Though research on the Semantic Web has progressed at a steady pace, its promise has yet to be realized. One major difficulty is that, by its very nature, the Semantic Web is a large, uncensored system to which anyone may contribute. This raises the question of how much credence to give each source. We cannot expect each user to know the trustworthiness of each source, nor would we want to assign top-down or global credibility values due to the subjective nature of trust. We tackle this problem by employing a web of trust, in which each user maintains trusts in a small number of other users. We then compose these trusts into trust values for all other users. The result of our computation is not an agglomerate "trustworthiness" of each user. Instead, each user receives a personalized set of trusts, which may vary widely from person to person. We define properties for combination functions which merge such trusts, and define a class of functions for which merging may be done locally while maintaining these properties. We give examples of specific functions and apply them to data from Epinions and our BibServ bibliography server. Experiments confirm that the methods are robust to noise, and do not put unreasonable expectations on users. We hope that these methods will help move the Semantic Web closer to fulfilling its promise.

Trust management for the Semantic Web

The B Book

http://www.umbertostraccia.it/cs/download/papers/JWS08/JWS08.pdf

Managing uncertainty and vagueness in description logics for the Semantic Web

https://www.um.edu.mt/library/oar/bitstream/123456789/22142/1/bt45-aij.pdf

Automatic generation of textual summaries from neonatal intensive care data

Preferences in AI: An overview

This paper proposes a general discussion of the handling of imprecise and uncertain information in temporal reasoning in the framework of fuzzy sets and possibility theory. The introduction of fuzzy features in temporal reasoning can be related to different issues. First, it can be motivated by the need of a gradual, linguistic-like description of temporal relations even in the face of complete information. An extension of Allen relational calculus is proposed, based on fuzzy comparators expressing linguistic tolerance. Fuzzy Allen relations are defined from a fuzzy partition made by three possible fuzzy relations between dates (approximately equal, clearly smaller, and clearly greater). Second, the handling of fuzzy or incomplete information leads to pervade classical Allen relations, and more generally fuzzy Allen relations, with uncertainty. The paper provides a detailed presentation of the calculus of fuzzy Allen relations (including the composition table of these relations). Moreover, the paper discusses the patterns for propagating uncertainty about (fuzzy) Allen relations in a possibilistic way.

/pdf/fuzziness-and-uncertainty-in-temporal-reasoning-2xp938db3w.pdf

Fuzziness and Uncertainty in Temporal Reasoning

The paper presents a new approach to database preference queries, where preferences are represented in a possibilistic logic manner, using symbolic weights. The symbolic weights may be processed without assessing their precise value, which leaves the freedom for the user to not specify any priority among the preferences. The user may also enforce a (partial) ordering between them, if necessary. The approach can be related to the processing of fuzzy queries whose components are conditionally weighted in terms of importance. In this paper, importance levels are symbolically processed, and refinements of both Pareto ordering and minimum ordering are used. The representational power of the proposed setting is stressed, while the approach is compared with database Best operator-like methods and with the CP-net approach developed in artificial intelligence. The paper also provides a structured and rather broad overview of the different lines of research in the literature dealing with the handling of preferences in database queries.

Database preference queries--a possibilistic logic approach with symbolic priorities

The paper presents a new approach to database preferences queries, where preferences are represented in a possibilistic logic manner, using symbolic weights. The symbolic weights may be processed without assessing their precise value, which leaves the freedom for the user to not specify any priority among the preferences. The user may also enforce a (partial) ordering between them, if necessary. The approach can be related to the processing of fuzzy queries whose components are conditionally weighted in terms of importance. Here, importance levels are symbolically processed, and refinements of both Pareto ordering and minimum ordering are used. The representational power of the proposed setting is stressed, while the approach is compared with database Best operator-like methods and with the CP-net approach developed in artificial intelligence. The paper also provides a structured and rather broad overview of the different lines of research in the literature dealing with the handling of preferences in database queries.

Database preferences queries: a possibilistic logic approach with symbolic priorities

Nowadays, the exploding number of functionally similar Web services has led to a new challenge of selecting the most relevant services using quality of service (QoS) aspects. Traditionally, the relevance of a service is determined by computing an overall score that aggregates individual QoS values. Users are required to assign weights to QoS attributes. This is a rather demanding task and an imprecise specification of the weights could result in missing some user desired services. Recent approaches focus on computing service skyline over a set of QoS aspects. This can completely free users from assigning weights to QoS attributes. However, two main drawbacks characterize such approaches. First, the service skyline often privileges services with a bad compromise between different QoS attributes. Second, as the size of the service skyline may be quite large, users will be overwhelmed during the service selection process. In this paper, we introduce a new concept, called alpha-dominant service skyline, to address the above issues and we develop a suitable algorithm for computing it efficiently. Experimental evaluation conducted on synthetically generated datasets, demonstrates both the effectiveness of the introduced concept and the efficiency of the proposed algorithm.

Allel Hadjali

Papers

Fuzziness and Uncertainty in Temporal Reasoning

Database preference queries--a possibilistic logic approach with symbolic priorities

Database preferences queries: a possibilistic logic approach with symbolic priorities

On the Use of Fuzzy Dominance for Computing Service Skyline Based on QoS

Empty versus overabundant answers to flexible relational queries