-7182-2023-22-88-103"},{"issue":"1","key":"4_CR20","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1016\/j.jce.2018.10.004","volume":"47","author":"P Grajzl","year":"2019","unstructured":"Grajzl, P., Murrell, P.: Toward understanding 17th century English culture: a structural topic model of Francis Bacon\u2019s ideas. J. Comput. Econ. 47(1), 111\u2013135 (2019)","journal-title":"J. Comput. Econ."},{"key":"4_CR21","doi-asserted-by":"crossref","unstructured":"Griffiths, T.L., Steyvers, M.: Finding scientific topics. Proc. Natl. Acad. Sci. (2004)","DOI":"10.1073\/pnas.0307752101"},{"key":"4_CR22","unstructured":"Grootendorst, M.: BERTopic: neural topic modeling with a class-based TF-IDF procedure. arXiv preprint arXiv:2203.05794 (2022)"},{"key":"4_CR23","unstructured":"Hofmann, T.: Probabilistic latent semantic analysis. In: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, pp. 289\u2013296. Morgan Kaufmann Publishers Inc. (1999)"},{"issue":"6","key":"4_CR24","doi-asserted-by":"publisher","first-page":"1515","DOI":"10.20537\/2076-7633-2020-12-6-1515-1528","volume":"12","author":"I Irkhin","year":"2020","unstructured":"Irkhin, I., Bulatov, V., Vorontsov, K.: Additive regularizarion of topic models with fast text vectorizartion (in Russian). Comput. Res. Model. 12(6), 1515\u20131528 (2020)","journal-title":"Comput. Res. Model."},{"key":"4_CR25","doi-asserted-by":"crossref","unstructured":"Jelinek, F., Mercer, R.L., Bahl, L.R., Baker, J.K.: Perplexity\u2014a measure of the difficulty of speech recognition tasks. J. Acoust. Soc. Am. 62(S1), S63\u2013S63 (1977)","DOI":"10.1121\/1.2016299"},{"key":"4_CR26","doi-asserted-by":"publisher","first-page":"123280","DOI":"10.1109\/ACCESS.2021.3109425","volume":"9","author":"D Koren\u010di\u0107","year":"2021","unstructured":"Koren\u010di\u0107, D., Ristov, S., Repar, J., \u0160najder, J.: A topic coverage approach to evaluation of topic models. IEEE Access 9, 123280\u2013123312 (2021)","journal-title":"IEEE Access"},{"key":"4_CR27","doi-asserted-by":"crossref","unstructured":"Lau, J.H., Newman, D., Baldwin, T.: Machine reading tea leaves: automatically evaluating topic coherence and topic model quality. In: Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, pp. 530\u2013539 (2014)","DOI":"10.3115\/v1\/E14-1056"},{"issue":"1","key":"4_CR28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40064-016-3252-8","volume":"5","author":"L Liu","year":"2016","unstructured":"Liu, L., Tang, L., Dong, W., Yao, S., Zhou, W.: An overview of topic modeling and its current applications in bioinformatics. Springerplus 5(1), 1\u201322 (2016). https:\/\/doi.org\/10.1186\/s40064-016-3252-8","journal-title":"Springerplus"},{"issue":"11","key":"4_CR29","doi-asserted-by":"publisher","first-page":"205","DOI":"10.21105\/joss.00205","volume":"2","author":"L McInnes","year":"2017","unstructured":"McInnes, L., Healy, J., Astels, S., et al.: hdbscan: hierarchical density based clustering. J. Open Source Softw. 2(11), 205 (2017)","journal-title":"J. Open Source Softw."},{"key":"4_CR30","doi-asserted-by":"crossref","unstructured":"McInnes, L., Healy, J., Melville, J.: UMAP: Uniform manifold approximation and projection for dimension reduction. arXiv preprint arXiv:1802.03426 (2018)","DOI":"10.21105\/joss.00861"},{"key":"4_CR31","unstructured":"Mimno, D., Wallach, H., Talley, E., Leenders, M., McCallum, A.: Optimizing semantic coherence in topic models. In: Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, pp. 262\u2013272. Association for Computational Linguistics (2011)"},{"key":"4_CR32","unstructured":"Newman, D., Lau, J.H., Grieser, K., Baldwin, T.: Automatic evaluation of topic coherence. In: Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, pp. 100\u2013108. Association for Computational Linguistics (2010)"},{"issue":"3","key":"4_CR33","doi-asserted-by":"publisher","first-page":"214","DOI":"10.1080\/23251042.2020.1866281","volume":"7","author":"F Rabitz","year":"2021","unstructured":"Rabitz, F., Tele\u0161ien\u0117, A., Zolubien\u0117, E.: Topic modelling the news media representation of climate change. Environ. Sociol. 7(3), 214\u2013224 (2021). https:\/\/doi.org\/10.1080\/23251042.2020.1866281","journal-title":"Environ. Sociol."