. .. Contributions, 134 6.1.1 Incorporating semantic dependencies among values to improve value confidence estimation, p.134

, Considering semantic dependencies among values during the truth estimation phase, p.134

, Incorporating dependencies among data items to improve value confidence estimation, p.135

, Use-case study on real-world data, p.135

. , Synthetic datasets, real-world datasets and source code

. , 6.3.1 Application to multi-truth scenario, p.137

&. Static,

. , Considering OWA when generating partial order of values

. , Extracting a priori knowledge from multiple ontologies

. .. Graphical-user-interface, , p.139

A. References-ageno, P. R. Comas, A. M. Naderi, H. Rodríguez, and J. Turmo, , 2013.

, The talp participation at tac-kbp 2013, Proceedings of the 6th Text Analysis Conference

R. Agrawal, T. Imielí-nski, and A. Swami, Mining association rules between sets of items in large databases, ACM SIGMOD Record, vol.22, issue.2, pp.207-216, 1993.

A. V. Aho, M. R. Garey, and J. D. Ullman, The transitive reduction of a directed graph, SIAM Journal on Computing, vol.1, issue.2, pp.131-137, 1972.

H. T. Al-feel, M. Koutb, and H. Suoror, Semantic web on scope: A new architectural model for the semantic web, Journal of Computer Science, vol.4, issue.7, pp.613-324, 2008.

H. Allcott and M. Gentzkow, Social media and fake news in the 2016 election, Journal of Economic Perspectives, vol.31, issue.2, pp.211-247, 2017.

P. Anokhin and A. Motro, Data integration: Inconsistency detection and resolution based on source properties, Proceedings of the International Workshop on Foundations of Models for Information Integration, 2001.

M. Ashburner, C. A. Ball, J. A. Blake, D. Botstein, H. Butler et al., Gene ontology: tool for the unification of biology, Nature genetics, vol.25, issue.1, pp.25-29, 2000.

S. Auer, C. Bizer, G. Kobilarov, J. Lehmann, R. Cyganiak et al., Dbpedia: A nucleus for a web of open data. The Semantic Web, 2007.

F. Baader, D. Calvanese, D. Mcguinness, P. Patel-schneider, and D. Nardi, The description logic handbook: Theory, implementation and applicaReferences tions, 2003.

J. Bailey, F. Bry, T. Furche, and S. Schaffert, Web and semantic web query languages: A survey, Proceedings of the 1st international conference on Reasoning Web, pp.35-133, 2005.

M. Barati, Q. Bai, and Q. Liu, Mining semantic association rules from rdf data. Knowledge-Based Systems, vol.133, pp.183-196, 2017.

D. Beckett, RDF/XML Syntax Specification (Revised). World Wide Web Consortium, 2004.

T. Berners-lee, Uniform resource identifiers (uri): Generic syntax, 1998.

T. Berners-lee, J. Hendler, and O. Lassila, The semantic web, Scientific american, vol.284, issue.5, pp.34-43, 2001.

L. Berti-Équille and J. Borge-holthoefer, Veracity of data: From truth discovery computation algorithms to models of misinformation dynamics, 2015.

L. Berti-equille, A. D. Sarma, . Xin, M. Dong, A. Srivastava et al., Sailing the information ocean with awareness of currents: Discovery and application of source dependence, Proceedings of the Biennial Conference on Innovative Data Systems Research, pp.1-6, 2009.
URL : https://hal.archives-ouvertes.fr/hal-01856029

C. Bizer, T. Heath, and T. Berners-lee, Linked data-the story so far, International journal on semantic web and information systems, vol.5, issue.3, pp.1-22, 2009.

L. Blanco, V. Crescenzi, P. Merialdo, and P. Papotti, Probabilistic Models to Reconcile Complex Data from Inaccurate Data Sources, Proceedings of the 22nd International Conference on Advanced Information Systems Engineering, pp.83-97, 2010.

J. Bleiholder and F. Naumann, Data fusion, ACM Computing Surveys (CSUR, pp.1-41, 2009.

C. Böhm, F. Naumann, Z. Abedjan, D. Fenz, T. Grütze et al., Profiling linked open data with prolod. Data Engineering Workshops (ICDEW), IEEE 26th International Conference on, pp.175-178, 2010.

