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Crowdsourced Collective Entity Resolution with Relational Match Propagation [article]

Jiacheng Huang and Wei Hu and Zhifeng Bao and Yuzhong Qu
2020 arXiv   pre-print
In this paper, we propose a novel approach called crowdsourced collective ER, which leverages the relationships between entities to infer matches jointly rather than independently.  ...  Knowledge bases (KBs) store rich yet heterogeneous entities and facts. Entity resolution (ER) aims to identify entities in KBs which refer to the same real-world object.  ...  There remain two challenges to achieve such a crowdsourced collective ER. The first challenge is how to conduct an effective relational match propagation.  ... 
arXiv:2002.09361v1 fatcat:smnyozdz2zbptct36bbiqjl75m

Crowdsourced Collective Entity Resolution with Relational Match Propagation

Jiacheng Huang, Wei Hu, Zhifeng Bao, Yuzhong Qu
2020 2020 IEEE 36th International Conference on Data Engineering (ICDE)  
In this paper, we propose a novel approach called crowdsourced collective ER, which leverages the relationships between entities to infer matches jointly rather than independently.  ...  Knowledge bases (KBs) store rich yet heterogeneous entities and facts. Entity resolution (ER) aims to identify entities in KBs which refer to the same real-world object.  ...  There remain two challenges to achieve such a crowdsourced collective ER. The first challenge is how to conduct an effective relational match propagation.  ... 
doi:10.1109/icde48307.2020.00011 dblp:conf/icde/HuangHBQ20 fatcat:vbdojyxaxveepf5todo72lkk3m

Effective Crowdsourcing of Multiple Tasks for Comprehensive Knowledge Extraction

Sangha Nam, Minho Lee, Donghwan Kim, Kijong Han, Kuntae Kim, Sooji Yoon, Eun-Kyung Kim, Key-Sun Choi
2020 International Conference on Language Resources and Evaluation  
., entity linking, coreference resolution, and relation extraction), data are not available for a continuous and coherent evaluation of all information extraction tasks in a comprehensive framework.  ...  This paper aims to propose a Korean information extraction initiative point and promote research in this field by presenting crowdsourcing data collected for four information extraction tasks from the  ...  Because when we collected the crowdsourcing data only with the common corpus of entity linking and co-reference resolution, the dataset was small and the relation extrac- tion model could not be trained  ... 
dblp:conf/lrec/NamLKHKYKC20 fatcat:ji3czrrxrvbc5eijsvxpiuqqoq

Large-scale linked data integration using probabilistic reasoning and crowdsourcing

Gianluca Demartini, Djellel Eddine Difallah, Philippe Cudré-Mauroux
2013 The VLDB journal  
Finally, we resort to human computation by dynamically generating crowdsourcing tasks in case the algorithmic components fail to come up with convincing results.  ...  We tackle the problems of semiautomatically matching linked data sets and of linking large collections of Web pages to linked data.  ...  Reference reconciliation [21] , for example, builds a dependency graph and exploits relations to propagate information among entities.  ... 
doi:10.1007/s00778-013-0324-z fatcat:s6g6emp2qjeflkoasym37ys5fm

Fault-Tolerant Entity Resolution with the Crowd [article]

Anja Gruenheid and Besmira Nushi and Tim Kraska and Wolfgang Gatterbauer and Donald Kossmann
2015 arXiv   pre-print
Although the crowd generates insightful information especially for complex problems such as entity resolution (ER), the output quality of crowd workers is often noisy.  ...  In recent years, crowdsourcing is increasingly applied as a means to enhance data quality.  ...  CONCLUSION In this work, we discussed the problem of entity resolution with unreliable data collected through crowdsourcing.  ... 
arXiv:1512.00537v1 fatcat:cfkaaju3kndnbezglerqvyfs54

Refining Automatically Extracted Knowledge Bases Using Crowdsourcing

Chunhua Li, Pengpeng Zhao, Victor S. Sheng, Xuefeng Xian, Jian Wu, Zhiming Cui
2017 Computational Intelligence and Neuroscience  
Then, based on semantic constraints, we propose rank-based and graph-based algorithms for crowdsourced knowledge refining, which judiciously select the most beneficial candidate facts to conduct crowdsourcing  ...  In this paper, we leverage crowdsourcing to improve the quality of automatically extracted knowledge bases.  ...  12] , image classification [13] , and entity resolution [14] .  ... 
doi:10.1155/2017/4092135 pmid:28588611 pmcid:PMC5446892 fatcat:ntycm4lnrrfobmrvmone6fks64

Crowdsourced Data Management: A Survey

Guoliang Li, Jiannan Wang, Yudian Zheng, Michael J. Franklin
2016 IEEE Transactions on Knowledge and Data Engineering  
These tasks, such as entity resolution, sentiment analysis, and image recognition can be enhanced through the use of human cognitive ability.  ...  There has been significant work addressing these three factors for designing crowdsourced tasks, developing crowdsourced data manipulation operators, and optimizing plans consisting of multiple operators  ...  In addition, a crowdsourcing system can provide specialized operators for certain purposes. For example, entity resolution can use a crowdsourced join to find objects referring to the same entity.  ... 
doi:10.1109/tkde.2016.2535242 fatcat:sit3comyvra4djqkl4xre3kj24

