{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T13:07:02Z","timestamp":1765544822629,"version":"3.40.3"},"publisher-location":"Cham","reference-count":33,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030883607"},{"type":"electronic","value":"9783030883614"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"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":[[2021]]},"DOI":"10.1007\/978-3-030-88361-4_16","type":"book-chapter","created":{"date-parts":[[2021,9,29]],"date-time":"2021-09-29T07:07:22Z","timestamp":1632899242000},"page":"270-286","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Using Compositional Embeddings for Fact Checking"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1614-2391","authenticated-orcid":false,"given":"Ana Alexandra Morim","family":"da Silva","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8609-8277","authenticated-orcid":false,"given":"Michael","family":"R\u00f6der","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7112-3516","authenticated-orcid":false,"given":"Axel-Cyrille Ngonga","family":"Ngomo","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,9,30]]},"reference":[{"issue":"3","key":"16_CR1","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1016\/S0378-8733(03)00009-1","volume":"25","author":"LA Adamic","year":"2003","unstructured":"Adamic, L.A., Adar, E.: Friends and neighbors on the web. Soc. Netw. 25(3), 211\u2013230 (2003)","journal-title":"Soc. Netw."},{"doi-asserted-by":"crossref","unstructured":"Athreya, R.G., Ngonga Ngomo, A.C., Usbeck, R.: Enhancing community interactions with data-driven chatbots-the dbpedia chatbot. In: Companion of the Web Conference 2018 on the Web Conference 2018, pp. 143\u2013146 (2018)","key":"16_CR2","DOI":"10.1145\/3184558.3186964"},{"key":"16_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"722","DOI":"10.1007\/978-3-540-76298-0_52","volume-title":"The Semantic Web","author":"S Auer","year":"2007","unstructured":"Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., Ives, Z.: DBpedia: a nucleus for a web of open data. In: Aberer, K., et al. (eds.) ASWC\/ISWC -2007. LNCS, vol. 4825, pp. 722\u2013735. Springer, Heidelberg (2007). https:\/\/doi.org\/10.1007\/978-3-540-76298-0_52"},{"unstructured":"Bordes, A., Usunier, N., Garcia-Duran, A., Weston, J., Yakhnenko, O.: Translating embeddings for modeling multi-relational data. In: Advances in Neural Information Processing Systems, pp. 2787\u20132795 (2013)","key":"16_CR4"},{"unstructured":"Chah, N.: OK google, what is your ontology? or: exploring freebase classification to understand Google\u2019s knowledge graph. CoRR abs\/1805.03885 (2018)","key":"16_CR5"},{"issue":"6","key":"16_CR6","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0128193","volume":"10","author":"GL Ciampaglia","year":"2015","unstructured":"Ciampaglia, G.L., Shiralkar, P., Rocha, L.M., Bollen, J., Menczer, F., Flammini, A.: Computational fact checking from knowledge networks. PLoS ONE 10(6), e0128193 (2015)","journal-title":"PLoS ONE"},{"doi-asserted-by":"crossref","unstructured":"Demir, C., Ngonga Ngomo, A.C.: Convolutional complex knowledge graph embeddings. In: Proceedings of the Extended Semantic Web Conference (2020)","key":"16_CR7","DOI":"10.1007\/978-3-030-77385-4_24"},{"doi-asserted-by":"crossref","unstructured":"Dettmers, T., Minervini, P., Stenetorp, P., Riedel, S.: Convolutional 2D knowledge graph embeddings. CoRR abs\/1707.01476 (2017)","key":"16_CR8","DOI":"10.1609\/aaai.v32i1.11573"},{"key":"16_CR9","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/j.websem.2015.08.001","volume":"35","author":"D Gerber","year":"2015","unstructured":"Gerber, D., et al.: DeFacto\u2013temporal and multilingual deep fact validation. Web Semantics 35, 85\u2013101 (2015)","journal-title":"Web Semantics"},{"doi-asserted-by":"crossref","unstructured":"Jeh, G., Widom, J.: Simrank: a measure of structural-context