{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T19:20:29Z","timestamp":1743103229743,"version":"3.40.3"},"publisher-location":"Cham","reference-count":38,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030616151"},{"type":"electronic","value":"9783030616168"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","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":[[2020]]},"DOI":"10.1007\/978-3-030-61616-8_61","type":"book-chapter","created":{"date-parts":[[2020,10,16]],"date-time":"2020-10-16T23:07:42Z","timestamp":1602889662000},"page":"761-772","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Boosting Tricks for Word Mover\u2019s Distance"],"prefix":"10.1007","author":[{"given":"Konstantinos","family":"Skianis","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fragkiskos D.","family":"Malliaros","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nikolaos","family":"Tziortziotis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michalis","family":"Vazirgiannis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,10,14]]},"reference":[{"issue":"Feb","key":"61_CR1","first-page":"1137","volume":"3","author":"Y Bengio","year":"2003","unstructured":"Bengio, Y., Ducharme, R., Vincent, P., Jauvin, C.: A neural probabilistic language model. J. Mach. Learn. Res. 3(Feb), 1137\u20131155 (2003)","journal-title":"J. Mach. Learn. Res."},{"key":"61_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1007\/3-540-36618-0_22","volume-title":"Advances in Information Retrieval","author":"B Bigi","year":"2003","unstructured":"Bigi, B.: Using Kullback-Leibler distance for text categorization. In: Sebastiani, F. (ed.) ECIR 2003. LNCS, vol. 2633, pp. 305\u2013319. Springer, Heidelberg (2003). https:\/\/doi.org\/10.1007\/3-540-36618-0_22"},{"key":"61_CR3","doi-asserted-by":"crossref","unstructured":"Brokos, G.I., Malakasiotis, P., Androutsopoulos, I.: Using centroids of word embeddings and word mover\u2019s distance for biomedical document retrieval in question answering. In: Proceedings of the 15th Workshop on Biomedical Natural Language Processing (2016)","DOI":"10.18653\/v1\/W16-2915"},{"key":"61_CR4","unstructured":"Cachopo, A.M.d.J.C.: Improving methods for single-label text categorization. Instituto Superior T\u00e9cnico, Portugal (2007)"},{"key":"61_CR5","unstructured":"Chen, L., et al.: Adversarial text generation via feature-mover\u2019s distance. In: Advances in Neural Information Processing Systems (2018)"},{"key":"61_CR6","doi-asserted-by":"crossref","unstructured":"Collobert, R., Weston, J.: A unified architecture for natural language processing: Deep neural networks with multitask learning. In: Proceedings of the 25th International Conference on Machine Learning, pp. 160\u2013167. ACM (2008)","DOI":"10.1145\/1390156.1390177"},{"key":"61_CR7","doi-asserted-by":"crossref","unstructured":"Das, R., Zaheer, M., Dyer, C.: Gaussian LDA for topic models with word embeddings. In: Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). Association for Computational Linguistics (2015)","DOI":"10.3115\/v1\/P15-1077"},{"key":"61_CR8","doi-asserted-by":"crossref","unstructured":"Davis, J.V., Kulis, B., Jain, P., Sra, S., Dhillon, I.S.: Information-theoretic metric learning. In: Proceedings of the 24th International Conference on Machine Learning, pp. 209\u2013216. ACM (2007)","DOI":"10.1145\/1273496.1273523"},{"issue":"6","key":"61_CR9","doi-asserted-by":"publisher","first-page":"391","DOI":"10.1002\/(SICI)1097-4571(199009)41:6<391::AID-ASI1>3.0.CO;2-9","volume":"41","author":"S Deerwester","year":"1990","unstructured":"Deerwester, S., Dumais, S.T., Furnas, G.W., Landauer, T.K., Harshman, R.: Indexing by latent semantic analysis. J. Am. Soc. Inf. Sci. 41(6), 391 (1990)","journal-title":"J. Am. Soc. Inf. Sci."