{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T09:24:41Z","timestamp":1763457881586,"version":"3.40.3"},"publisher-location":"Cham","reference-count":37,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030337018"},{"type":"electronic","value":"9783030337025"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[[2019]]},"DOI":"10.1007\/978-3-030-33702-5_14","type":"book-chapter","created":{"date-parts":[[2019,10,25]],"date-time":"2019-10-25T21:01:49Z","timestamp":1572037309000},"page":"186-201","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Leveraging AI in Service Automation Modeling: From Classical AI Through Deep Learning to Combination Models"],"prefix":"10.1007","author":[{"given":"Qing","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5878-0765","authenticated-orcid":false,"given":"Larisa","family":"Shwartz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8068-0920","authenticated-orcid":false,"given":"Genady Ya.","family":"Grabarnik","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7379-2852","authenticated-orcid":false,"given":"Michael","family":"Nidd","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8595-7431","authenticated-orcid":false,"given":"Jinho","family":"Hwang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,10,22]]},"reference":[{"key":"14_CR1","first-page":"1289","volume":"3","author":"G Forman","year":"2003","unstructured":"Forman, G.: An extensive empirical study of feature selection metrics for text classification. J. Mach. Learn. Res. 3, 1289\u20131305 (2003)","journal-title":"J. Mach. Learn. Res."},{"key":"14_CR2","doi-asserted-by":"crossref","unstructured":"Joulin, A., Grave, E., Bojanowski, P., Mikolov, T.: Bag of tricks for efficient text classification, arXiv preprint arXiv:1607.01759 (2016)","DOI":"10.18653\/v1\/E17-2068"},{"issue":"2","key":"14_CR3","first-page":"40","volume":"2","author":"DW Ruck","year":"1990","unstructured":"Ruck, D.W., Rogers, S.K., Kabrisky, M.: Feature selection using a multilayer perceptron. J. Neural Network Comput. 2(2), 40\u201348 (1990)","journal-title":"J. Neural Network Comput."},{"key":"14_CR4","doi-asserted-by":"crossref","unstructured":"Kim, Y.: Convolutional neural networks for sentence classification, arXiv preprint arXiv:1408.5882 (2014)","DOI":"10.3115\/v1\/D14-1181"},{"key":"14_CR5","unstructured":"Zhang, X., LeCun, Y.: Text understanding from scratch, arXiv preprint arXiv:1502.01710 (2015)"},{"key":"14_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"425","DOI":"10.1007\/978-3-030-17642-6_37","volume-title":"Service-Oriented Computing \u2013 ICSOC 2018 Workshops","author":"L Shwartz","year":"2019","unstructured":"Shwartz, L., et al.: CEA: a service for cognitive event automation. In: Liu, X., et al. (eds.) ICSOC 2018. LNCS, vol. 11434, pp. 425\u2013429. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-17642-6_37"},{"key":"14_CR7","doi-asserted-by":"crossref","unstructured":"Zeng, C., Li, T., Shwartz, L., Grabarnik, G.Y.: Hierarchical multi-label classification over ticket data using contextual loss. In: 2014 IEEE NOMS (2014)","DOI":"10.1109\/NOMS.2014.6838267"},{"key":"14_CR8","doi-asserted-by":"publisher","first-page":"657","DOI":"10.1137\/1.9781611975321.74","volume-title":"Proceedings of the 2018 SIAM International Conference on Data Mining","author":"Qing Wang","year":"2018","unstructured":"Wang, Q., Li, T., Iyengar, S., Shwartz, L., Grabarnik, G.Y.: Online IT ticket automation recommendation using hierarchical multi-armed bandit algorithms. In: Proceedings of the 2018 SIAM International Conference on Data Mining, SIAM, pp. 657\u2013665 (2018)"},{"key":"14_CR9","doi-asserted-by":"publisher","first-page":"1569","DOI":"10.1109\/TKDE.2018.2866041","volume":"31","author":"Q Wang","year":"2018","unstructured":"Wang, Q., Zeng, C., Zhou, W., Li, T., Iyengar, S.S., Shwartz, L., Grabarnik, G.: Online interactive collaborative filtering using multi-armed bandit with dependent arms. IEEE Trans. Knowl. Data Eng. 31, 1569\u20131580 (2018)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"14_CR10","doi-asserted-by":"crossref","unstructured":"Zeng, C., Wang, Q., Wang, W., Li, T., Shwartz, L.: Online inference for time-varying temporal dependency discovery from time series. In: 2016 IEEE International Conference on Big Data (Big Data), pp. 1281\u20131290. IEEE (2016)","DOI":"10.1109\/BigData.2016.7840732"},{"key":"14_CR11","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-84628-754-1","volume-title":"Natural Language Processing and Text Mining","author":"A Kao","year":"2007","unstructured":"Kao, A., Poteet, S.R.: Natural Language Processing and Text Mining. Springer, London (2007). https:\/\/doi.org\/10.1007\/978-1-84628-754-1"},{"key":"14_CR12","unstructured":"Bottou, L., et al.: Comparison of classifier methods: a case study in handwritten digit recognition. In: International Conference on Pattern Recognition, p. 77. IEEE Computer Society Press (1994)"},{"key":"14_CR13","doi-asserted-by":"publisher","first-page":"415","DOI":"10.1109\/TNN.2002.1000139","volume":"13","author":"C-W Hsu","year":"2002","unstructured":"Hsu, C.