similarity. In: Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2002)","key":"16_CR10","DOI":"10.1145\/775047.775126"},{"doi-asserted-by":"crossref","unstructured":"Ji, S., Pan, S., Cambria, E., Marttinen, P., Yu, P.S.: A survey on knowledge graphs: representation, acquisition, and applications. IEEE Trans. Neural Netw. Learn. Syst. 1\u201321 (2021)","key":"16_CR11","DOI":"10.1109\/TNNLS.2021.3070843"},{"issue":"1","key":"16_CR12","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1007\/BF02289026","volume":"18","author":"L Katz","year":"1953","unstructured":"Katz, L.: A new status index derived from sociometric analysis. Psychometrika 18(1), 39\u201343 (1953)","journal-title":"Psychometrika"},{"issue":"1","key":"16_CR13","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."},{"issue":"11","key":"16_CR14","doi-asserted-by":"publisher","first-page":"1370","DOI":"10.14778\/3137628.3137646","volume":"10","author":"F Li","year":"2017","unstructured":"Li, F., Dong, X.L., Langen, A., Li, Y.: Knowledge verification for long-tail verticals. Proc. VLDB Endow. 10(11), 1370\u20131381 (2017)","journal-title":"Proc. VLDB Endow."},{"doi-asserted-by":"crossref","unstructured":"Liben-Nowell, D., Kleinberg, J.: The link prediction problem for social networks. In: Proceedings of the Twelfth International Conference on Information and Knowledge Management (2003)","key":"16_CR15","DOI":"10.1145\/956863.956972"},{"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: Twenty-Ninth AAAI Conference on Artificial Intelligence (2015)","key":"16_CR16","DOI":"10.1609\/aaai.v29i1.9491"},{"unstructured":"Lu, H., Hu, H.: Dense: an enhanced non-abelian group representation for knowledge graph embedding (2020)","key":"16_CR17"},{"key":"16_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"376","DOI":"10.1007\/978-3-030-00668-6_23","volume-title":"The Semantic Web \u2013 ISWC 2018","author":"S Malyshev","year":"2018","unstructured":"Malyshev, S., Kr\u00f6tzsch, M., Gonz\u00e1lez, L., Gonsior, J., Bielefeldt, A.: Getting the most out of wikidata: semantic technology usage in wikipedia\u2019s knowledge graph. In: Vrande\u010di\u0107, D., et al. (eds.) ISWC 2018. LNCS, vol. 11137, pp. 376\u2013394. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-00668-6_23"},{"doi-asserted-by":"crossref","unstructured":"Nickel, M., Tresp, V., Kriegel, H.P.: Factorizing yago: scalable machine learning for linked data. In: Proceedings of the 21st International Conference on World Wide Web (2012)","key":"16_CR19","DOI":"10.1145\/2187836.2187874"},{"unstructured":"Shi, B., Weninger, T.: Fact checking in large knowledge graphs - a discriminative predicate path mining approach. CoRR abs\/1510.05911 (2015)","key":"16_CR20"},{"key":"16_CR21","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1016\/j.knosys.2016.04.015","volume":"104","author":"B Shi","year":"2016","unstructured":"Shi, B., Weninger, T.: Discriminative predicate path mining for fact checking in knowledge graphs. Knowl.-Based Syst. 104, 123\u2013133 (2016)","journal-title":"Knowl.-Based Syst."},{"doi-asserted-by":"crossref","unstructured":"Shiralkar, P., Flammini, A., Menczer, F., Ciampaglia, G.L.: Finding streams in knowledge graphs to support fact checking. In: 2017 IEEE International Conference on Data Mining (ICDM), pp. 859\u2013864. IEEE (2017)","key":"16_CR22","DOI":"10.1109\/ICDM.2017.105"},{"unstructured":"Singhal, A.: Introducing the knowledge graph: things, not strings. Official google blog, May 2012. https:\/\/www.blog.google\/products\/search\/introducing-knowledge-graph-things-not\/","key":"16_CR23"},{"unstructured":"Socher, R., Chen, D., Manning, C.D., Ng, A.: Reasoning with neural tensor networks for knowledge base completion. In: Advances in Neural Information Processing Systems (2013)","key":"16_CR24"},{"issue":"11","key":"16_CR25","doi-asserted-by":"publisher","first-page":"992","DOI":"10.14778\/3402707.3402736","volume":"4","author":"Y Sun","year":"2011","unstructured":"Sun, Y., Han, J., Yan, X., Yu, P.S., Wu, T.: Pathsim: meta path-based top-k similarity search in heterogeneous information networks. Proc. VLDB Endow. 