H. Boley, Relationships between logic programming and rdf. Proceedings of the 6th Pacific Rim International Conference on Artificial Intelligence, pp.201-218, 2000.

A. Bordes, N. Usunier, A. Garcia-duran, J. Weston, and O. Yakhnenko, Translating embeddings for modeling multi-relational data. AdReferences vances in neural information processing systems, pp.2787-2795, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00920777

D. Brickley and R. V. Guha, RDF vocabulary description language 1.0: RDF schema (W3C Recommendation), vol.3, 2004.

P. Buche, C. Dervin, O. Haemmerle, and R. Thomopoulos, Fuzzy querying of incomplete, imprecise, and heterogeneously structured data in the relational model using ontologies and rules, IEEE Transactions on Fuzzy Systems, vol.13, issue.3, pp.373-383, 2005.

M. Buffa, C. F. Zucker, T. Bergeron, and H. Aouzal, Semantic web technologies for improving remote visits of museums, using a mobile robot, Proceedings of the ISWC 2016 Posters & Demonstrations Track colocated with 15th International Semantic Web Conference, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01400924

Y. Chi, Y. Yang, and R. R. Muntz, Hybridtreeminer: An efficient algorithm for mining frequent rooted trees and free trees using canonical forms, Proceedings of the 16th International Conference on Scientific and Statistical Database Management, pp.11-20, 2004.

D. Amato, C. Staab, S. Tettamanzi, A. G. Minh, T. D. Gandon et al., Ontology enrichment by discovering multi-relational association rules from ontological knowledge bases, Proceedings of the 31st Annual ACM Symposium on Applied Computing, pp.333-338, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01322947

B. A. Davey and H. A. Priestley, Introduction to lattices and order, 1990.

J. David, Association rule ontology matching approach, International Journal on Semantic Web and Information Systems, vol.3, issue.2, pp.27-49, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00461292

J. David, F. Guillet, R. Gras, and H. Briand, Conceptual hierarchies matching: an approach based on discovery of implication rules between concepts, Proceedings of the 17th biennial European Conference on Artificial Intelligence, vol.6, pp.357-361, 2006.
URL : https://hal.archives-ouvertes.fr/hal-00461462

J. De-bruijn, F. Martin-recuerda, D. Manov, and M. Ehrig, D4. 2.1 state-of-the-art-survey on ontology merging and aligning v1, SEKT Project deliverable D, vol.4, pp.2-3, 2004.

X. Dong, E. Gabrilovich, G. Heitz, W. Horn, N. Lao et al., Knowledge vault: A web-scale approach to probabilistic knowledge fusion, Proceedings of the 20th ACM SIGKDD international conference on Knowledge Discovery and Data mining, pp.601-610, 2014.

R. Dong, X. L. Berti-equille, L. Hu, Y. Srivastava, and D. , Global detection of complex copying relationships between sources, Proceedings of the VLDB Endowment, vol.3, pp.1358-1369, 2010.

X. L. Dong, L. Berti-equille, and D. Srivastava, Integrating conflicting data: the role of source dependence, Proceedings of the VLDB Endowment, vol.2, pp.550-561, 2009.
URL : https://hal.archives-ouvertes.fr/hal-01855870

X. L. Dong, L. Berti-equille, and D. Srivastava, Truth Discovery and Copying Detection in a Dynamic World, Proceedings of the VLDB Endowment, vol.2, pp.562-573, 2009.
URL : https://hal.archives-ouvertes.fr/hal-01855862

X. L. Dong, E. Gabrilovich, G. Heitz, W. Horn, K. Murphy et al., From data fusion to knowledge fusion, Proceedings of the VLDB Endowment, vol.7, pp.881-892, 2014.

X. L. Dong, E. Gabrilovich, K. Murphy, V. Dang, W. Horn et al., Knowledge-based trust: Estimating the trustworthiness of web sources, Proceedings of the VLDB Endowment, vol.8, pp.938-949, 2015.

X. L. Dong and F. Naumann, Data fusion: resolving data conflicts for integration, Proceedings of the VLDB Endowment, vol.2, pp.1654-1655, 2009.

