{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:35:55Z","timestamp":1750221355544,"version":"3.41.0"},"publisher-location":"New York, New York, USA","reference-count":7,"publisher":"ACM Press","license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1145\/3184558.3186241","type":"proceedings-article","created":{"date-parts":[[2018,4,18]],"date-time":"2018-04-18T18:04:25Z","timestamp":1524074665000},"page":"501-505","source":"Crossref","is-referenced-by-count":0,"title":["HARE"],"prefix":"10.1145","author":[{"given":"Maribel","family":"Acosta","sequence":"first","affiliation":[{"name":"Karlsruhe Institute of Technology, Karlsruhe, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elena","family":"Simperl","sequence":"additional","affiliation":[{"name":"University of Southampton, Southampton, United Kingdom"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fabian","family":"Fl\u00f6ck","sequence":"additional","affiliation":[{"name":"GESIS - Leibniz Institute for the Social Sciences, K\u00f6ln, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maria-Esther","family":"Vidal","sequence":"additional","affiliation":[{"name":"TIB Information Center - Universidad Simon Bolivar, Hannover, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","reference":[{"key":"key-10.1145\/3184558.3186241-1","unstructured":"Ziawasch Abedjan, Toni Grütze, Anja Jentzsch, and Felix Naumann. 2014. Profiling and mining RDF data with ProLOD+. In IEEE 30th International Conference on Data Engineering, Chicago, ICDE 2014, IL, USA, March 31 - April 4, 2014. 1198--1201."},{"key":"key-10.1145\/3184558.3186241-2","doi-asserted-by":"crossref","unstructured":"Maribel Acosta, Elena Simperl, Fabian Flöck, and Maria-Esther Vidal. 2015. HARE: A Hybrid SPARQL Engine to Enhance Query Answers via Crowdsourcing Proceedings of the 8th International Conference on Knowledge Capture, K-CAP 2015, Palisades, NY, USA, October 7--10, 2015. 11:1--11:8.","DOI":"10.1145\/2815833.2815848"},{"key":"key-10.1145\/3184558.3186241-3","doi-asserted-by":"crossref","unstructured":"Maribel Acosta, Elena Simperl, Fabian Flöck, and Maria-Esther Vidal. 2017. Enhancing answer completeness of SPARQL queries via crowdsourcing. Web Semantics: Science, Services and Agents on the World Wide Web (2017). \/10.1007\/3--540--45921--9","DOI":"10.1016\/j.websem.2017.07.001"},{"key":"key-10.1145\/3184558.3186241-4","doi-asserted-by":"crossref","unstructured":"H. Park, R. Pang, A. G. Parameswaran, H. Garcia-Molina, N. Polyzotis, and J. Widom. 2012. Deco: A System for Declarative Crowdsourcing. PVLDB, Vol. 5, 12 (2012), 1990--1993.","DOI":"10.14778\/2367502.2367555"},{"key":"key-10.1145\/3184558.3186241-5","doi-asserted-by":"crossref","unstructured":"Hyunjung Park and Jennifer Widom. 2013. Query Optimization over Crowdsourced Data. PVLDB, Vol. 6, 10 (2013), 781--792.","DOI":"10.14778\/2536206.2536207"},{"key":"key-10.1145\/3184558.3186241-6","doi-asserted-by":"crossref","unstructured":"Hyunjung Park and Jennifer Widom. 2014. CrowdFill: collecting structured data from the crowd SIGMOD. 577--588.","DOI":"10.1145\/2588555.2610503"},{"key":"key-10.1145\/3184558.3186241-7","doi-asserted-by":"crossref","unstructured":"Amrapali Zaveri, Anisa Rula, Andrea Maurino, Ricardo Pietrobon, Jens Lehmann, and Sören Auer. 2016. Quality assessment for Linked Data: A Survey. Semantic Web, Vol. 7, 1 (2016), 63--93.","DOI":"10.3233\/SW-150175"}],"event":{"number":"2018","sponsor":["IW3C2, International World Wide Web Conference Committee","SIGWEB, ACM Special Interest Group on Hypertext, Hypermedia, and Web"],"acronym":"WWW '18","name":"Companion of the The Web Conference 2018","start":{"date-parts":[[2018,4,23]]},"location":"Lyon, France","end":{"date-parts":[[2018,4,27]]}},"container-title":["Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3184558.3186241","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/dl.acm.org\/ft_gateway.cfm?id=3186241&ftid=1958219&dwn=1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T02:26:06Z","timestamp":1750213566000},"score":1,"resource":{"primary":{"URL":"http:\/\/dl.acm.org\/citation.cfm?doid=3184558.3186241"}},"subtitle":["An Engine for Enhancing Answer Completeness of SPARQL Queries via Crowdsourcing"],"proceedings-subject":"The Web Conference 2018","short-title":[],"issued":{"date-parts":[[2018]]},"references-count":7,"URL":"https:\/\/doi.org\/10.1145\/3184558.3186241","relation":{},"subject":[],"published":{"date-parts":[[2018]]}}}