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Infrastructure for rapid open knowledge network development
dc.contributor.authorCafarella, Michael
dc.contributor.authorAnderson, Michael
dc.contributor.authorBeltagy, Iz
dc.contributor.authorCattan, Arie
dc.contributor.authorChasins, Sarah
dc.contributor.authorDagan, Ido
dc.contributor.authorDowney, Doug
dc.contributor.authorEtzioni, Oren
dc.contributor.authorFeldman, Sergey
dc.contributor.authorGao, Tian
dc.contributor.authorHope, Tom
dc.contributor.authorHuang, Kexin
dc.contributor.authorJohnson, Sophie
dc.contributor.authorKing, Daniel
dc.contributor.authorLo, Kyle
dc.contributor.authorLou, Yuze
dc.contributor.authorShapiro, Matthew
dc.contributor.authorShen, Dinghao
dc.contributor.authorSubramanian, Shivashankar
dc.contributor.authorWang, Lucy Lu
dc.contributor.authorWang, Yuning
dc.contributor.authorWang, Yitong
dc.contributor.authorWeld, Daniel S.
dc.contributor.authorVo-Phamhi, Jenny
dc.contributor.authorZeng, Anna
dc.contributor.authorZou, Jiayun
dc.date.accessioned2022-04-08T18:03:55Z
dc.date.available2023-04-08 14:03:53en
dc.date.available2022-04-08T18:03:55Z
dc.date.issued2022-03
dc.identifier.citationCafarella, Michael; Anderson, Michael; Beltagy, Iz; Cattan, Arie; Chasins, Sarah; Dagan, Ido; Downey, Doug; Etzioni, Oren; Feldman, Sergey; Gao, Tian; Hope, Tom; Huang, Kexin; Johnson, Sophie; King, Daniel; Lo, Kyle; Lou, Yuze; Shapiro, Matthew; Shen, Dinghao; Subramanian, Shivashankar; Wang, Lucy Lu; Wang, Yuning; Wang, Yitong; Weld, Daniel S.; Vo-Phamhi, Jenny ; Zeng, Anna; Zou, Jiayun (2022). "Infrastructure for rapid open knowledge network development." AI Magazine 43(1): 59-68.
dc.identifier.issn0738-4602
dc.identifier.issn2371-9621
dc.identifier.urihttps://hdl.handle.net/2027.42/172012
dc.description.abstractThe past decade has witnessed a growth in the use of knowledge graph technologies for advanced data search, data integration, and query‐answering applications. The leading example of a public, general‐purpose open knowledge network (aka knowledge graph) is Wikidata, which has demonstrated remarkable advances in quality and coverage over this time. Proprietary knowledge graphs drive some of the leading applications of the day including, for example, Google Search, Alexa, Siri, and Cortana. Open Knowledge Networks are exciting: they promise the power of structured database‐like queries with the potential for the wide coverage that is today only provided by the Web. With the current state of the art, building, using, and scaling large knowledge networks can still be frustratingly slow. This article describes a National Science Foundation Convergence Accelerator project to build a set of Knowledge Network Programming Infrastructure systems to address this issue.
dc.publisherWiley Periodicals, Inc.
dc.publisherSpringer‐Verlag
dc.titleInfrastructure for rapid open knowledge network development
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelComputer Science
dc.subject.hlbtoplevelEngineering
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/172012/1/aaai12038_am.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/172012/2/aaai12038.pdf
dc.identifier.doi10.1002/aaai.12038
dc.identifier.sourceAI Magazine
dc.identifier.citedreferenceBarman, S., S. Chasins, R. Bodík, and S. Gulwani. 2016. “ Ringer: Web Automation by Demonstration.” In Proceedings of the 2016 ACM SIGPLAN International Conference on Object‐Oriented Programming, Systems, Languages, and Applications, OOPSLA 2016, part of SPLASH 2016, eds. E. Visser, and Y. Smaragdakis, 748 – 64. Amsterdam, The Netherlands: ACM. October 30–November 4, 2016.
dc.identifier.citedreference2019. “ Welcome to MusicBrainz! ” https://musicbrainz.org/ (accessed May 30, 2019).
dc.identifier.citedreferenceGeoNames. 2019. GeoNames. http://www.geonames.org/ (accessed May 30, 2019).
dc.identifier.citedreferenceFerreira, A. A., M. A. Gonçalves, and A. H. Laender. 2012. “ A Brief Survey of Automatic Methods for Author Name Disambiguation.” SIGMOD Rec. 41 ( 2 ): 15 – 26.
dc.identifier.citedreferenceEtzioni, O., M. J. Cafarella, D. Downey, S. Kok, A. Popescu, T. Shaked, S. Soderland, D. S. Weld, and A. Yates. 2004. “ Web‐Scale Information Extraction in KnowItAll: (Preliminary Results).” In Proceedings of the 13th International Conference on World Wide Web, WWW 2004, 100 – 10. New York, NY, USA; ACM. May 17–20, 2004.