-W., Lin, C.-J.: A comparison of methods for multiclass support vector machines. IEEE Trans. Neural Networks 13, 415\u2013425 (2002)","journal-title":"IEEE Trans. Neural Networks"},{"issue":"4","key":"14_CR14","first-page":"97","volume":"18","author":"TG Dietterich","year":"1997","unstructured":"Dietterich, T.G.: Machine-learning research. AI Mag. 18(4), 97\u201397 (1997)","journal-title":"AI Mag."},{"issue":"1","key":"14_CR15","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45(1), 5\u201332 (2001)","journal-title":"Mach. Learn."},{"issue":"3","key":"14_CR16","first-page":"18","volume":"2","author":"A Liaw","year":"2002","unstructured":"Liaw, A., Wiener, M., et al.: Classification and regression by randomforest. R News 2(3), 18\u201322 (2002)","journal-title":"R News"},{"key":"14_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1007\/978-3-540-74469-6_35","volume-title":"Database and Expert Systems Applications","author":"A Prinzie","year":"2007","unstructured":"Prinzie, A., Van den Poel, D.: Random multiclass classification: generalizing random forests to random MNL and random NB. In: Wagner, R., Revell, N., Pernul, G. (eds.) DEXA 2007. LNCS, vol. 4653, pp. 349\u2013358. Springer, Heidelberg (2007). https:\/\/doi.org\/10.1007\/978-3-540-74469-6_35"},{"key":"14_CR18","doi-asserted-by":"crossref","unstructured":"Santner, J., Unger, M., Pock, T., Leistner, C., Saffari, A., Bischof, A.: Interactive texture segmentation using random forests and total variation. In: BMVC, pp. 1\u201312. Citeseer (2009)","DOI":"10.5244\/C.23.66"},{"key":"14_CR19","doi-asserted-by":"crossref","unstructured":"Chen, T., Guestrin, T.: XGBoost: a scalable tree boosting system. In: Proceedings of the 22nd ACM SIGKDD, pp. 785\u2013794 (2016)","DOI":"10.1145\/2939672.2939785"},{"key":"14_CR20","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1007\/978-3-319-71928-3_34","volume-title":"Mining Intelligence and Knowledge Exploration","author":"S Madisetty","year":"2017","unstructured":"Madisetty, S., Desarkar, M.S.: An ensemble based method for predicting emotion intensity of tweets. In: Ghosh, A., Pal, R., Prasath, R. (eds.) MIKE 2017. LNCS (LNAI), vol. 10682, pp. 359\u2013370. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-71928-3_34"},{"key":"14_CR21","doi-asserted-by":"crossref","unstructured":"Sharif Razavian, A., Azizpour, H., Sullivan, J., Carlsson, S.: CNN features off-the-shelf: an astounding baseline for recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 806\u2013813 (2014)","DOI":"10.1109\/CVPRW.2014.131"},{"issue":"7553","key":"14_CR22","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436 (2015)","journal-title":"Nature"},{"key":"14_CR23","doi-asserted-by":"crossref","unstructured":"Narasimhan, H., Pan, W., Kar, P., Protopapas, P., Ramaswamy, H.G.: Optimizing the multiclass f-measure via biconcave programming. In: 2016 IEEE 16th International Conference on Data Mining (ICDM), pp. 1101\u20131106. IEEE (2016)","DOI":"10.1109\/ICDM.2016.0143"},{"key":"14_CR24","doi-asserted-by":"crossref","unstructured":"Boser, B.E., Guyon, I.M., Vapnik, V.N.: A training algorithm for optimal margin classifiers. In: Proceedings of the Fifth Annual Workshop on Computational Learning Theory, pp. 144\u2013152. ACM (1992)","DOI":"10.1145\/130385.130401"},{"issue":"1","key":"14_CR25","first-page":"81","volume":"1","author":"JR Quinlan","year":"1986","unstructured":"Quinlan, J.R.: Induction of decision trees. Mach. Learn. 1(1), 81\u2013106 (1986)","journal-title":"Mach. Learn."},{"issue":"1","key":"14_CR26","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1109\/TIT.1967.1053964","volume":"13","author":"TM Cover","year":"1967","unstructured":"Cover, T.M., Hart, P.E., et al.: Nearest neighbor pattern classification. IEEE Trans. Inf. Theor. 13(1), 21\u201327 (1967)","journal-title":"IEEE Trans. Inf. Theor."