},{"key":"61_CR10","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: Bert: pre-training of deep bidirectional transformers for language understanding. In: NAACL 2019, (2019)"},{"key":"61_CR11","unstructured":"Globerson, A., Roweis, S.T.: Metric learning by collapsing classes. In: Advances in Neural Information Processing Systems, pp. 451\u2013458 (2006)"},{"key":"61_CR12","unstructured":"Goldberger, J., Hinton, G.E., Roweis, S.T., Salakhutdinov, R.R.: Neighbourhood components analysis. In: Advances in Neural Information Processing Systems, pp. 513\u2013520 (2005)"},{"issue":"2\u20133","key":"61_CR13","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":"61_CR14","unstructured":"Huang, G., Guo, C., Kusner, M.J., Sun, Y., Sha, F., Weinberger, K.Q.: Supervised word mover\u2019s distance. In: Advances in Neural Information Processing Systems, pp. 4862\u20134870 (2016)"},{"key":"61_CR15","unstructured":"Johnson, R., Zhang, T.: Supervised and semi-supervised text categorization using lstm for region embeddings. In: Proceedings of the 33rd International Conference on International Conference on Machine Learning - Volume 48, ICML 2016, pp. 526\u2013534. JMLR.org (2016). http:\/\/dl.acm.org\/citation.cfm?id=3045390.3045447"},{"key":"61_CR16","unstructured":"Kedem, D., Tyree, S., Sha, F., Lanckriet, G.R., Weinberger, K.Q.: Non-linear metric learning. In: Advances in Neural Information Processing Systems, pp. 2573\u20132581 (2012)"},{"key":"61_CR17","doi-asserted-by":"publisher","first-page":"122","DOI":"10.1016\/j.jbi.2017.09.014","volume":"75","author":"S Kim","year":"2017","unstructured":"Kim, S., Fiorini, N., Wilbur, W.J., Lu, Z.: Bridging the gap: Incorporating a semantic similarity measure for effectively mapping pubmed queries to documents. J. Biomed. Inform. 75, 122\u2013127 (2017)","journal-title":"J. Biomed. Inform."},{"key":"61_CR18","unstructured":"Kim, Y.: Convolutional neural networks for sentence classification. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, EMNLP 2014, 25\u201329 October 2014, Doha, Qatar, A meeting of SIGDAT, a Special Interest Group of the ACL, pp. 1746\u20131751 (2014). http:\/\/aclweb.org\/anthology\/D\/D14\/D14-1181.pdf"},{"key":"61_CR19","unstructured":"Kusner, M.J., Sun, Y., Kolkin, N.I., Weinberger, K.Q.: From word embeddings to document distances. In: ICML (2015)"},{"key":"61_CR20","doi-asserted-by":"crossref","unstructured":"Liu, Y., Liu, Z., Chua, T.S., Sun, M.: Topical word embeddings. In: AAAI, pp. 2418\u20132424 (2015)","DOI":"10.1609\/aaai.v29i1.9522"},{"key":"61_CR21","doi-asserted-by":"crossref","unstructured":"Malliaros, F.D., Skianis, K.: Graph-based term weighting for text categorization. In: 2015 IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 1473\u20131479. IEEE (2015)","DOI":"10.1145\/2808797.2808872"},{"key":"61_CR22","unstructured":"Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space. In: ICLR Workshop (2013)"},{"key":"61_CR23","doi-asserted-by":"crossref","unstructured":"Nikolentzos, G., Meladianos, P., Rousseau, F., Stavrakas, Y., Vazirgiannis, M.: Shortest-path graph kernels for document similarity. In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp. 1890\u20131900 (2017)","DOI":"10.18653\/v1\/D17-1202"},{"key":"61_CR24","doi-asserted-by":"crossref","unstructured":"Peters, M.E., et al.: Deep contextualized word representations. In: Proceedings of NAACL (2018)","DOI":"10.18653\/v1\/N18-1202"},{"issue":"3","key":"61_CR25","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1108\/eb046814","volume":"14","author":"MF Porter","year":"1980","unstructured":"Porter, M.F.: An algorithm for suffix stripping. Program 14(3), 130\u2013137 (1980)","journal-title":"Program"},{"key":"61_CR26","unstructured":"Puurula, A.: Cumulative progress in language models for information retrieval. In: Proceedings of the Australasian Language Technology Association Workshop 2013 (ALTA 2013), pp. 96\u2013100 (2013)"},{"key":"61_CR27","doi-asserted-by":"crossref","unstructured":"Rousseau, F., Vazirgiannis, M.: Graph-of-word and TW-IDF: new approach to ad hoc IR. