{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T22:15:16Z","timestamp":1779315316187,"version":"3.51.4"},"publisher-location":"Cham","reference-count":38,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030185756","type":"print"},{"value":"9783030185763","type":"electronic"}],"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\/978-3-030-18576-3_46","type":"book-chapter","created":{"date-parts":[[2019,4,23]],"date-time":"2019-04-23T08:05:29Z","timestamp":1556006729000},"page":"777-794","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Multi-hop Path Queries over Knowledge Graphs with Neural Memory Networks"],"prefix":"10.1007","author":[{"given":"Qinyong","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongzhi","family":"Yin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weiqing","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zi","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guibing","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Quoc Viet Hung","family":"Nguyen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,4,24]]},"reference":[{"key":"46_CR1","doi-asserted-by":"crossref","unstructured":"Achlioptas, D., Iliopoulos, F.: Random walks that find perfect objects and the lov\u00e1sz local lemma. In: FOCS, pp. 494\u2013503. IEEE (2014)","DOI":"10.1109\/FOCS.2014.59"},{"key":"46_CR2","doi-asserted-by":"crossref","unstructured":"Bollacker, K., Evans, C., Paritosh, P., Sturge, T., Taylor, J.: Freebase: a collaboratively created graph database for structuring human knowledge. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 1247\u20131250 (2008)","DOI":"10.1145\/1376616.1376746"},{"key":"46_CR3","unstructured":"Bordes, A., Usunier, N., Garcia-Duran, A., Weston, J., Yakhnenko, O.: Translating embeddings for modeling multi-relational data. In: NIPS, pp. 2787\u20132795 (2013)"},{"key":"46_CR4","doi-asserted-by":"crossref","unstructured":"Chen, H., Yin, H., Wang, W., Wang, H., Nguyen, Q.V.H., Li, X.: PME: projected metric embedding on heterogeneous networks for link prediction. In: SIGKDD, pp. 1177\u20131186 (2018)","DOI":"10.1145\/3219819.3219986"},{"key":"46_CR5","doi-asserted-by":"crossref","unstructured":"Das, R., Neelakantan, A., Belanger, D., McCallum, A.: Chains of reasoning over entities, relations, and text using recurrent neural networks. arXiv preprint arXiv:1607.01426 (2016)","DOI":"10.18653\/v1\/E17-1013"},{"key":"46_CR6","doi-asserted-by":"crossref","unstructured":"Friedman, J., Hastie, T., Tibshirani, R.: The Elements of Statistical Learning, vol. 1 (2001)","DOI":"10.1007\/978-0-387-21606-5_1"},{"issue":"6","key":"46_CR7","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1007\/s00778-015-0394-1","volume":"24","author":"L Gal\u00e1rraga","year":"2015","unstructured":"Gal\u00e1rraga, L., Teflioudi, C., Hose, K., Suchanek, F.M.: Fast rule mining in ontological knowledge bases with AMIE+. VLDB J. Int. J. Very Large Data Bases 24(6), 707\u2013730 (2015)","journal-title":"VLDB J. Int. J. Very Large Data Bases"},{"key":"46_CR8","unstructured":"Graves, A., Wayne, G., Danihelka, I.: Neural turing machines. arXiv (2014)"},{"key":"46_CR9","unstructured":"Grefenstette, E., Hermann, K.M., Suleyman, M., Blunsom, P.: Learning to transduce with unbounded memory. In: NIPS, pp. 1828\u20131836 (2015)"},{"key":"46_CR10","doi-asserted-by":"crossref","unstructured":"Guu, K., Miller, J., Liang, P.: Traversing knowledge graphs in vector space. In: EMNLP, pp. 318\u2013327 (2015)","DOI":"10.18653\/v1\/D15-1038"},{"key":"46_CR11","doi-asserted-by":"crossref","unstructured":"Hsieh, C.K., Yang, L., Cui, Y., Lin, T.Y., Belongie, S., Estrin, D.: Collaborative metric learning. In: WWW, pp. 193\u2013201 (2017)","DOI":"10.1145\/3038912.3052639"},{"issue":"6","key":"46_CR12","doi-asserted-by":"publisher","first-page":"855","DOI":"10.1007\/s00778-017-0484-3","volume":"26","author":"NQ Hung","year":"2017","unstructured":"Hung, N.Q., et al.: Answer validation for generic crowdsourcing tasks with minimal efforts. VLDB J. 26(6), 855\u2013880 (2017)","journal-title":"VLDB J."