Semantic metrics

In the context of the Semantic Web, many ontology-related operations, e.g. ontology ranking, segmentation, alignment, articulation, reuse, evaluation, can be boiled down to one fundamental operation: computing the similarity and?or dissimilarity among ontological entities, and in some cases among ontologies themselves. In this paper, we review standard metrics for computing distance measures and we propose a series of semantic metrics. We give a formal account of semantic metrics drawn from a variety of research disciplines, and enrich them with semantics based on standard Description Logic constructs. We argue that concept-based metrics can be aggregated to produce numeric distances at ontology-level and we speculate on the usability of our ideas through potential areas

Business Process Retrieval Based on Behavioral Semantics

This paper develops a framework for retrieving business processes considering search requirements based on behavioral semantics properties; it presents a framework called "BeMantics" for retrieving business processes based on structural, linguistics, and behavioral semantics properties. The relevance of the framework is evaluated retrieving business processes from a repository, and collecting a set of relevant business processes manually issued by human judges. The "BeMantics" framework scored high precision values (0.717) but low recall values (0.558), which implies that even when the framework avoided false negatives, it prone to false positives. The highest pre- cision value was scored in the linguistic criterion showing that using semantic inference in the tasks comparison allowed to reduce around 23.6 % the number of false positives. Using semantic inference to compare tasks of business processes can improve the precision; but if the ontologies are from narrow and specific domains, they limit the semantic expressiveness obtained with ontologies from more general domains. Regarding the perform- ance, it can be improved by using a filter phase which indexes business processes taking into account behavioral semantics propertie

Ranking trapezoidal fuzzy numbers based on set theoretic indices with Hurwicz criterion / Nazirah Ramli

Ranking of fuzzy numbers (FNs) is an important procedure for many applications in fuzzy theory, in particular, decision-making. Various methods of ranking fuzzy numbers (RFNs) have been developed but no method can rank overlapped trapezoidal fuzzy numbers (TrFNs) satisfactorily in all cases and situations. Some methods produce non-discriminate and non-intuitive results, limited to normal TrFNs and only consider neutral decision makers’ perspective. Some methods also have complex computation and cannot discriminate the ranking of TrFNs having the same mode and symmetric spread. The objective of this thesis is to develop new ranking indices (NRI) based on Sokal & Sneath, Dice and Ochiai set theoretic similarity measure (STSM) indices, and formulate the procedures for ranking overlapped TrFNs where the overlapped TrFNs are classified into seven main types. Eight phases are involved in the development of the NRI which consist of determining the fuzzy maximum (FMax), fuzzy minimum (FMin), evidences, total evidences, pair wise ranking, transitivity of relation and ranking of n TrFNs. The TrFNs involved are taken from the benchmark cases in the literature. The usage of second function principle in determining the FMax and FMin enables the NRI to rank non-normal TrFNs and this has overcome the limitations in some of the previous ranking indices which can only rank normal TrFNs. This study investigates on the development of the NRI and based on that, two observations and three algorithms are created. The determination of ranking results of the NRI involved three stages which are by comparing the values of total evidences in the development phase, by using the observations and by using the algorithms. The observations had rendered the NRI as advantageous method in RFNs since the ranking results can be obtained for all with , and represent pessimistic, neutral and optimistic decision makers’ perspective respectively. Based on the algorithms, the ranking of each type of overlapped TrFNs can be determined merely by the point wise operations. This study evaluates the performance of NRI in terms of rationality, consistency and robustness criteria. The NRI satisfies five axioms on the rationality properties which is similar with some of the previous ranking indices. Most of the ranking results for NRI which are independent with decision makers’ perspective have consistent ranking with the previous methods. The ranking results for some TrFNs with included TrFNs having the same mode and symmetric spread (which cannot be discriminated by a number of the previous methods) are affected by the decision makers’ perspective and this shows that the NRI has strong discrimination ability. For the robustness criterion of the NRI, type of changes of the TrFNs and conditions for robustness are proposed, and these have been applied to the Anugerah Kualiti Naib Canselor (AKNC) case study. The findings show that the NRI is robust for solving AKNC case study with the Dice and Ochiai ranking indices have less computing time compared with some of the previous methods. As the NRI can rank all types of FNs and all types of decision makers’ perspective, and the ranking can be determined merely by the point wise operations, NRI becomes an advantageous ranking method for solving multi-criteria decision-making (MCDM) problems in fuzzy environment. 1 ,05 .0,05 .01 ,5.