The DOI matches its Crossref record.
Uncertainty in Knowledge Provenance
Overview
Integrity signals
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Cites
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Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Knowledge Provenance has been proposed to annotate the reliability of information extracted from web sources based on who created the assertion, how much the creator can be trusted, and what the information depends on.
“Knowledge Provenance (KP) has been proposed to create an approach to annotate the reliability of information extracted from web sources based on who created the assertion, how much the creator can be trusted, and what the information depends on.”
From Provenance-driven nanopublications: representing source lineage and trust networks for multi-source assertions (2025) · cites this paper as [12]
The PROV-K ontology is built upon the PROV Ontology (PROV-O) and is grounded in the literature defining knowledge provenance.
“The PROV-K ontology is built upon the PROV Ontology (PROV-O) and is grounded in the literature defining knowledge provenance [11][12][13].”
From Provenance-driven nanopublications: representing source lineage and trust networks for multi-source assertions (2025) · cites this paper as [13]
Knowledge Provenance has been proposed to annotate the reliability of information extracted from web sources based on who created the assertion, how much the creator can be trusted, and what the information depends on.
“Knowledge Provenance (KP) has been proposed to create an approach to annotate the reliability of information extracted from web sources based on who created the assertion, how much the creator can be trusted, and what the information depends on.”
From Provenance-driven nanopublications: representing source lineage and trust networks for multi-source assertions (2025) · cites this paper as [13]
The PROV-K ontology is built upon the PROV Ontology (PROV-O) and is grounded in the literature defining knowledge provenance.
“The PROV-K ontology is built upon the PROV Ontology (PROV-O) and is grounded in the literature defining knowledge provenance [11][12][13].”
From Provenance-driven nanopublications: representing source lineage and trust networks for multi-source assertions (2025) · cites this paper as [12]
PROV-K follows the theoretical guidelines provided by the Static KP ontology while integrating some elements from the Dynamic KP, such as timestamps for truth values and trust relationships.
“The PROV-K follows the theoretical guidelines provided by the Static KP ontology [11] while integrating some elements from the Dynamic KP, such as timestamps for truth values and trust relationships [12].”
From Provenance-driven nanopublications: representing source lineage and trust networks for multi-source assertions (2025) · cites this paper as [12]
PROV-K includes the concepts of assigned certainty degree and certainty degree, originally defined in the Uncertainty-oriented KP.
“We also include the concepts of assigned certainty degree and certainty degree, originally defined in the Uncertainty-oriented KP [13].”
From Provenance-driven nanopublications: representing source lineage and trust networks for multi-source assertions (2025) · cites this paper as [13]
Citations
Cites
No references could be resolved yet.
Research works printed but not linked: 14
- Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Scientific American (May 2001) · DOI
- Bhatnager, R.K., Kanal, R.: Handling Uncertain Information: A Review of Numeric and Non-numeric Methods. In: Kanal, L., Lemmer, J.F. (eds.) Uncertainty in Artificial Intelligence, Elsevier Science Publishers, Amsterdam (1986)
- Blaze, M., Feigenbaum, J., Lacy, J.: Decentralized Trust Management. In: Proceedings of IEEE Conference on Security and Privacy (May 1996) · DOI
- Chu, Y.: Trust Management for the World Wide Web, Master Thesis, MIT (1997)
- Gil, Y., Ratnakar, V.: Trusting information sources one citizen at a time. In: Horrocks, I., Hendler, J. (eds.) ISWC 2002. LNCS, vol. 2342, p. 162. Springer, Heidelberg (2002) · DOI
- Golbeck, J., Hendler, J., Parsia, B.: Trust Networks on the Semantic Web. University of Maryland, College Park (2002) · DOI
- Herrmann, P.: Trust-Based Protection of Software Component Users and Designers. In: Nixon, P., Terzis, S. (eds.) iTrust 2003. LNCS, vol. 2692, pp. 75–90. Springer, Heidelberg (2003) · DOI
- Jøsang, A.: A Logic for Uncertain Probabilities. International Journal of Uncertainty, Fuzziness, and Knowledge-Based Systems 9(3), 279–311 (2001) · DOI
- Khare, R., Rifkin, A.: Weaving and Web of Trust. World Wide Web Journal 2(3), 77–112 (1997)
- Kinateder, M., Rothermel, K.: Architecture and Algorithms for a Distributed Reputation System. In: Nixon, P., Terzis, S. (eds.) iTrust 2003. LNCS, vol. 2692, pp. 1–16. Springer, Heidelberg (2003) · DOI
- MacKay, D.J.C.: Information Theory, Inference, and Learning Algorithm. Cambridge University Press, Cambridge (2003)
- Richardson, M., Agrawal, R., Domingos, P.: Trust management for the semantic web. In: Fensel, D., Sycara, K., Mylopoulos, J. (eds.) ISWC 2003. LNCS, vol. 2870, pp. 351–368. Springer, Heidelberg (2003) · DOI
- Shannon, C.E.: A Mathematical Theory of Communication. The Bell System Technical Journal 27, 379–423, 623–656 (1948) · DOI · Paper page
- Twigg, A.: A subjective approach to routing in P2P and ad hoc networks. In: Nixon, P., Terzis, S. (eds.) iTrust 2003. LNCS, vol. 2692, pp. 225–238. Springer, Heidelberg (2003) · DOI
Cited by
Sorted by citations
Menotti, L., Marchesin, S., Giachelle, F., & Silvello, G. (2025) · International Journal on Digital Libraries · doi:10.1007/s00799-025-00431-x · Cited by 5
Metadata
- Authors
- Huang, J., & Fox, M. S.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2004
- Pages
- 372-387
- ISSN
- 0302-9743
- 1611-3349
- Cited by
- 15
- References
- 0
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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