Fuzzy matchmaking in e-marketplaces of peer entities using Datalog

Abstract

We present an approach to matchmaking in electronic marketplaces of peer entities, which mixes in a formal and principled way Datalog, fuzzy sets and utility theory, in order to determine the most promising matches between prospective counterparts. The use of Datalog ensures the scalability of our approach to large marketplaces, while Fuzzy Logic provides a neat connection with logical specifications and allows to model soft constraints and how well they could be satisfied by an agreement. Noteworthy is that our approach takes into account in the peer-to-peer matchmaking also preferences of each counterpart and their utilities. This allows to rule out of the match list those counteroffers that, although seemingly appealing for the buyer, would probably lead to failure due to contrasting preferences of the seller, and paves the way to the actual negotiation stage.

Semantic Matching Strategies for Job Recruitment: A Comparison of New and Known Approaches

“…Fuzzy techniques are introduced in Ragone et al [22] where they consider a peer-to-peer e-marketplace of used cars. Also a form of logic programming is applied using fuzzy extension of Datalog.…”

“…Also a form of logic programming is applied using fuzzy extension of Datalog. Papers [6,22] contain extensive lists of further references concerning practical algorithms, related areas of multiobjective decision making, logic programming, description logic, query reformulation and top-k query answering.…”

A Fuzzy Extension to the OWL 2 RL Ontology Language

“…However, the semantics would be based again on fuzzy interpretations. Note that, due to the flexibility allowed in the fuzzy setting, there is a spate of fuzzy extensions of Datalog (see [43,44,45,46,47,48,49] to name just a few). Here, we will stick to the most standard syntax and features of Datalog, which are enough to study the correspondence of the fuzzy DLs we defined in the previous section, and we will not consider such extensions.…”

Semantic Inference on Heterogeneous E-Marketplace Activities

“…There is an extensive e-marketplace literature on semantic inference that includes several comprehensive studies [1], [4], [6], [13], [16], [54], [55]. In addition, there is ample research work on the classification of inference engine [34], [39], [49].…”