4(11), 992\u20131003 (2011)","journal-title":"Proc. VLDB Endow."},{"unstructured":"Sun, Z., Deng, Z., Nie, J., Tang, J.: Rotate: knowledge graph embedding by relational rotation in complex space. CoRR abs\/1902.10197 (2019)","key":"16_CR26"},{"doi-asserted-by":"crossref","unstructured":"Syed, Z.H., R\u00f6der, M., Ngonga Ngomo, A.C.: Factcheck: validating RDF triples using textual evidence. In: Proceedings of the 27th ACM International Conference on Information and Knowledge Management, pp. 1599\u20131602. ACM (2018)","key":"16_CR27","DOI":"10.1145\/3269206.3269308"},{"key":"16_CR28","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"630","DOI":"10.1007\/978-3-030-30793-6_36","volume-title":"The Semantic Web \u2013 ISWC 2019","author":"ZH Syed","year":"2019","unstructured":"Syed, Z.H., R\u00f6der, M., Ngomo, A.-C.N.: Unsupervised discovery of corroborative paths for fact validation. In: Ghidini, C., et al. (eds.) ISWC 2019. LNCS, vol. 11778, pp. 630\u2013646. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-30793-6_36"},{"doi-asserted-by":"crossref","unstructured":"Toutanova, K., Chen, D., Pantel, P., Poon, H., Choudhury, P., Gamon, M.: Representing text for joint embedding of text and knowledge bases. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp. 1499\u20131509, September 2015","key":"16_CR29","DOI":"10.18653\/v1\/D15-1174"},{"issue":"12","key":"16_CR30","doi-asserted-by":"publisher","first-page":"2724","DOI":"10.1109\/TKDE.2017.2754499","volume":"29","author":"Q Wang","year":"2017","unstructured":"Wang, Q., Mao, Z., Wang, B., Guo, L.: Knowledge graph embedding: a survey of approaches and applications. IEEE Trans. Knowl. Data Eng. 29(12), 2724\u20132743 (2017)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"doi-asserted-by":"crossref","unstructured":"Wang, Z., Zhang, J., Feng, J., Chen, Z.: Knowledge graph embedding by translating on hyperplanes. In: Twenty-Eighth AAAI Conference on Artificial Intelligence (2014)","key":"16_CR31","DOI":"10.1609\/aaai.v28i1.8870"},{"key":"16_CR32","doi-asserted-by":"publisher","first-page":"294","DOI":"10.1016\/j.physa.2016.03.091","volume":"456","author":"Z Xu","year":"2016","unstructured":"Xu, Z., Pu, C., Yang, J.: Link prediction based on path entropy. Phys. A 456, 294\u2013301 (2016)","journal-title":"Phys. A"},{"key":"16_CR33","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1016\/j.knosys.2014.12.014","volume":"76","author":"M Zhao","year":"2015","unstructured":"Zhao, M., Chow, T.W., Zhang, Z., Li, B.: Automatic image annotation via compact graph based semi-supervised learning. Knowl.-Based Syst. 76, 148\u2013165 (2015)","journal-title":"Knowl.-Based Syst."}],"container-title":["Lecture Notes in Computer Science","The Semantic Web \u2013 ISWC 2021"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-88361-4_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,10]],"date-time":"2023-01-10T18:32:16Z","timestamp":1673375536000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-88361-4_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030883607","9783030883614"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-88361-4_16","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"30 September 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ISWC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Semantic Web Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 October 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 October 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"semweb2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iswc2021.semanticweb.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":"Easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"202","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":"42","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":"21% - 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":"3.5","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":"2.5","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)"}}]}}