Measuring Inconsistency in Probabilistic Knowledge Bases
By Matthias Thimm. 2009
50 citations recorded by the source corpus.
This paper develops an inconsistency measure on conditional probabilistic knowledge bases. The measure is based on fundamental principles for inconsistency measures and thus provides a solid theoretical framework for the treatment of inconsistencies in probabilistic expert systems. We illustrate its usefulness and immediate application on several examples and present some formal results. Building on this measure we use the Shapley value---a well-known solution for coalition games---to define a sophisticated indicator that is not only able to measure inconsistencies but to reveal the causes of inconsistencies in the knowledge base. Altogether these tools guide the knowledge engineer in his aim to restore consistency and therefore enable him to build a consistent and usable knowledge base that can be employed in probabilistic expert systems.
Subfields: Artificial Intelligence, Probabilistic & Bayesian Methods, Knowledge Graphs & Representation
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Hinrich Schütze
- Yoav Goldberg
- Mohit Bansal
- Peter Clark
- Eduard H. Hovy
- Yonatan Belinkov
- Yejin Choi
- Oyvind Tafjord
In Probabilistic & Bayesian Methods
- Hinrich Schütze
- Nora Kassner
- Oyvind Tafjord
- Peter Clark
- Eduard H. Hovy
- Matthias Thimm
- Yoav Goldberg
- Abhilasha Ravichander
In Knowledge Graphs & Representation
- Hinrich Schütze
- Nora Kassner
- Peter Clark
- Oyvind Tafjord
- Eduard H. Hovy
- Matthias Thimm
- Yoav Goldberg
- Yanai Elazar
Citations in the corpus
- Measuring and Improving Consistency in Pretrained Language Models (2021, background): “Other work aims to quantify the degree to which KBs are inconsistent and detects inconsistent statements (Thimm, 2009; Muiño, 2011; Thimm, 2013).”
- Measuring and repairing inconsistency in probabilistic knowledge bases (2011, unknown): “, that in [17] and ours) let us consider a small fragment of ΦCB , given by the following subset of rules:”
- Enriching a Model's Notion of Belief using a Persistent Memory (2021, methodology): “In the area of formal knowledge-bases (KBs), efficient algorithms have been developed for detecting, measuring, and resolving inconsistency (Hansen and Jaumard, 2000; Andersen and Pretolani, 2001; Thimm, 2009; Muiño, 2011; Thimm, 2013).”
- Inconsistency measures for probabilistic logics (2013, methodology): “This approach can also be applied for inconsistency measures for probabilistic logics as has been done for the measure I 1 in (Thimm, 2009).”