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 59\u201368. ACM (2013)","DOI":"10.1145\/2505515.2505671"},{"key":"61_CR28","unstructured":"Salton, G.: The smart retrieval system\u2013experiments in automatic document processing (1971)"},{"issue":"11","key":"61_CR29","doi-asserted-by":"publisher","first-page":"613","DOI":"10.1145\/361219.361220","volume":"18","author":"G Salton","year":"1975","unstructured":"Salton, G., Wong, A., Yang, C.S.: A vector space model for automatic indexing. Commun. ACM 18(11), 613\u2013620 (1975)","journal-title":"Commun. ACM"},{"key":"61_CR30","doi-asserted-by":"crossref","unstructured":"Schofield, A., Magnusson, M., Mimno, D.: Pulling out the stops: rethinking stopword removal for topic models. In: Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, vol. 2, pp. 432\u2013436 (2017)","DOI":"10.18653\/v1\/E17-2069"},{"key":"61_CR31","doi-asserted-by":"crossref","unstructured":"Skianis, K., Rousseau, F., Vazirgiannis, M.: Regularizing text categorization with clusters of words. In: Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pp. 1827\u20131837 (2016)","DOI":"10.18653\/v1\/D16-1188"},{"key":"61_CR32","doi-asserted-by":"crossref","unstructured":"Stone, B., Dennis, S., Kwantes, P.J.: Comparing methods for document similarity analysis. TopiCS, DOI 10 (2010)","DOI":"10.1111\/j.1756-8765.2010.01108.x"},{"key":"61_CR33","unstructured":"Tao, J., Cuturi, M., Yamamoto, A.: A distance between text documents based on topic models and ground metric learning. In: The 26th Annual Conference of the Japanese Society for Artificial Intelligence (2012)"},{"key":"61_CR34","unstructured":"Van Rijsbergen, C.J.: Information retrieval (1979)"},{"issue":"Feb","key":"61_CR35","first-page":"207","volume":"10","author":"KQ Weinberger","year":"2009","unstructured":"Weinberger, K.Q., Saul, L.K.: Distance metric learning for large margin nearest neighbor classification. J. Mach. Learn. Res. 10(Feb), 207\u2013244 (2009)","journal-title":"J. Mach. Learn. Res."},{"key":"61_CR36","doi-asserted-by":"crossref","unstructured":"Witt, N., Seifert, C., Granitzer, M.: Explaining topical distances using word embeddings. In: Database and Expert Systems Applications (DEXA), 2016 27th International Workshop on. pp. 212\u2013217. IEEE (2016)","DOI":"10.1109\/DEXA.2016.052"},{"key":"61_CR37","unstructured":"Yang, L., Jin, R.: Distance metric learning: a comprehensive survey, vol. 2, no. 2. Michigan State University (2006)"},{"key":"61_CR38","doi-asserted-by":"crossref","unstructured":"Zhang, M., Liu, Y., Luan, H.B., Sun, M., Izuha, T., Hao, J.: Building earth mover\u2019s distance on bilingual word embeddings for machine translation. In: AAAI, pp. 2870\u20132876 (2016)","DOI":"10.1609\/aaai.v30i1.10351"}],"container-title":["Lecture Notes in Computer Science","Artificial Neural Networks and Machine Learning \u2013 ICANN 2020"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-61616-8_61","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,23]],"date-time":"2022-11-23T18:30:16Z","timestamp":1669228216000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-61616-8_61"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030616151","9783030616168"],"references-count":38,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-61616-8_61","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"14 October 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICANN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Neural Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bratislava","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Slovakia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 September 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 September 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icann2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/e-nns.org\/icann2020\/","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":"OCS","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"249","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":"139","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":"56% - 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":"2.5","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":"*The conference was postponed to 2021 due to the COVID-19 pandemic.","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)"}}]}}