Trust-based Revision for Expressive Web Syndication

Golbeck, Jennifer; Halaschek-Wiener, Christian

doi:10.1093/logcom/exn045

Cited by 14 publications

(6 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The authors in [8] proposes a kernel revision operator and give two algorithms to define specific kernel revision operators. The authors in [9] develop a revision operator based on a trust-based incision function. The other type of formula-based approaches is to find maximally satisfiable terminologies.…”

Section: Related Workmentioning

confidence: 99%

“…Similarly, there also exist many approaches for ontology revision. Most works, such as those reported in [8], [9], on ontology revision are based on the AGM theory [10]. An important principle of these works is minimal change, i.e., a revision approach should delete information from the original ontology as little as possible.…”

Section: Introductionmentioning

confidence: 99%

“…In [8], a kernel revision operator is proposed based on an incision function that is used to select axioms from each MIPS. In [9], the authors propose a revision operator based on a trust-based incision function which aims to find minimal set of axioms that need to be removed to render a terminology logically correct. Nevertheless, the delete operation may lead to the loss of valuable information in an ontology.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Graph-based approaches to debugging and revision of terminologies in DL-Lite

Zhang

et al. 2016

Knowledge-Based Systems

View full text Add to dashboard Cite

In this paper, we deal with the problem of debugging and revision of incoherent terminologies. Ontology debugging aims to provide the explanation of the causes of incoherence and ontology revision aims to eliminate the incoherence. For this purpose, we propose the graph-based approaches to deal with the debugging and revision of terminologies for a family of lightweight ontology languages, DL-Lite. First of all, we transform DL-Lite ontologies to graphs. To deal with the problem of ontology debugging, we calculate the minimal incoherence-preserving subsets (MIPS) of an ontology by computing the minimal incoherence-preserving path-pairs (MIPP) based on the transformed graph. To deal with the problem of ontology revision, we propose the notion of revision state which separates the terminology of an ontology into two disjoint sets: the set of wanted axioms and the set of unwanted axioms. We further define a revision operator based on the revision state. Afterwards, two revision algorithms are proposed to instantiate the revision operator: one is based on a scoring function, and the other one is based on a hitting set tree. We implement these algorithms and conduct experiments of ontology debugging and ontology revision on several adapted real ontologies. The experimental results of ontology debugging show that our approach of calculating MIPS based on graph is efficient and outperforms the state of the art. The experimental results of ontology revision show that the algorithm based on a scoring function is more efficient than the algorithm based on a hitting set tree.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Graph-based approaches to debugging and revision of terminologies in DL-Lite

Zhang

et al. 2016

Knowledge-Based Systems

View full text Add to dashboard Cite

show abstract

“…Therefore, before using such knowledge bases, their conflicts should be resolved. Golbeck and Halaschek-Wiener (2009) present a belief revision algorithm for ontologies, which is based on trust degrees of information sources to remove conflicting statements from a knowledge base. However, as the authors point out, the proposed algorithm is not guaranteed to be optimal.…”

Section: Related Workmentioning

confidence: 99%

Reasoning with streamed uncertain information from unreliable sources

Arunkumar

Şensoy

Srivatsa

et al. 2015

Expert Systems with Applications

View full text Add to dashboard Cite

a b s t r a c tHumans or intelligent software agents are increasingly faced with the challenge of making decisions based on large volumes of streaming information from diverse sources. Decision makers must process the observed information by inferring additional information, estimating its reliability and orienting it for decision-making. In this paper, we propose a stream-reasoning framework that achieves all these goals. While information is streamed as unstructured reports (e.g., text in natural language) from unreliable sources, our framework first converts it into a structured form using Controlled English and then it derives some facts that are useful for decision-making, and estimates the trust in these facts. Lastly, various facts are fused based on their trustworthiness. This process is totally undertaken on streaming information resulting in new facts being inferred from incoming information which immediately goes through trust assessment framework and trust is propagated to the inferred fact. In this paper, we propose a comprehensive framework where unstructured reports are streamed from heterogeneous and potentially untrustworthy information sources. These reports are processed to extract valuable uncertain information, which is represented using controlled natural language and subjective logic. Additional information is inferred using deduction and abduction operations over subjective opinions derived from the reports. Before fusing extracted and inferred opinions, the framework estimates trustworthiness of these opinions, detects conflicts between them, and resolve these conflicts by analysing evidence about the reliability of their sources. Lastly, we describe an implementation of the framework using International Technology Alliance (ITA) assets (Information Fabric Services and Controlled English Fact Store) and present an experimental evaluation that quantifies the efficiency with respect to accuracy and overhead of the proposed framework.

show abstract

“…In contrast, paraconsistent reasoning, as applied here, limits the influence to inconsistencies to fragments of the knowledge base. An approach similar to ours, but based on belief revision is proposed in [7].…”

Section: Related Workmentioning

confidence: 99%

On the Semantics of Trust and Caching in the Semantic Web

Schenk

2008

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. The Semantic Web is a distributed environment for knowledge representation and reasoning. The distributed nature brings with it failing data sources and inconsistencies between autonomous knowledge bases. To reduce problems resulting from unavailable sources and to improve performance, caching can be used. Caches, however, raise new problems of imprecise or outdated information. We propose to distinguish between certain and cached information when reasoning on the semantic web, by extending the well known FOUR bilattice of truth and knowledge orders to FOUR − C, taking into account cached information. We discuss how users can be offered additional information about the reliability of inferred information, based on the availability of the corresponding information sources. We then extend the framework towards FOUR − T , allowing for multiple levels of trust on data sources. In this extended setting, knowledge about trust in information sources can be used to compute, how well an inferred statement can be trusted and to resolve inconsistencies arising from connecting multiple data sources. We redefine the stable model and well founded semantics on the basis of FOUR − T , and reformalize the Web Ontology Language OWL2 based on logical bilattices, to augment OWL knowledge bases with trust based reasoning.The Semantic Web is envisioned to be a Web of Data [2]. As such, it integrates information from various sources, may it be through rules, data replication or similar mechanisms. Obviously, in a distributed scenario, information sources may become unavailable. In order to still be able to answer queries in such cases, mechanisms like caching can be used to reduce the negative implications of failure. Alternatively, some default truth value could be assumed for unavailable information. However, cached values may be inaccurate or outdated, default assumptions can be wrong. Moreover, also available information sources may be trusted to different extents. We propose a framework for reasoning with such trust levels, which allows to give additional information on the reliability of results to the user. In particular, we are able to tell whether a statement's truth value is inferred based on really accessible information, or whether it might change in the future, when cached or default values are updated. Consequently, we extend the framework towards multiple levels of trust, taking into account a trust order over information sources, which can possibly be partial. While assigning absolute trust values has little semantics, users are usually good at comparing the trustworthiness of two information sources.

show abstract

Trust-based Revision for Expressive Web Syndication

Cited by 14 publications

References 33 publications

Graph-based approaches to debugging and revision of terminologies in DL-Lite

Graph-based approaches to debugging and revision of terminologies in DL-Lite

Reasoning with streamed uncertain information from unreliable sources

On the Semantics of Trust and Caching in the Semantic Web

Contact Info

Product

Resources

About