B. Eiermann, P. B. Rahmner, S. Korkmaz, C. Landberg, B. Lilja et al., , 2010.

, Knowledge bases for clinical decision support in drug prescribingdevelopment, quality assurance, management, integration, implementation and evaluation of clinical value. In Decision support systems

J. Euzenat and P. Shvaiko, Ontology matching, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00817824

F. Feldman, Leibniz and leibniz'law, The Philosophical Review, vol.79, issue.4, pp.510-522, 1970.
DOI : 10.2307/2184291

J. Fürnkranz and T. Kliegr, A brief overview of rule learning. International Symposium on Rules and Rule Markup Languages for the Semantic Web, pp.54-69, 2015.

L. Galárraga, Applications of rule mining in knowledge bases, Proceedings of the 7th Workshop on Ph.D Students, pp.45-49, 2014.

L. Galárraga, Actes des 31 e Conférence sur la Gestion de Données, 2015.

L. Galárraga and F. M. Suchanek, Towards a numeric rule mining language, Proceedings of Automated Knowledge Base Construction workshop, 2014.

L. Galárraga, C. Teflioudi, K. Hose, and F. M. Suchanek, Fast rule mining in ontological knowledge bases with amie+, The VLDB Journal, vol.24, issue.6, pp.707-730, 2015.

L. A. Galárraga, C. Teflioudi, K. Hose, and F. Suchanek, Amie: association rule mining under incomplete evidence in ontological knowledge bases, Proceedings of the 22nd international conference on World Wide Web, pp.413-422, 2013.

A. Galland, S. Abiteboul, A. Marian, and P. Senellart, Corroborating information from disagreeing views, Proceedings of the 3rd ACM international conference on Web Search and Data Mining, pp.131-140, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00429546

J. Gao, Q. Li, B. Zhao, W. Fan, and J. Han, Truth discovery and crowdsourcing aggregation: A unified perspective, Proceedings of the VLDB Endowment, vol.8, pp.2048-2049, 2015.

L. Getoor and C. P. Diehl, Link mining: A survey, SIGKDD Explor. Newsl, vol.7, issue.2, pp.3-12, 2005.

B. Goethals and J. V. Bussche, Relational association rules: Getting warmer, Proceedings of the ESF Exploratory Workshop on Pattern Detection and Discovery, pp.125-139, 2002.

W. O. Group, OWL 2 web ontology language. document overview, 2012.

T. R. Gruber, A translation approach to portable ontology specifications. Knowledge acquisition, vol.5, pp.199-220, 1993.

N. Guarino, Formal ontology in information systems, Proceedings of the first international conference (fois'98), vol.46, 1998.

N. Guarino, D. Oberle, and S. Staab, What is an ontology?, Handbook on ontologies, pp.1-17, 2009.

A. Guzman-arenas, A. Cuevas, and A. Jimenez, The centroid or consensus of a set of objects with qualitative attributes, Expert Systems with Applications, vol.38, issue.5, pp.4908-4919, 2011.

S. Harispe, Knowledge-based semantic measures: From theory to applications, 2014.
URL : https://hal.archives-ouvertes.fr/tel-01175611

S. Harispe, A. Imoussaten, F. Trousset, and J. Montmain, On the consideration of a bring-to-mind model for computing the information content of concepts defined into ontologies, Proceedings of the 2015 IEEE International Conference on Fuzzy Systems, pp.1-8, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01485047

S. References-harispe, S. Ranwez, S. Janaqi, and J. Montmain, The semantic measures library and toolkit: fast computation of semantic similarity and relatedness using biomedical ontologies, Bioinformatics, vol.30, issue.5, pp.740-742, 2014.

S. Harispe, S. Ranwez, S. Janaqi, and J. Montmain, Semantic similarity from natural language and ontology analysis, Synthesis Lectures on Human Language Technologies, vol.8, issue.1, pp.1-254, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01288380

I. Horrocks, B. Parsia, P. Patel-schneider, and J. Hendler, Semantic web architecture: Stack or two towers?, Proceedings of the 3rd International Workshop on Principles and Practice of Semantic Web Reasoning, pp.37-41, 2005.

