{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T19:45:13Z","timestamp":1743104713167,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030594121"},{"type":"electronic","value":"9783030594138"}],"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\/978-3-030-59413-8_19","type":"book-chapter","created":{"date-parts":[[2020,9,21]],"date-time":"2020-09-21T16:54:52Z","timestamp":1600707292000},"page":"225-240","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Novel Shilling Attack Detection Method Based on T-Distribution over the Dynamic Time Intervals"],"prefix":"10.1007","author":[{"given":"Wanqiao","family":"Yuan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yingyuan","family":"Xiao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xu","family":"Jiao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenchen","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenguang","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongya","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,9,22]]},"reference":[{"key":"19_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"350","DOI":"10.1007\/978-3-030-18579-4_21","volume-title":"Database Systems for Advanced Applications","author":"J Yuan","year":"2019","unstructured":"Yuan, J., Jin, Y., Liu, W., Wang, X.: Attention-based neural tag recommendation. In: Li, G., Yang, J., Gama, J., Natwichai, J., Tong, Y. (eds.) DASFAA 2019. LNCS, vol. 11447, pp. 350\u2013365. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-18579-4_21"},{"key":"19_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1007\/978-3-319-91455-8_23","volume-title":"Database Systems for Advanced Applications","author":"K Xu","year":"2018","unstructured":"Xu, K., Cai, Y., Min, H., Chen, J.: Top-N trustee recommendation with binary user trust feedback. In: Liu, C., Zou, L., Li, J. (eds.) DASFAA 2018. LNCS, vol. 10829, pp. 269\u2013279. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-91455-8_23"},{"issue":"2","key":"19_CR3","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1007\/s11859-018-1301-6","volume":"23","author":"H Yi","year":"2018","unstructured":"Yi, H., Niu, Z., Zhang, F., Li, X., Wang, Y.: Robust recommendation algorithm based on kernel principal component analysis and fuzzy C-means clustering. Wuhan Univ. J. Nat. Sci. 23(2), 111\u2013119 (2018). https:\/\/doi.org\/10.1007\/s11859-018-1301-6","journal-title":"Wuhan Univ. J. Nat. Sci."},{"key":"19_CR4","doi-asserted-by":"crossref","unstructured":"Kaur, P., Goel, S.: Shilling attack models in recommender system. In: 2016 International Conference on Inventive Computation Technologies. IEEE (2016)","DOI":"10.1109\/INVENTIVE.2016.7824865"},{"issue":"12","key":"19_CR5","doi-asserted-by":"publisher","first-page":"1564","DOI":"10.1109\/TSMC.2015.2416126","volume":"45","author":"H Oh","year":"2015","unstructured":"Oh, H., Kim, S., Park, S., Zhou, M.: Can you trust online ratings? A mutual reinforcement model for trustworthy online rating systems. IEEE Trans. Syst. Man Cybern.: Syst. 45(12), 1564\u20131576 (2015)","journal-title":"IEEE Trans. Syst. Man Cybern.: Syst."},{"key":"19_CR6","doi-asserted-by":"crossref","unstructured":"Cheng, Z., Hurley, N.: Effective diverse and obfuscated attacks on model-based recommender systems. In: RecSys, New York, NY, USA, pp. 141\u2013148 (2009)","DOI":"10.1145\/1639714.1639739"},{"issue":"2017","key":"19_CR7","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1016\/j.physa.2017.04.048","volume":"483","author":"J Yu","year":"2017","unstructured":"Yu, J., Gao, M., Rong, W., Li, W., Xiong, Q., Wen, J.: Hybrid attacks on model-based social recommender systems. Physica A 483(2017), 171\u2013181 (2017)","journal-title":"Physica A"},{"key":"19_CR8","doi-asserted-by":"crossref","unstructured":"Zhang, S., Chakrabarti, A., Ford, J., Makedon, F.: Attack detection in time series for recommender systems. In: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Philadelphia, Pennsylvania, USA, pp. 809\u2013814, August 2006","DOI":"10.1145\/1150402.1150508"},{"key":"19_CR9","first-page":"845","volume":"2014","author":"M Gao","year":"2014","unstructured":"Gao, M., Yuan, Q., Ling, B., Xiong, Q.: Detection of abnormal item based on time intervals for recommender systems. Sci. World J. 2014, 845\u2013897 (2014)","journal-title":"Sci. World J."},{"issue":"8","key":"19_CR10","first-page":"135","volume":"10","author":"M Gao","year":"2015","unstructured":"Gao, M., Tian, R., Wen, J., Xiong, Q., Ling, B., Yang, L.: Item anomaly detection based on dynamic partition for time series in recommender systems. PLoS ONE 10(8), 135\u2013155 (2015)","journal-title":"PLoS ONE"},{"key":"19_CR11","doi-asserted-by":"crossref","unstructured":"Chirita, P., Nejdl, W., Zamfir, C.: Preventing shilling attacks in online recommender systems. In: Seventh ACM International Workshop on Web Information and Data Management, Bremen, Germany, pp. 67\u201374 (2005)","DOI":"10.1145\/1097047.1097061"},{"key":"19_CR12","doi-asserted-by":"crossref","unstructured":"Burke, R., Mobasher, B., Williams, C., Bhaumik, R.: Classification features for attack detection in collaborative recommender systems. In: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Philadelphia, Pennsylvania, USA, pp. 542\u2013547 (2006)","DOI":"10.1145\/1150402.1150465"},{"issue":"3","key":"19_CR13","doi-asserted-by":"publisher","first-page":"53","DOI":"10.4018\/IJWSR.2017070104","volume":"14","author":"M Gao","year":"2017","unstructured":"Gao, M., Li, X., Rong, W., Wen, J., Xiong, Q.: The performance of location aware shilling attacks in web service recommendation. Int. J. Web Serv. Res. 14(3), 53\u201366 (2017)","journal-title":"Int. J. Web Serv. Res."