dc.identifier.citedreferenceCybulska, A., and P. Vossen. 2014. “ Using a Sledgehammer to Crack a Nut? Lexical Diversity and Event Coreference Resolution.” In Proceedings of the LREC, 4545 – 52. Reykjavik: Iceland. https://aclanthology.org/L14-1646/
dc.identifier.citedreferenceCohan, A., S. Feldman, I. Beltagy, D. Downey, and D. Weld. 2020. “ SPECTER: Document‐level Representation Learning using Citation‐informed Transformers.” In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2270 – 82. Association for Computational Linguistics. https://www.researchgate.net/publication/343302079_SPECTER_Document-level_Representation_Learning_using_Citationinformed_Transformers
dc.identifier.citedreferenceChasins, S. E., M. Mueller, and R. Bodík. 2018. “ Rousillon: Scraping Distributed Hierarchical Web Data.” In Baudisch, P.; Schmidt, A.; and Wilson, A., eds. 2018. In Proceedings of the 31st Annual ACM Symposium on User Interface Software and Technology, UIST 2018, 963 – 75. Berlin, Germany: ACM. October 14–17, 2018. https://dl.acm.org/doi/abs/10.1145/3242587.3242661
dc.identifier.citedreferenceCattan, A., S. Johnson, D. Weld, I. Dagan, I. Beltagy, D. Downey, and T. Hope. 2021. SciCo: Hierarchical Cross‐Document Coreference for Scientific Concepts.
dc.identifier.citedreferenceCattan, A., A. Eirew, G. Stanovsky, M. Joshi, and I. Dagan. 2020. “ Streamlining Cross‐Document Coreference Resolution: Evaluation and Modeling.” https://arxiv.org/abs/2009.11032
dc.identifier.citedreferenceBizer, C. 2009. “ The Emerging Web of Linked Data.” IEEE Intelligent Systems 24 ( 5 ): 87 – 92.
dc.identifier.citedreferenceAuer, S., C. Bizer, G. Kobilarov, J. Lehmann, R. Cyganiak, and Z. Ives. 2007. “ DBpedia: A Nucleus for a Web of Open Data.” In Proceedings of the 6th International The Semantic Web and 2Nd Asian Conference on Asian Semantic Web Conference, ISWC’07/ASWC’07, 722 – 35. Berlin, Heidelberg: Springer‐Verlag. https://doi.org/10.1007/978-3-540-76298-0_52
dc.identifier.citedreferenceZhang, Y., F. Zhang, P. Yao, and J. Tang. 2018. “ Name Disambiguation in AMiner: Clustering, Maintenance, and Human in the Loop.” In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD’18, 1002 – 11. New York, NY, USA: Association for Computing Machinery. https://dl.acm.org/doi/10.1145/3219819.3219859
dc.identifier.citedreferenceZeng, A., I. Sabek, and M. Cafarella. 2021. Unpublished Analysis of Wikidata Dumps.
dc.identifier.citedreferenceXu, Y., M. Li, L. Cui, S. Huang, F. Wei, and M. Zhou. 2020. “ LayoutLM: Pre‐Training of Text and Layout for Document Image Understanding.” Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining New York, NY, USA: Association for Computing Machinery. 1192 – 200. https://dl.acm.org/doi/10.1145/3394486.3403172
dc.identifier.citedreferenceWang, L. L., K. Lo, Y. Chandrasekhar, R. Reas, J. Yang, D. Burdick, D. Eide, K. Funk, Y. Katsis, R. M. Kinney, Y. Li, Z. Liu, W. Merrill, P. Mooney, D. A. Murdick, D. Rishi, J. Sheehan, Z. Shen, B. Stilson, A. D. Wade, K. Wang, N. X. R. Wang, C. Wilhelm, B. Xie, D. M. Raymond, D. S. Weld, O. Etzioni, and S. Kohlmeier. 2020. “ CORD‐19: The COVID‐19 Open Research Dataset.” In Proceedings of the 1st Workshop on NLP for COVID‐19 at ACL 2020. Association for Computational Linguistics; Seattle, WA. https://arxiv.org/abs/2004.10706
dc.identifier.citedreferenceVrandečić, D., and M. Krötzsch 2014. “ Wikidata: A Free Collaborative Knowledgebase.” Communications of the ACM 57 ( 10 ): 78 – 85.
dc.identifier.citedreferenceTheUniProtConsortium. 2018. “ UniProt: A Worldwide Hub of Protein Knowledge.” Nucleic Acids Research 47: D506 – 15.
dc.identifier.citedreferenceSuchanek, F. M., G. Kasneci, and G. Weikum. 2007. “ Yago: A Core of Semantic Knowledge.” In Proceedings of the 16th International Conference on World Wide Web, WWW’07, 697 – 706. New York, NY, USA: ACM. https://dblp.org/rec/conf/www/SuchanekKW07.html?view=bibtex
dc.identifier.citedreferenceSubramanian, S., D. King, D. Downey, and S. Feldman. 2021. “ S2AND: A Benchmark and Evaluation System for Author Name Disambiguation.”
dc.identifier.citedreferenceSinghal, A. 2012. “ Introducing the Knowledge Graph: Things, Not Strings.” https://googleblog.blogspot.com/2012/05/introducing‐knowledge‐graph‐things‐not.html (accessed May 30, 2019).
dc.identifier.citedreferenceShen, Z., R. Zhang, M. Dell, B. C. G. Lee, J. Carlson, and W. Li. 2021. LayoutParser: A Unified Toolkit for Deep Learning Based Document Image Analysis.
dc.identifier.citedreferenceRoberts, K., T. Alam, S. Bedrick, D. Demner‐Fushman, K. Lo, I. Soboroff, E. Voorhees, L. L. Wang, and W. Hersh. 2020. “ TREC‐COVID: Rationale and Structure of an Information Retrieval Shared Task for COVID‐19.” Journal of the American Medical Informatics Association: JAMIA 27: 1431 – 6.
dc.identifier.citedreferenceNeumann, M., Z. Shen, and S. Skjonsberg. 2021. PAWLS: PDF Annotation With Labels and Structure.
dc.working.doiNOen
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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