P. Jean, S. Harispe, S. Ranwez, P. Bellot, and J. Montmain, Uncertainty detection in natural language: a probabilistic model, Proceedings of the 6th International Conference on Web Intelligence, Mining and Semantics, vol.10, pp.1-10, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01484994

D. Jensen, Statistical challenges to inductive inference in linked data, Proceedings of the 2nd International Conference on Artificial Intelligence and Statistics, 1999.

S. Jiang, D. Lowd, and D. Dou, Learning to refine an automatically extracted knowledge base using markov logic, Proceedings of IEEE 12th International Conference on the Data Mining, pp.912-917, 2012.

C. Joslyn and E. Hogan, Order metrics for semantic knowledge systems, Proceedings of the 5th International Conference on Hybrid Artificial Intelligence Systems, pp.399-409, 2010.

Y. Kalfoglou and M. Schorlemmer, Ontology mapping: The state of the art, Knowl. Eng. Rev, vol.18, issue.1, pp.1-31, 2003.

A. Kiryakov, Semantic Web Technologies: trends and research in ontology-based systems, pp.115-138, 2006.

J. M. Kleinberg, Authoritative Sources in a Hyperlinked Environment, Journal of the ACM, vol.46, pp.668-677, 1999.

T. Knap, J. Michelfeit, and M. Necask`ynecask`-necask`y, Linked open data aggregation: Conflict resolution and aggregate quality, Proceedings of the IEEE 36th Annual Conference Workshops on Computer Software and Applications, pp.106-111, 2012.

A. Kosmopoulos, I. Partalas, E. Gaussier, G. Paliouras, and I. Androutsopoulos, Evaluation measures for hierarchical classification: a References unified view and novel approaches, Data Mining and Knowledge Discovery, vol.29, issue.3, pp.820-865, 2015.

M. Krotofil, J. Larsen, and D. Gollmann, The process matters: Ensuring data veracity in cyber-physical systems, Proceedings of the 10th ACM Symposium on Information, Computer and Communications Security, pp.133-144, 2015.

M. Kuramochi and G. Karypis, Frequent subgraph discovery. Data Mining, Proceedings IEEE international conference on, pp.313-320, 2001.

N. Lao, T. Mitchell, and W. W. Cohen, Random walk inference and learning in a large scale knowledge base, Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp.529-539, 2011.

D. M. Lazer, M. A. Baum, Y. Benkler, A. J. Berinsky, K. M. Greenhill et al., The science of fake news, Science, vol.359, issue.6380, pp.1094-1096, 2018.

J. Lehmann and . Völker, Perspectives on ontology learning, vol.18, 2014.

C. Li, V. S. Sheng, L. Jiang, and H. Li, Noise filtering to improve data and model quality for crowdsourcing. Knowledge-Based Systems, vol.107, pp.96-103, 2016.

H. Li, B. Zhao, and A. Fuxman, The wisdom of minority: Discovering and targeting the right group of workers for crowdsourcing, Proceedings of the 23rd international conference on World Wide Web, pp.165-176, 2014.

Q. Li, Y. Li, J. Gao, L. Su, B. Zhao et al., A confidence-aware approach for truth discovery on long-tail data, Proceedings of the VLDB Endowment, vol.8, pp.425-436, 2014.

Q. Li, Y. Li, J. Gao, B. Zhao, W. Fan et al., Resolving conflicts in heterogeneous data by truth discovery and source reliability estimation, Proceedings of the 2014 ACM SIGMOD international conference on Management of Data, pp.1187-1198, 2014.

Y. Li, J. Gao, C. Meng, Q. Li, L. Su et al., A survey on truth discovery, SIGKDD Explor. Newsl, vol.17, issue.2, pp.1-16, 2015.

Y. Li, Q. Li, J. Gao, L. Su, B. Zhao et al., Conflicts to harmony: A framework for resolving conflicts in heterogeneous data by truth discovery, IEEE Transactions on Knowledge and Data Engineering, vol.28, issue.8, pp.1986-1999, 2016.

D. References-lin, An information-theoretic definition of similarity, Proceedings of the 15th International Conference of Machine Learning, vol.98, pp.296-304, 1998.

