{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T21:08:34Z","timestamp":1743109714285,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030590505"},{"type":"electronic","value":"9783030590512"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/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":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-59051-2_10","type":"book-chapter","created":{"date-parts":[[2020,9,12]],"date-time":"2020-09-12T19:02:51Z","timestamp":1599937371000},"page":"149-163","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Model-Agnostic Recommendation Explanation System Based on Knowledge Graph"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1706-0125","authenticated-orcid":false,"given":"Yuhao","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3038-7678","authenticated-orcid":false,"given":"Jun","family":"Miyazaki","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,2,8]]},"reference":[{"issue":"6","key":"10_CR1","doi-asserted-by":"publisher","first-page":"734","DOI":"10.1109\/TKDE.2005.99","volume":"17","author":"G Adomavicius","year":"2005","unstructured":"Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Trans. Knowl. Data Eng. 17(6), 734\u2013749 (2005). https:\/\/doi.org\/10.1109\/TKDE.2005.99","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"10_CR2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-29659-3","volume-title":"Recommender Systems","author":"CC Aggarwal","year":"2016","unstructured":"Aggarwal, C.C.: Recommender Systems. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-29659-3"},{"doi-asserted-by":"crossref","unstructured":"Ai, Q., Azizi, V., Chen, X., Zhang, Y.: Learning heterogeneous knowledge base embeddings for explainable recommendation. ArXiv arXiv:1805.03352 (2018)","key":"10_CR3","DOI":"10.3390\/a11090137"},{"doi-asserted-by":"crossref","unstructured":"Balog, K., Radlinski, F., Arakelyan, S.: Transparent, scrutable and explainable user models for personalized recommendation. In: SIGIR 2019, pp. 265\u2013274 (2019)","key":"10_CR4","DOI":"10.1145\/3331184.3331211"},{"unstructured":"Boschin, A., Bonald, T.: WikiDataSets: standardized sub-graphs from WikiData. arXiv:1906.04536 [cs, stat], June 2019. http:\/\/arxiv.org\/abs\/1906.04536","key":"10_CR5"},{"unstructured":"Catherine, R., Mazaitis, K., Esk\u00e9nazi, M., Cohen, W.W.: Explainable entity-based recommendations with knowledge graphs. ArXiv arXiv:1707.05254 (2017)","key":"10_CR6"},{"unstructured":"Cheng, H.T., et al.: Wide & deep learning for recommender systems. In: Proceedings of the 1st Workshop on Deep Learning for Recommender Systems DLRS 2016, pp. 7\u201310. Association for Computing Machinery, New York (2016)","key":"10_CR7"},{"unstructured":"Gong, Y., Zhang, Q.: Hashtag recommendation using attention-based convolutional neural network. In: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence IJCAI 2016, pp. 2782\u20132788. AAAI Press (2016)","key":"10_CR8"},{"doi-asserted-by":"crossref","unstructured":"He, X., Liao, L., Zhang, H., Nie, L., Hu, X., Chua, T.S.: Neural collaborative filtering. In: Proceedings of the 26th International Conference on World Wide Web WWW 2017, pp. 173\u2013182. International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, CHE (2017)","key":"10_CR9","DOI":"10.1145\/3038912.3052569"},{"doi-asserted-by":"crossref","unstructured":"Ma, W., et al.: Jointly learning explainable rules for recommendation with knowledge graph. In: WWW 2019, pp. 1210\u20131221 (2019)","key":"10_CR10","DOI":"10.1145\/3308558.3313607"},{"doi-asserted-by":"crossref","unstructured":"Peake, G., Wang, J.: Explanation mining: post hoc interpretability of latent factor models for recommendation systems. In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining KDD 2018, pp. 2060\u20132069. Association for Computing Machinery, New York (2018)","key":"10_CR11","DOI":"10.1145\/3219819.3220072"},{"unstructured":"Singh, J., Anand, A.: Posthoc interpretability of learning to rank models using secondary training data. ArXiv arXiv:1806.11330 (2018)","key":"10_CR12"},{"key":"10_CR13","doi-asserted-by":"publisher","first-page":"479","DOI":"10.1007\/978-0-387-85820-3_15","volume-title":"Recommender Systems Handbook","author":"N Tintarev","year":"2011","unstructured":"Tintarev, N., Masthoff, J.: Designing and evaluating explanations for recommender systems. In: Ricci, F., Rokach, L., Shapira, B., Kantor, P.B. (eds.) Recommender Systems Handbook, pp. 479\u2013510. Springer, Boston, MA (2011). https:\/\/doi.org\/10.1007\/978-0-387-85820-3_15"},{"doi-asserted-by":"crossref","unstructured":"Wang, H., et al.: RippleNet: propagating user preferences on the knowledge graph for recommender systems. In: Proceedings of the 27th ACM International Conference on Information and Knowledge Management CIKM 2018, pp. 417\u2013426. Association for Computing Machinery, New York (2018)","key":"10_CR14","DOI":"10.1145\/3269206.3271739"},{"doi-asserted-by":"crossref","unstructured":"Wang, J., de Vries, A.P., Reinders, M.J.T.: Unifying user-based and item-based collaborative filtering approaches by similarity fusion. In: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval SIGIR 2006, pp. 501\u2013508. Association for Computing Machinery, New York, NY (2006)","key":"10_CR15","DOI":"10.1145\/1148170.1148257"},{"key":"10_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"102","DOI":"10.1007\/978-3-319-93803-5_10","volume-title":"Data Mining and Big Data","author":"S Wang","year":"2018","unstructured":"Wang, S., Tian, H., Zhu, X., Wu, Z.: Explainable matrix factorization with constraints on neighborhood in the latent space. In: Tan, Y., Shi, Y., Tang, Q. (eds.) DMBD 2018. LNCS, vol. 10943, pp. 102\u2013113. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-93803-5_10"},{"doi-asserted-by":"publisher","unstructured":"Wang, X., Chen, Y., Yang, J., Wu, L., Wu, Z., Xie, X.: A reinforcement learning framework for explainable recommendation. In: 2018 IEEE International Conference on Data Mining (ICDM), pp. 587\u2013596, November 2018. https:\/\/doi.org\/10.1109\/ICDM.2018.00074","key":"10_CR17","DOI":"10.1109\/ICDM.2018.00074"},{"unstructured":"Zhang, Y., Chen, X.: Explainable recommendation: a survey and new perspectives. ArXiv arXiv:1804.11192 (2018)","key":"10_CR18"},{"issue":"2","key":"10_CR19","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1162\/dint_a_00008","volume":"1","author":"WX Zhao","year":"2019","unstructured":"Zhao, W.X., et al.: Kb4rec: a data set for linking knowledge bases with recommender systems. Data Intell. 1(2), 121\u2013136 (2019)","journal-title":"Data Intell."}],"container-title":["Lecture Notes in Computer Science","Database and Expert Systems Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-59051-2_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T11:38:12Z","timestamp":1709811492000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-59051-2_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030590505","9783030590512"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-59051-2_10","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":"8 February 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DEXA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Database and Expert Systems Applications","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":"14 September 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 September 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dexa2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.dexa.org\/dexa2020","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":"190","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":"38","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":"20","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":"20% - 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":"4-6","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":"3-4","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":"Due to the COVID-19 pandemic the conference was held online. DEXA Workshops volume: submissions sent - 15, full papers accepted - 6, short papers accepted - 4, reviewers per paper 3, papers per reviewer 1-2","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)"}}]}}