},{"issue":"1","key":"14_CR27","first-page":"100","volume":"28","author":"JA Hartigan","year":"1979","unstructured":"Hartigan, J.A., Wong, M.A.: Algorithm as 136: a k-means clustering algorithm. J. Roy. Stat. Soc. Ser. C (Appl. Stat.) 28(1), 100\u2013108 (1979)","journal-title":"J. Roy. Stat. Soc. Ser. C (Appl. Stat.)"},{"key":"14_CR28","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"378","DOI":"10.1007\/978-3-319-64185-0_28","volume-title":"Digital Forensics and Watermarking","author":"X Ren","year":"2017","unstructured":"Ren, X., Guo, H., Li, S., Wang, S., Li, J.: A novel image classification method with CNN-XGBoost model. In: Kraetzer, C., Shi, Y.-Q., Dittmann, J., Kim, H.J. (eds.) IWDW 2017. LNCS, vol. 10431, pp. 378\u2013390. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-64185-0_28"},{"key":"14_CR29","unstructured":"Wang, Q.: Intelligent data mining techniques for automatic service management. In: FIU Electronic Theses and Dissertations. FIU (2018). https:\/\/digitalcommons.fiu.edu\/etd\/3883"},{"key":"14_CR30","doi-asserted-by":"crossref","unstructured":"Wang, Q., Zhou, W., Zeng, C., Li, T., Shwartz, L., Grabarnik, G.Y.: Constructing the knowledge base for cognitive it service management. In: 2017 IEEE International Conference on Services Computing (SCC), pp. 410\u2013417. IEEE (2017)","DOI":"10.1109\/SCC.2017.59"},{"key":"14_CR31","doi-asserted-by":"crossref","unstructured":"Zhou, W., et al.: Star: a system for ticket analysis and resolution. In: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 2181\u20132190. ACM (2017)","DOI":"10.1145\/3097983.3098190"},{"key":"14_CR32","doi-asserted-by":"crossref","unstructured":"Wang, Q., Zeng, C., Iyengar, S., Li, T., Shwartz, L., Grabarnik, G.Y.: AISTAR: an intelligent system for online IT ticket automation recommendation. In: 2018 IEEE International Conference on Big Data (Big Data), pp. 1875\u20131884. IEEE (2018)","DOI":"10.1109\/BigData.2018.8622446"},{"key":"14_CR33","doi-asserted-by":"crossref","unstructured":"Zeng, C., Wang, C., Mokhtari, S., Li, T.: Online context-aware recommendation with time varying multi-armed bandit. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 2025\u20132034. ACM (2016)","DOI":"10.1145\/2939672.2939878"},{"key":"14_CR34","doi-asserted-by":"crossref","unstructured":"Yang, Z., Yang, D., Dyer, C., He, X., Smola, A., Hovy, E.: Hierarchical attention networks for document classification. In: Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 1480\u20131489 (2016)","DOI":"10.18653\/v1\/N16-1174"},{"issue":"1\u20134","key":"14_CR35","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1007\/s13042-010-0001-0","volume":"1","author":"Y Zhang","year":"2010","unstructured":"Zhang, Y., Jin, R., Zhou, Z.-H.: Understanding bag-of-words model: a statistical framework. Int. J. Mach. Learn. Cybern. 1(1\u20134), 43\u201352 (2010)","journal-title":"Int. J. Mach. Learn. Cybern."},{"issue":"4","key":"14_CR36","first-page":"467","volume":"18","author":"PF Brown","year":"1992","unstructured":"Brown, P.F., Desouza, P.V., Mercer, R.L., Pietra, V.J.D., Lai, J.C.: Class-based n-gram models of natural language. Comput. Linguist. 18(4), 467\u2013479 (1992)","journal-title":"Comput. Linguist."},{"issue":"8","key":"14_CR37","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735\u20131780 (1997)","journal-title":"Neural Comput."}],"container-title":["Lecture Notes in Computer Science","Service-Oriented Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-33702-5_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,24]],"date-time":"2024-10-24T23:06:03Z","timestamp":1729811163000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-33702-5_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030337018","9783030337025"],"references-count":37,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-33702-5_14","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"22 October 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICSOC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Service-Oriented Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Toulouse","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"France","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 October 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31 October 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icsoc2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icsoc-laas.fr\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}