F. Ma, Y. Li, Q. Li, M. Qiu, J. Gao et al., Faitcrowd: Fine grained truth discovery for crowdsourced data aggregation, Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp.745-754, 2015.

O. Maimon and L. Rokach, Data mining and knowledge discovery handbook, vol.2, 2005.

F. Manola and E. Miller, RDF primer. W3C Recommendation, 2004.

, Rdf primer. World Wide Web Consortium, 2004.

P. N. Mendes, M. Jakob, A. García-silva, and C. Bizer, Dbpedia spotlight: shedding light on the web of documents, Proceedings of the 7th International Conference on Semantic Systems, pp.1-8, 2011.

C. Meng, W. Jiang, Y. Li, J. Gao, L. Su et al., Truth discovery on crowd sensing of correlated entities, Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems, pp.169-182, 2015.

M. Minsky, A framework for representing knowledge, 1974.

B. Motik, B. C. Grau, I. Horrocks, Z. Wu, A. Fokoue et al., Owl 2 web ontology language: Profiles, vol.27, 2008.

S. Muggleton, Inverse entailment and progol. New generation computing, vol.13, pp.245-286, 1995.

S. Muggleton, Learning from positive data, International Conference on Inductive Logic Programming, pp.358-376, 1996.

S. Mukherjee, G. Weikum, and C. Danescu-niculescu-mizil, People on drugs: credibility of user statements in health communities, Proceedings of the 20th ACM SIGKDD international conference on Knowledge Discovery and Data mining, pp.65-74, 2014.

N. Nakashole and T. M. Mitchell, Language-aware truth assessment of fact candidates, Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, vol.1, pp.1009-1019, 2014.

V. Nebot and R. Berlanga, Finding association rules in semantic web data. Knowledge-Based System, vol.25, pp.51-62, 2012.

Y. Nenov, R. Piro, B. Motik, I. Horrocks, Z. Wu et al., Rdfox: A highly-scalable rdf store, Proceedings of the 14th International References Semantic Web Conference, pp.3-20, 2015.

M. Nickel, K. Murphy, V. Tresp, and E. Gabrilovich, A review of relational machine learning for knowledge graphs, Proceedings of the IEEE, vol.104, issue.1, pp.11-33, 2016.

M. Nickel, V. Tresp, and H. Kriegel, A three-way model for collective learning on multi-relational data, ICML, vol.11, pp.809-816, 2011.

R. S. Nickerson, Confirmation bias: A ubiquitous phenomenon in many guises, Review of general psychology, vol.2, issue.2, p.175, 1998.

A. G. Nuzzolese, V. Presutti, A. Gangemi, A. Musetti, and P. Ciancarini, Aemoo: exploring knowledge on the web, Proceedings of Web Science, pp.272-275, 2013.

C. Ordonez and K. Zhao, Evaluating association rules and decision trees to predict multiple target attributes, vol.15, pp.173-192, 2011.

R. W. Ouyang, L. M. Kaplan, A. Toniolo, M. Srivastava, and T. J. Norman, Aggregating crowdsourced quantitative claims: Additive and multiplicative models, IEEE Transactions on Knowledge and Data Engineering, vol.28, issue.7, pp.1621-1634, 2016.

R. W. Ouyang, M. Srivastava, A. Toniolo, and T. J. Norman, Truth discovery in crowdsourced detection of spatial events, IEEE Transactions on Knowledge and Data Engineering, vol.28, issue.4, pp.1047-1060, 2016.

E. Pariser, The filter bubble: What the internet is hiding from you, 2011.

J. Pasternack and D. Roth, Knowing what to believe (when you already know something), Proceedings of the 23rd International Conference on Computational Linguistics, pp.877-885, 2010.

J. Pasternack and D. Roth, Making better informed trust decisions with generalized fact-finding, Proceedings of the 22nd International Joint Conference on Artificial Intelligence, pp.2324-2329, 2011.

J. Pasternack and D. Roth, Latent credibility analysis, Proceedings of the 22nd international conference on World Wide Web, pp.1009-1020, 2013.