},{"issue":"1","key":"46_CR13","first-page":"1","volume":"30","author":"NQV Hung","year":"2018","unstructured":"Hung, N.Q.V., Viet, H.H., Tam, N.T., Weidlich, M., Yin, H., Zhou, X.: Computing crowd consensus with partial agreement. TKDE 30(1), 1\u201314 (2018)","journal-title":"TKDE"},{"key":"46_CR14","unstructured":"Jenatton, R., Roux, N.L., Bordes, A., Obozinski, G.R.: A latent factor model for highly multi-relational data. In: NIPS, pp. 3167\u20133175 (2012)"},{"key":"46_CR15","unstructured":"Khot, T., Balasubramanian, N., Gribkoff, E., Sabharwal, A., Clark, P., Etzioni, O.: Markov logic networks for natural language question answering. arXiv (2015)"},{"key":"46_CR16","doi-asserted-by":"crossref","unstructured":"Kok, S., Domingos, P.: Statistical predicate invention. In: Proceedings of the 24th International Conference on Machine Learning, pp. 433\u2013440 (2007)","DOI":"10.1145\/1273496.1273551"},{"issue":"1","key":"46_CR17","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1007\/s10994-010-5205-8","volume":"81","author":"N Lao","year":"2010","unstructured":"Lao, N., Cohen, W.W.: Relational retrieval using a combination of path-constrained random walks. Mach. Learn. 81(1), 53\u201367 (2010)","journal-title":"Mach. Learn."},{"key":"46_CR18","unstructured":"Lao, N., Mitchell, T., Cohen, W.W.: Random walk inference and learning in a large scale knowledge base. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 529\u2013539. Association for Computational Linguistics (2011)"},{"key":"46_CR19","doi-asserted-by":"crossref","unstructured":"Lin, Y., Liu, Z., Sun, M., Liu, Y., Zhu, X.: Learning entity and relation embeddings for knowledge graph completion. In: AAAI, vol. 15, pp. 2181\u20132187 (2015)","DOI":"10.1609\/aaai.v29i1.9491"},{"key":"46_CR20","unstructured":"Mahdisoltani, F., Biega, J., Suchanek, F.M.: Yago3: a knowledge base from multilingual wikipedias. In: CIDR (2013)"},{"key":"46_CR21","doi-asserted-by":"crossref","unstructured":"Miller, A., Fisch, A., Dodge, J., Karimi, A.H., Bordes, A., Weston, J.: Key-value memory networks for directly reading documents. arXiv (2016)","DOI":"10.18653\/v1\/D16-1147"},{"key":"46_CR22","unstructured":"Min, B., Grishman, R., Wan, L., Wang, C., Gondek, D.: Distant supervision for relation extraction with an incomplete knowledge base. In: PHLT-NAACL, pp. 777\u2013782 (2013)"},{"key":"46_CR23","unstructured":"Minsky, M.: The Society of Mind (1986)"},{"issue":"4","key":"46_CR24","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1007\/BF03037089","volume":"8","author":"S Muggleton","year":"1991","unstructured":"Muggleton, S.: Inductive logic programming. New Gener. Comput. 8(4), 295\u2013318 (1991)","journal-title":"New Gener. Comput."},{"key":"46_CR25","doi-asserted-by":"crossref","unstructured":"Neelakantan, A., Roth, B., Mc-Callum, A.: Compositional vector space models for knowledge base inference. In: 2015 AAAI Spring Symposium Series (2015)","DOI":"10.3115\/v1\/P15-1016"},{"key":"46_CR26","unstructured":"Nguyen, T.T., Duong, C.T., Weidlich, M., Yin, H., Nguyen, Q.V.H.: Retaining data from streams of social platforms with minimal regret. In: Twenty-Sixth International Joint Conference on Artificial Intelligence. No. EPFL-CONF-227978 (2017)"},{"key":"46_CR27","unstructured":"Nickel, M., Tresp, V., Kriegel, H.P.: A three-way model for collective learning on multi-relational data. In: ICML, vol. 11, pp. 809\u2013816 (2011)"},{"issue":"6","key":"46_CR28","first-page":"373","volume":"4","author":"F Niu","year":"2011","unstructured":"Niu, F., R\u00e9, C., Doan, A., Shavlik, J.: Tuffy: scaling up