Integrating semantic Web services ranking mechanisms using a common preference model

Abstract

Service ranking has been long-acknowledged to play a fundamental role in helping users to select the best offerings among services retrieved from a search request. There exist many ranking mechanisms, each one providing ad hoc preference models that offer different levels of expressiveness. Consequently, applying a single mechanism to a particular scenario constrains the user to define preferences based on that mechanism's facilities. Furthermore, a more flexible solution that uses several independent mechanisms will face interoperability issues because of the differences between preference models provided by each ranking mechanism. In order to overcome these issues, we propose a Preferencebased Universal Ranking Integration (PURI) framework that enables the combination of several ranking mechanisms using a common, holistic preference model. Using PURI, different ranking mechanisms are seamlessly and transparently integrated, offering a single façade to define preferences using highly expressive facilities that are not only decoupled from the concrete mechanisms that perform the ranking process, but also allow to exploit synergies from the combination of integrated mechanisms. We also thoroughly present a particular application scenario in the SOA4All EU project and evaluate the benefits and applicability of PURI in further domains.

Priority-Based Human Resource Allocation in Business Processes

“…The implementation can be divided into a domain-independent part and a domain-specific part. The first part is based on PURI [6], a preference framework that provides the building blocks to implement new ranking mechanisms and also provides an implementation of the ranking mechanisms of all of the composite preferences. For our proof-of-concept, we implemented the generic ranking mechanism for both the atomic preferences and for all gt functions based on the preference types defined in SOUP.…”

“…The first challenge is solved by leveraging SOUP, a highly expressive user preference model defined by García et al [4,6] that we adapt to the BP domain in this paper. To deal with the second challenge, we have developed a novel algorithm to rank resources according to the preferences expressed in SOUP.…”

“…Ranking mechanisms can be shared between different preference terms. In [6], ranking mechanisms for composite preference terms are discussed. However, the authors do not provide details about the ranking mechanisms for atomic preferences because they heavily depend on the characteristics of the knowledge base that contains the information about the domain concepts used in the preferences.…”

“…Our solution builds on the adaptation of a user preference model that was developed for the discovery and ranking of semantic web services [4] to the domain at hand. As a proof of concept, we have extended the resource management tool Collection of Resource-centrIc Supporting Tools And Languages (CRISTAL) 3 [5] with the Semantic Ontology of User Preferences (SOUP) component [6] to support priority-based allocation. In this system, Resource Assignment Language (RAL) [7] is used for resource selection.…”

Linked USDL Agreement: Effectively Sharing Semantic Service Level Agreements on the Web

“…These paper-based contracts are often prepared by lawyers and require a case-by-case customization. The following illustrative and representative extract of a service agreement contract 16 describes service level availability. Contracts are often composed of two parts: 1) the agreement and 2) the exhibits.…”