C. Perez, Technological revolutions and techno-economic paradigms, Cambridge journal of economics, vol.34, issue.1, pp.185-202, 2010.

S. Plous, The psychology of judgment and decision making, 1993.

R. Pochampally, A. Das-sarma, X. L. Dong, A. Meliou, D. Srivastava et al., Fusing data with correlations, Proceedings of the 2014 ACM SIGMOD international conference on Management of Data, pp.433-444, 2014.

J. Pujara, H. Miao, L. Getoor, and W. Cohen, Knowledge graph identification, Proceedings of the 12th International Semantic Web Conference, pp.542-557, 2013.

G. Qi, C. C. Aggarwal, J. Han, and T. Huang, Mining collective intelligence in diverse groups, Proceedings of the 22nd International Conference on World Wide Web, WWW '13, pp.1041-1052, 2013.

Q. K. Quboa and M. Saraee, A state-of-the-art survey on semantic web mining, Intelligent Information Management, vol.5, issue.01, pp.1-10, 2013.

J. R. Quinlan, Learning logical definitions from relations, Machine learning, vol.5, issue.3, pp.239-266, 1990.

I. A. Richards and C. K. Ogden, The meaning of meaning: a study of the influence of language upon thought and of the science of symbolism, Routledge and Kegan Paul Ltd, 1923.

P. Ristoski and H. Paulheim, Semantic web in data mining and knowledge discovery: A comprehensive survey. Web semantics: science, services and agents on the World Wide Web, vol.36, pp.1-22, 2016.

H. Robbins, An empirical bayes approach to statistics, Contributions to the Theory of Statistics, vol.1, pp.157-163, 1956.

O. R. Rocha, C. F. Zucker, and A. Giboin, Extraction of relevant resources and questions from dbpedia to automatically generate quizzes on specific domains, Proceedings of the International Conference on Intelligent Tutoring Systems, pp.380-385, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01811490

M. Samadi, P. Talukdar, M. Veloso, and M. Blum, Claimeval: Integrated and flexible framework for claim evaluation using credibility of sources, Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, pp.222-228, 2016.

D. Sánchez and M. Batet, Semantic similarity estimation in the biomedical domain: An ontology-based information-theoretic perspective, Journal of biomedical informatics, vol.44, issue.5, pp.749-759, 2011.

M. Schmachtenberg, C. Bizer, and H. Paulheim, Adoption of the linked data best practices in different topical domains, Proceedings of the 13th International Semantic Web Conference, pp.245-260, 2014.

S. Schoenmackers, O. Etzioni, D. S. Weld, and J. Davis, Learning firstReferences order horn clauses from web text, Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pp.1088-1098, 2010.

N. Seco, T. Veale, and J. Hayes, An intrinsic information content metric for semantic similarity in wordnet, Proceedings of the 16th European Conference on Artificial Intelligence, pp.1089-1090, 2004.

G. Shafer, A mathematical theory of evidence, vol.1, 1976.

P. Smyth, U. M. Fayyad, M. C. Burl, P. Perona, and P. Baldi, Inferring ground truth from subjective labelling of venus images, Advances in neural information processing systems, pp.1085-1092, 1995.

S. Soderland, J. Gilmer, R. Bart, O. Etzioni, and D. S. Weld, Open information extraction to kbp relations in 3 hours, Proceedings of the 6th Text Analysis Conference, 2013.

J. Sowa, Conceptual structures: Information processing in mind and machine, 1984.

K. A. Spackman, K. E. Campbell, and R. A. Côté, Snomed rt: a reference terminology for health care, Proceedings of the American Medical Informatics Association Annual fall Symposium, p.640, 1997.

S. Staab and R. Studer, Handbook on ontologies-second edition, 2009.

L. Su, Q. Li, S. Hu, S. Wang, J. Gao et al., Generalized decision aggregation in distributed sensing systems, Proceedings of the 2014 IEEE 35th Real-Time Systems Symposium, pp.1-10, 2014.

G. Sudeepthi, G. Anuradha, and M. S. Babu, A survey on semantic web search engine, International Journal of Computer Science Issues, vol.9, issue.2, pp.241-245, 2012.