A Survey of Volunteered Open Geo-Knowledge Bases in the Semantic Web [chapter]

Andrea Ballatore, David C. Wilson, Michela Bertolotto
2013 Intelligent Systems Reference Library  
Over the past decade, rapid advances in web technologies, coupled with innovative models of spatial data collection and consumption, have generated a robust growth in geo-referenced information, resulting  ...  Particular attention is devoted to the crucial issue of the quality of geo-knowledge bases, as well as of crowdsourced data.  ...  A related task is that of 'spatial co-reference resolution,' i.e. determining whether two digital representations refer to the same real-world entity.  ... 
doi:10.1007/978-3-642-37688-7_5 fatcat:i72rmxk36fbnrmnrdpkmccrbfu

An Overview of End-to-End Entity Resolution for Big Data

Vassilis Christophides, Vasilis Efthymiou, Themis Palpanas, George Papadakis, Kostas Stefanidis
2020 ACM Computing Surveys  
or by propagating their similarity to 217 neighbor entities via relations that will be matched in a next round.  ...  An Overview of End-to-End Entity Resolution for Big Data 127:33 intelligently addressed by a series of Crowdsourcing-based ER methods.  ...  Added knowledge can be measured by the number of relationships of a merged en-1320 tity with other entities.  ... 
doi:10.1145/3418896 fatcat:7sm2ag7uljfg7h3hvljyjg2sgm

Semantic Enhancement of Volunteered Geographic Information

Laura Di Rocco
2016 International Conference of the Italian Association for Artificial Intelligence  
To overcome this heterogeneity and quality problem, a solution is to rely on ontologies to classify spatial entities tags and names.  ...  This problem is addressed in the PhD project with specific reference to the tags used in OpenStreetMap for describing georeferenced objects relevant in urban context, producing as result an ontology for  ...  With our approach, we perform a matching between OSM objects and our concepts, using simple standard queries on a relational database.  ... 
dblp:conf/aiia/Rocco16 fatcat:tz6yo7tobrb3jcgdyzxltk4m74

A Survey on Data Collection for Machine Learning: a Big Data – AI Integration Perspective [article]

Yuji Roh, Geon Heo, Steven Euijong Whang
2019 arXiv   pre-print
Data collection is a major bottleneck in machine learning and an active research topic in multiple communities. There are largely two reasons data collection has recently become a critical issue.  ...  In this survey, we perform a comprehensive study of data collection from a data management point of view.  ...  The entity augmentation is performed by filling in missing values of attributes in some or all of the entities by matching multiple Web tables using schema matching.  ... 
arXiv:1811.03402v2 fatcat:wviufzo2p5dtrnfrbisgkzrpd4

End-to-End Entity Resolution for Big Data: A Survey [article]

Vassilis Christophides, Vasilis Efthymiou, Themis Palpanas, George Papadakis, Kostas Stefanidis
2020 arXiv   pre-print
indexing and matching methods in order to cope with more than one of the Big Data characteristics simultaneously.  ...  One of the most important tasks for improving data quality and the reliability of data analytics results is Entity Resolution (ER).  ...  propagating their similarity to neighbor entities via relations that will be matched in a next round.  ... 
arXiv:1905.06397v3 fatcat:rs2qoolz2jcppklriew5pjfefq

Deco

Aditya Ganesh Parameswaran, Hyunjung Park, Hector Garcia-Molina, Neoklis Polyzotis, Jennifer Widom
2012 Proceedings of the 21st ACM international conference on Information and knowledge management - CIKM '12  
introduced in the crowdsourcing environment.  ...  Specifically, declarative queries are posed over stored relational data as well as data computed on-demand from the crowd, and the underlying system orchestrates the computation of query answers.  ...  How does it deal with the latency of crowdsourcing services? How does it deal with the resolution of disagreement or uncertainty in answer tuples?  ... 
doi:10.1145/2396761.2398421 dblp:conf/cikm/ParameswaranPGPW12 fatcat:vtboeki5dzdijozsllyrxwniva

The Value of Paraphrase for Knowledge Base Predicates

Bingcong Xue, Sen Hu, Lei Zou, Jiashu Cheng
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
of machine mining and crowdsourcing.  ...  Collecting paraphrase for predicates in knowledge bases (KBs) is the key to comprehend the RDF triples in KBs.  ...  Get to the point: Summarization with pointer-generator networks.  ... 
doi:10.1609/aaai.v34i05.6475 fatcat:dwph5dwiuvcmtk5smlb7i2jscy

System Learning of User Interactions

Michael Kaschesky, Guillaume Bouchard, Stephane Gamard, Adrian Gschwend, Patrick Furrer, Reinhard Riedl
2012 Americas Conference on Information Systems  
The constant interaction with users provides a valuable data source that is used to improve human-computer interaction and for adapting to specific user preferences.  ...  Machine learning methods optimize semantic analysis and matching based on implicit and explicit feedback of users.  ...  Semantic matching Crowdsourcing for semantic Automating semantic (relational model learning) matching (tensor matching (active relational factorization) learning) Graphical user interfaces Adaptive layouts  ... 
dblp:conf/amcis/KascheskyBGGFR12 fatcat:z4lsxu36u5evfhzh775ylliuzq
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