statistical inference in markov logic networks using an rdbms. VLDB 4(6), 373\u2013384 (2011)","journal-title":"VLDB"},{"key":"46_CR29","unstructured":"Poole, D.: First-order probabilistic inference. In: IJCAI, vol. 3, pp. 985\u2013991 (2003)"},{"key":"46_CR30","unstructured":"Sukhbaatar, S., Weston, J., Fergus, R., et al.: End-to-end memory networks. In: NIPS, pp. 2440\u20132448 (2015)"},{"key":"46_CR31","doi-asserted-by":"crossref","unstructured":"Toutanova, K., Chen, D.: Observed versus latent features for knowledge base and text inference. In: Proceedings of the 3rd Workshop on Continuous Vector Space Models and their Compositionality, pp. 57\u201366 (2015)","DOI":"10.18653\/v1\/W15-4007"},{"key":"46_CR32","doi-asserted-by":"crossref","unstructured":"Wang, Q., Yin, H., Hu, Z., Lian, D., Wang, H., Huang, Z.: Neural memory streaming recommender networks with adversarial training. In: SIGKDD, pp. 2467\u20132475 (2018)","DOI":"10.1145\/3219819.3220004"},{"key":"46_CR33","doi-asserted-by":"crossref","unstructured":"Wang, Z., Zhang, J., Feng, J., Chen, Z.: Knowledge graph embedding by translating on hyperplanes. In: AAAI, vol. 14, pp. 1112\u20131119 (2014)","DOI":"10.1609\/aaai.v28i1.8870"},{"key":"46_CR34","unstructured":"Yang, B., Yih, W.t., He, X., Gao, J., Deng, L.: Embedding entities and relations for learning and inference in knowledge bases. arXiv (2014)"},{"issue":"3","key":"46_CR35","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1145\/2629461","volume":"32","author":"H Yin","year":"2014","unstructured":"Yin, H., Cui, B., Sun, Y., Hu, Z., Chen, L.: Lcars: a spatial item recommender system. TOIS 32(3), 11 (2014)","journal-title":"TOIS"},{"key":"46_CR36","doi-asserted-by":"crossref","unstructured":"Yin, H., Wang, Q., Zheng, K., Li, Z., Yang, J., Zhou, X.: Social influence-based group representation learning for group recommendation. In: ICDE (2019)","DOI":"10.1109\/ICDE.2019.00057"},{"key":"46_CR37","doi-asserted-by":"crossref","unstructured":"Yin, H., Zou, L., Nguyen, Q.V.H., Huang, Z., Zhou, X.: Joint event-partner recommendation in event-based social networks. In: ICDE (2018)","DOI":"10.1109\/ICDE.2018.00088"},{"key":"46_CR38","doi-asserted-by":"crossref","unstructured":"Zhang, J., Shi, X., King, I., Yeung, D.Y.: Dynamic key-value memory networks for knowledge tracing. In: WWW, pp. 765\u2013774 (2017)","DOI":"10.1145\/3038912.3052580"}],"container-title":["Lecture Notes in Computer Science","Database Systems for Advanced Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-18576-3_46","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T13:01:42Z","timestamp":1710334902000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-18576-3_46"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030185756","9783030185763"],"references-count":38,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-18576-3_46","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"24 April 2019","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":"Chiang Mai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Thailand","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":"22 April 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 April 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dasfaa2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/dasfaa2019.eng.cmu.ac.th\/","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":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"501","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":"92","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":"64","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":"18% - 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":"3","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":"13 demo papers, 6 tutorial 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)"}}]}}