},{"key":"4_CR34","doi-asserted-by":"crossref","unstructured":"Rahimi, H., Naacke, H., Constantin, C., Amann, B.: ANTM: aligned neural topic models for exploring evolving topics. In: Transactions on Large-Scale Data-and Knowledge-Centered Systems LVI: Special Issue on Data Management-Principles, Technologies, and Applications, pp. 76\u201397. Springer (2024)","DOI":"10.1007\/978-3-662-69603-3_3"},{"key":"4_CR35","doi-asserted-by":"crossref","unstructured":"R\u00f6der, M., Both, A., Hinneburg, A.: Exploring the space of topic coherence measures. In: Proceedings of the Eighth ACM International Conference on Web Search and Data Mining, pp. 399\u2013408 (2015)","DOI":"10.1145\/2684822.2685324"},{"key":"4_CR36","doi-asserted-by":"publisher","first-page":"1192","DOI":"10.1007\/s10664-015-9379-3","volume":"21","author":"C Rosen","year":"2016","unstructured":"Rosen, C., Shihab, E.: What are mobile developers asking about? A large scale study using stack overflow. Empir. Softw. Eng. 21, 1192\u20131223 (2016)","journal-title":"Empir. Softw. Eng."},{"issue":"1","key":"4_CR37","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1108\/eb026526","volume":"28","author":"K Sparck Jones","year":"1972","unstructured":"Sparck Jones, K.: A statistical interpretation of term specificity and its application in retrieval. J. Doc. 28(1), 11\u201321 (1972)","journal-title":"J. Doc."},{"issue":"4","key":"4_CR38","first-page":"7","volume":"23","author":"AV Suhareva","year":"2019","unstructured":"Suhareva, A.V., Voroncov, K.V.: Postroenie polnogo nabora tem verojatnostnyh temati\u010deskih modelej (in Russian). Intellektual\u2019nye sistemy. Teorija i prilo\u017eenija 23(4), 7\u201323 (2019)","journal-title":"Intellektual\u2019nye sistemy. Teorija i prilo\u017eenija"},{"key":"4_CR39","doi-asserted-by":"crossref","unstructured":"Veselova, E., Vorontsov, K.: Topic balancing with additive regularization of topic models. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, pp. 59\u201365 (2020)","DOI":"10.18653\/v1\/2020.acl-srw.9"},{"key":"4_CR40","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"370","DOI":"10.1007\/978-3-319-26123-2_36","volume-title":"Analysis of Images, Social Networks and Texts","author":"K Vorontsov","year":"2015","unstructured":"Vorontsov, K., Frei, O., Apishev, M., Romov, P., Dudarenko, M.: BigARTM: open source library for regularized multimodal topic modeling of large collections. In: Khachay, M.Y., Konstantinova, N., Panchenko, A., Ignatov, D.I., Labunets, V.G. (eds.) AIST 2015. CCIS, vol. 542, pp. 370\u2013381. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-26123-2_36"},{"key":"4_CR41","unstructured":"Wallach, H., Mimno, D., McCallum, A.: Rethinking LDA: Why priors matter. In: Advances in Neural Information Processing Systems, vol. 22 (2009)"},{"key":"4_CR42","unstructured":"Wang, X., Yang, Y.: Neural topic model with attention for supervised learning. In: International Conference on Artificial Intelligence and Statistics, pp. 1147\u20131156. PMLR (2020)"},{"key":"4_CR43","doi-asserted-by":"crossref","unstructured":"Yang, X., Zhao, H., Phung, D., Buntine, W., Du, L.: LLM reading tea leaves: automatically evaluating topic models with large language models. arXiv preprint arXiv:2406.09008 (2024)","DOI":"10.1162\/tacl_a_00744"},{"key":"4_CR44","doi-asserted-by":"crossref","unstructured":"Zhao, W., Zou, W., Chen, J.J.: Topic modeling for cluster analysis of large biological and medical datasets. In: BMC Bioinformatics, vol.\u00a015, pp. 1\u201311. Springer (2014)","DOI":"10.1186\/1471-2105-15-S11-S11"}],"container-title":["Lecture Notes in Computer Science","Analysis of Images, Social Networks and Texts"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-88036-0_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,11]],"date-time":"2025-06-11T02:57:25Z","timestamp":1749610645000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-88036-0_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031880353","9783031880360"],"references-count":44,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-88036-0_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"15 April 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that\u00a0are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"AIST","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Analysis of Images, Social Networks and Texts","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bishkek","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kyrgyzstan","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aist2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/aistconf.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}