{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T00:49:22Z","timestamp":1743036562052,"version":"3.40.3"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030161477"},{"type":"electronic","value":"9783030161484"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","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":[[2019]]},"DOI":"10.1007\/978-3-030-16148-4_45","type":"book-chapter","created":{"date-parts":[[2019,4,4]],"date-time":"2019-04-04T02:50:37Z","timestamp":1554346237000},"page":"587-599","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["NeoLOD: A Novel Generalized Coupled Local Outlier Detection Model Embedded Non-IID Similarity Metric"],"prefix":"10.1007","author":[{"given":"Fan","family":"Meng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Huo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaolong","family":"Qi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shichao","family":"Yi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,3,22]]},"reference":[{"key":"45_CR1","doi-asserted-by":"crossref","unstructured":"Breunig, M.M., Kriegel, H.-P., Ng, R.T., Sander, J.: LOF: identifying density-based local outliers. In: Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data, pp. 1\u201312 (2000)","DOI":"10.1145\/342009.335388"},{"issue":"2","key":"45_CR2","doi-asserted-by":"publisher","first-page":"371","DOI":"10.1007\/s10618-016-0471-0","volume":"31","author":"M Ernst","year":"2017","unstructured":"Ernst, M., Haesbroeck, G.: Comparison of local outlier detection techniques in spatial multivariate data. Data Min. Knowl. Discov. 31(2), 371\u2013399 (2017)","journal-title":"Data Min. Knowl. Discov."},{"key":"45_CR3","doi-asserted-by":"crossref","unstructured":"Kriegel, H.-P., Kr\u00f6ger, P., Schubert, E., Zimek, A.: LoOP: local outlier probabilities. In: Proceedings of the 18th ACM Conference on Information and Knowledge Management, pp. 1649\u20131652. ACM (2009)","DOI":"10.1145\/1645953.1646195"},{"key":"45_CR4","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"813","DOI":"10.1007\/978-3-642-01307-2_84","volume-title":"Advances in Knowledge Discovery and Data Mining","author":"K Zhang","year":"2009","unstructured":"Zhang, K., Hutter, M., Jin, H.: A new local distance-based outlier detection approach for scattered real-world data. In: Theeramunkong, T., Kijsirikul, B., Cercone, N., Ho, T.-B. (eds.) PAKDD 2009. LNCS (LNAI), vol. 5476, pp. 813\u2013822. Springer, Heidelberg (2009). https:\/\/doi.org\/10.1007\/978-3-642-01307-2_84"},{"issue":"1","key":"45_CR5","doi-asserted-by":"publisher","first-page":"190","DOI":"10.1007\/s10618-012-0300-z","volume":"28","author":"E Schubert","year":"2014","unstructured":"Schubert, E., Zimek, A., Kriegel, H.-P.: Local outlier detection reconsidered: a generalized view on locality with applications to spatial, video, and network outlier detection. Data Min. Knowl. Discov. 28(1), 190\u2013237 (2014)","journal-title":"Data Min. Knowl. Discov."},{"issue":"5","key":"45_CR6","doi-asserted-by":"publisher","first-page":"631","DOI":"10.1109\/TKDE.2007.1009","volume":"19","author":"X Song","year":"2007","unstructured":"Song, X., Wu, M., Jermaine, C., Ranka, S.: Conditional anomaly detection. IEEE Trans. Knowl. Data Eng. 19(5), 631\u2013645 (2007)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"45_CR7","doi-asserted-by":"crossref","unstructured":"Wang, X., Davidson, I.: Discovering contexts and contextual outliers using random walks in graphs. In: 2009 Ninth IEEE International Conference on Data Mining, ICDM 2009, pp. 1034\u20131039. IEEE (2009)","DOI":"10.1109\/ICDM.2009.95"},{"key":"45_CR8","doi-asserted-by":"crossref","unstructured":"Zheng, G., Brantley, S.L., Lauvaux, T., Li, Z.: Contextual spatial outlier detection with metric learning. In: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 2161\u20132170. ACM (2017)","DOI":"10.1145\/3097983.3098143"},{"key":"45_CR9","doi-asserted-by":"publisher","first-page":"1810","DOI":"10.1109\/TKDE.2018.2808532","volume":"30","author":"S Jian","year":"2018","unstructured":"Jian, S., Cao, L., Lu, K., Gao, H.: Unsupervised coupled metric similarity for non-IID categorical data. IEEE Trans. Knowl. Data Eng. 30, 1810\u20131823 (2018)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"45_CR10","doi-asserted-by":"publisher","first-page":"1254","DOI":"10.1109\/TKDE.2018.2791525","volume":"30","author":"C Zhu","year":"2018","unstructured":"Zhu, C., Cao, L., Liu, Q., Yin, J., Kumar, V.: Heterogeneous metric learning of categorical data with hierarchical couplings. IEEE Trans. Knowl. Data Eng. 30, 1254\u20131267 (2018)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"45_CR11","unstructured":"Chen, L., Liu, H., Pang, G., Cao, L.: Learning homophily couplings from non-IID data for joint feature selection and noise-resilient outlier detection. In: Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI-2017, pp. 2585\u20132591 (2017)"},{"key":"45_CR12","doi-asserted-by":"crossref","unstructured":"Pang, G., Cao, L., Chen, L., Liu, H.: Learning homophily couplings from non-IID data for joint feature selection and noise-resilient outlier detection. In: Proceedings of the 26th International Joint Conference on Artificial Intelligence, pp. 2585\u20132591. AAAI Press (2017)","DOI":"10.24963\/ijcai.2017\/360"},{"issue":"1","key":"45_CR13","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1007\/s10994-006-6889-7","volume":"65","author":"I Tsamardinos","year":"2006","unstructured":"Tsamardinos, I., Brown, L.E., Aliferis, C.F.: The max-min hill-climbing Bayesian network structure learning algorithm. Mach. Learn. 65(1), 31\u201378 (2006)","journal-title":"Mach. Learn."},{"issue":"4","key":"45_CR14","doi-asserted-by":"publisher","first-page":"781","DOI":"10.1109\/TNNLS.2014.2325872","volume":"26","author":"C Wang","year":"2015","unstructured":"Wang, C., Dong, X., Zhou, F., Cao, L., Chi, C.H.: Coupled attribute similarity learning on categorical data. IEEE Trans. Neural Netw. Learn. Syst. 26(4), 781\u2013797 (2015)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"1","key":"45_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2133360.2133361","volume":"6","author":"D Ienco","year":"2012","unstructured":"Ienco, D., Pensa, R.G., Meo, R.: From context to distance: learning dissimilarity for categorical data clustering. ACM Trans. Knowl. Discov. Data 6(1), 1\u201325 (2012)","journal-title":"ACM Trans. Knowl. Discov. Data"}],"container-title":["Lecture Notes in Computer Science","Advances in Knowledge Discovery and Data Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-16148-4_45","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T12:31:27Z","timestamp":1709814687000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-16148-4_45"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030161477","9783030161484"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-16148-4_45","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 March 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PAKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific-Asia Conference on Knowledge Discovery and Data Mining","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Macau","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":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 April 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 April 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pakdd2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.pakdd2019.org","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Microsoft Conf. Man. Toolkit CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"542","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":"137","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":"25% - 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":"3.79","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":"5.85","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":"In addition, there were 31 PAKDD 2019 Workshops' papers accepted for publication","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)"}}]}}