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Accurate unlexicalized parsing
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Probabilistic Message Passing in Peer Data Management Systems
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Wikify!: linking documents to encyclopedic knowledge
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Entity Name System: The Back-Bone of an Open and Scalable Web of Data
ICSC '08 Proceedings of the 2008 IEEE International Conference on Semantic Computing
idMesh: graph-based disambiguation of linked data
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Broad-coverage sense disambiguation and information extraction with a supersense sequence tagger
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Open information extraction from the web
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Boilerplate detection using shallow text features
Proceedings of the third ACM international conference on Web search and data mining
Ad-hoc object retrieval in the web of data
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Annotating named entities in Twitter data with crowdsourcing
CSLDAMT '10 Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk
Overview of the INEX 2009 entity ranking track
INEX'09 Proceedings of the Focused retrieval and evaluation, and 8th international conference on Initiative for the evaluation of XML retrieval
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ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
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Crowdsourcing for book search evaluation: impact of hit design on comparative system ranking
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Enhanced results for web search
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Repeatable and reliable search system evaluation using crowdsourcing
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Proceedings of the VLDB Endowment
Effective and efficient entity search in RDF data
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dipLODocus[RDF]: short and long-tail RDF analytics for massive webs of data
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DBpedia spotlight: shedding light on the web of documents
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Factor graphs and the sum-product algorithm
IEEE Transactions on Information Theory
Map to humans and reduce error: crowdsourcing for deduplication applied to digital libraries
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CrowdMap: crowdsourcing ontology alignment with microtasks
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part I
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Leveraging transitive relations for crowdsourced joins
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Microblog-genre noise and impact on semantic annotation accuracy
Proceedings of the 24th ACM Conference on Hypertext and Social Media
Like prediction: modeling like counts by bridging facebook pages with linked data
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RESLVE: leveraging user interest to improve entity disambiguation on short text
Proceedings of the 22nd international conference on World Wide Web companion
Pick-a-crowd: tell me what you like, and i'll tell you what to do
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User-driven quality evaluation of DBpedia
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Social drive: a crowdsourcing-based vehicular social networking system for green transportation
Proceedings of the third ACM international symposium on Design and analysis of intelligent vehicular networks and applications
Question selection for crowd entity resolution
Proceedings of the VLDB Endowment
Large-scale linked data integration using probabilistic reasoning and crowdsourcing
The VLDB Journal — The International Journal on Very Large Data Bases
Effective named entity recognition for idiosyncratic web collections
Proceedings of the 23rd international conference on World wide web
Crowdsourced Knowledge Acquisition: Towards Hybrid-Genre Workflows
International Journal on Semantic Web & Information Systems
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We tackle the problem of entity linking for large collections of online pages; Our system, ZenCrowd, identifies entities from natural language text using state of the art techniques and automatically connects them to the Linked Open Data cloud. We show how one can take advantage of human intelligence to improve the quality of the links by dynamically generating micro-tasks on an online crowdsourcing platform. We develop a probabilistic framework to make sensible decisions about candidate links and to identify unreliable human workers. We evaluate ZenCrowd in a real deployment and show how a combination of both probabilistic reasoning and crowdsourcing techniques can significantly improve the quality of the links, while limiting the amount of work performed by the crowd.