J. Surowiecki, The wisdom of crowds: Why the many are smarter than the few and how collective wisdom shapes business, economies, societies and nations, 2004.

T. P. Tanon, D. Stepanova, S. Razniewski, P. Mirza, and G. Weikum, , 2017.

, Completeness-aware rule learning from knowledge graphs, Proceedings of the 16th International Semantic Web Conference, pp.507-525

S. Ventura and J. M. Luna, Quality measures in pattern mining, pp.27-44, 2016.

J. Völker, D. Fleischhacker, and H. Stuckenschmidt, Automatic acquisition of class disjointness, Web Semant, vol.35, issue.P2, pp.124-139, 2015.

D. A. References-waguih and L. Berti-equille, Truth discovery algorithms: An experimental evaluation, 2014.

M. Wan, X. Chen, L. Kaplan, J. Han, J. Gao et al., From truth discovery to trustworthy opinion discovery: An uncertainty-aware quantitative modeling approach, Proceedings of the 22th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016.

D. Wang, T. Abdelzaher, and L. Kaplan, Social sensing: building reliable systems on unreliable data, 2015.

D. Wang, T. Abdelzaher, L. Kaplan, R. Ganti, S. Hu et al., Exploitation of physical constraints for reliable social sensing, Proceedings of the 2013 IEEE 34th Real-Time Systems Symposium, pp.212-223, 2013.

D. Wang, L. Kaplan, H. Le, and T. Abdelzaher, On truth discovery in social sensing: A maximum likelihood estimation approach, Proceedings of the 11th International Conference on Information Processing in Sensor Networks, pp.233-244, 2012.

S. Wang, L. Su, S. Li, S. Hu, T. Amin et al., Scalable social sensing of interdependent phenomena, Proceedings of the 14th International Conference on Information Processing in Sensor Networks, pp.202-213, 2015.

S. Wang, D. Wang, L. Su, L. Kaplan, and T. F. Abdelzaher, Towards cyber-physical systems in social spaces: The data reliability challenge, Proceedings of the 2014 IEEE 35th Real-Time Systems Symposium, pp.74-85, 2014.

X. Wang, Q. Z. Sheng, X. S. Fang, L. Yao, X. Xu et al., An integrated bayesian approach for effective multi-truth discovery, Proceedings of the 24th ACM International on Conference on Information and Knowledge Management, pp.493-502, 2015.

X. Wang, Q. Z. Sheng, L. Yao, X. Li, X. S. Fang et al., Empowering truth discovery with multi-truth prediction, Proceedings of the 25th ACM International on Conference on Information and Knowledge Management, pp.881-890, 2016.

Z. Wang and J. Li, Rdf2rules: Learning rules from RDF knowledge bases by mining frequent predicate cycles, 2015.

J. Whitehill, T. Wu, J. Bergsma, J. R. Movellan, and P. L. Ruvolo, Whose vote should count more: Optimal integration of labels from labelers of unknown expertise, Advances in neural information processing systems, pp.2035-2043, 2009.

X. Yin, J. Han, and P. S. Yu, Truth discovery with multiple conflicting information providers on the web, IEEE Transactions on Knowledge and Data Engineering, vol.20, issue.6, pp.796-808, 2008.

X. Yin and W. Tan, Semi-supervised truth discovery, Proceedings of the 20th international conference on World Wide Web, pp.217-226, 2011.

D. Yu, H. Huang, T. Cassidy, H. Ji, C. Wang et al., The wisdom of minority: Unsupervised slot filling validation based on multi-dimensional truth-finding, Proceedings of the 25th International Conference on Computational Linguistics, pp.1567-1578, 2014.

Q. Zeng, J. M. Patel, and D. Page, Quickfoil: Scalable inductive logic programming, Proceedings of the VLDB Endowment, vol.8, pp.197-208, 2014.

B. Zhao and J. Han, A probabilistic model for estimating real-valued truth from conflicting sources, Proceedings of the 10th International Workshop on Quality in DataBases, 2012.

B. Zhao, B. I. Rubinstein, J. Gemmell, and J. Han, A bayesian approach to discovering truth from conflicting sources for data integration, Proceedings of the VLDB Endowment, vol.5, pp.550-561, 2012.