},{"issue":"4","key":"19_CR14","doi-asserted-by":"publisher","first-page":"458","DOI":"10.1007\/s11518-018-5374-8","volume":"27","author":"Y Wang","year":"2018","unstructured":"Wang, Y., Qian, L., Li, F., Zhang, L.: A comparative study on Shilling detection methods for trustworthy recommendations. J. Syst. Sci. Syst. Eng. 27(4), 458\u2013478 (2018). https:\/\/doi.org\/10.1007\/s11518-018-5374-8","journal-title":"J. Syst. Sci. Syst. Eng."},{"key":"19_CR15","doi-asserted-by":"crossref","unstructured":"Li, W., Gao, M., Li, H., Zeng, J., Xiong, Q.: Shilling attack detection in recommender systems via selecting patterns analysis. IEICE Trans. Inf. Syst. E99.D(10), 2600\u20132611 (2016)","DOI":"10.1587\/transinf.2015EDP7500"},{"key":"19_CR16","unstructured":"Fan, Y., Gao, M., Yu, J., Song, Y., Wang, X.: Detection of Shilling attack based on bayesian model and user embedding. In: International Conference on Tools with Artificial Intelligence, pp. 639\u2013646. IEEE (2018)"},{"issue":"2016","key":"19_CR17","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1016\/j.knosys.2016.08.011","volume":"111","author":"Z Yang","year":"2016","unstructured":"Yang, Z., Cai, Z., Guan, X.: Estimating user behavior toward detecting anomalous ratings in rating systems. Knowl.-Based Syst. 111(2016), 144\u2013158 (2016)","journal-title":"Knowl.-Based Syst."},{"issue":"2018","key":"19_CR18","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1016\/j.knosys.2018.02.032","volume":"148","author":"F Zhang","year":"2018","unstructured":"Zhang, F., Zhang, Z., Zhang, P., Wang, S.: UD-HMM: an unsupervised method for shilling attack detection based on hidden Markov model and hierarchical clustering. Knowl.-Based Syst. 148(2018), 146\u2013166 (2018)","journal-title":"Knowl.-Based Syst."},{"key":"19_CR19","doi-asserted-by":"crossref","unstructured":"Wu, Z., Wu, J., Cao, J., Tao, D.: Hysad: a semi-supervised hybrid shilling attack detector for trustworthy product recommendation. In: Proceedings of the 18th International Conference on Knowledge Discovery and Data Mining, Beijing, China, pp. 985\u2013993 (2012)","DOI":"10.1145\/2339530.2339684"},{"issue":"2018","key":"19_CR20","doi-asserted-by":"publisher","first-page":"2559","DOI":"10.1109\/ACCESS.2017.2784370","volume":"6","author":"L Zhang","year":"2018","unstructured":"Zhang, L., Wu, Z., Cao, J.: Detecting spammer groups from product reviews: a partially supervised learning model. IEEE Access 6(2018), 2559\u20132567 (2018)","journal-title":"IEEE Access"},{"issue":"4","key":"19_CR21","first-page":"319","volume":"4","author":"X Shen","year":"2015","unstructured":"Shen, X., Wu, R.: Discussion on t-distribution and its application. Stat. Appl. 4(4), 319\u2013334 (2015)","journal-title":"Stat. Appl."}],"container-title":["Lecture Notes in Computer Science","Database Systems for Advanced Applications. DASFAA 2020 International Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-59413-8_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T13:27:01Z","timestamp":1710250021000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-59413-8_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030594121","9783030594138"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-59413-8_19","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":"22 September 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DASFAA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Database Systems for Advanced Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Jeju","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Korea (Republic of)","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":"24 September 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 September 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dasfaa2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/db.pknu.ac.kr\/dasfaa2020\/","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":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"487","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":"119","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":"23","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":"24% - 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":"3.11","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":"6.81","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":"15 demo papers and 4 industrial papers","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)"}}]}}