On User Preferences and Utility Functions in Selection: A Semantic Approach

Discovery tasks in the context of Semantic Web Services are generally performed using Description Logics. However, this formalism is not suited when non-functional, numerical parameters are involved in the discovery process. Furthermore, in selection tasks, where an optimization algorithm is needed, DLs are not capable of computing the optimum. Although there are DLs extensions that can handle numerical parameters, they bring decidability problems. Other solutions, as hybrid approaches which use DLs in functional discovery and other formalisms in non-functional selection, do not provide a semantic framework to describe user preferences based on non-functional properties. In this work, we propose to semantically describe user preferences, so they can be used to perform selection within a hybrid solution. By using semantically described utility functions in order to define user preferences, our proposal enables interoperability between service offers and demands, while providing a high level of expressiveness in these preferences and including them within SWS descriptions.Comisión Interministerial de Ciencia y Tecnología TIN2006-0047

Semantic Web Services Provisioning

Semantic Web Services constitute an important research area, where vari ous underlying frameworks, such as WSMO and OWL-S, define Semantic Web ontologies to describe Web services, so they can be automatically discovered, composed, and invoked. Service discovery has been traditionally interpreted as a functional filter in current Semantic Web Services frameworks, frequently performed by Description Logics reasoners. However, semantic provisioning has to be performed taking Quality-of-Service (QOS) into account, defining user preferences that enable QOS-aware Semantic Web Service selection. Nowadays, the research focus is actually on QOS-aware processes, so cur rent proposals are developing the field by providing QOS support to semantic provisioning, especially in selection processes. These processes lead to opti mization problems, where the best service among a set of services has to be selected, so Description Logics cannot be used in this context. Furthermore, user preferences has to be semantically defined so they can be used within selection processes. There are several proposals that extend Semantic Web Services frameworks allowing QOS-aware semantic provisioning. However, proposed selection techniques are very coupled with their proposed extensions, most of them being implemented ad hoc. Thus, there is a semantic gap between functional descriptions (usually using WSMO or OWL-S) and user preferences, which are specific for each proposal, using different ontologies or even non-semantic de scriptions, and depending on its corresponding ad hoc selection technique. In this report, we give an overview of most important Semantic Web Ser vices frameworks, showing a comparison between them. Then, a thorough analysis of state-of-the art proposals on QOS-aware semantic provisioning and user preferences descriptions is presented, discussing about their applicabil ity, advantages, and defects. Results from this analysis motivate our research work, which has been already materialized in two early contributions.Los servicios web semánticos constituyen un importante campo de inves tigación, en el cual distintos frameworks, como por ejemplo WSMO y OWL-S, definen ontologías de la web semántica para describir servicios web, de for ma que estos puedan ser descubiertos, compuestos e invocados de manera automática. El descubrimiento de servicios ha sido interpretado tradicional mente como un filtro funcional en los frameworks actuales de servicios web semánticos, usando para ello razonadores de lógica descriptiva. Sin embargo, las tareas de aprovisionamiento semántico deberían tener en cuenta la calidad del servicio, definiendo para ello preferencias de usuario de manera que sea posible realizar una selección de servicios web semánticos sensible a la cali dad. Actualmente, el foco de la investigación está en procesos sensibles a la ca lidad, por lo que las propuestas actuales están trabajando en este campo intro duciendo el soporte adecuado a la calidad del servicio dentro del aprovisio namiento semántico, y principalmente en las tareas de selección. Estas tareas desembocan en problemas de optimización, donde el mejor servicio de entre un concjunto debe ser seleccionado, por lo que las lógicas descriptivas no pue den ser usadas en este contexto. Además, las preferencias de usuario deben ser definidas semánticamente, de forma que puedan ser usadas en las tareas de selección. Existen bastantes propuestas que extienden los frameworks de servicios web semánticos para habilitar el aprovisionamiento sensible a la calidad. Sin embargo, las técnicas de selección propuestas están altamente acopladas con dichas extensiones, donde la mayoría de ellas implementan algoritmos ad hoc. Por tanto, existe un salto semántico entre las descripciones funcionales (nor malmente usando WSMO o OWL-S) y las preferencias de usuario, las cuales son definidas específicamente por cada propuesta, usando ontologías distin tas o incluso descripciones no semánticas que dependen de la correspondiente técnica de selección ad hoc

Ranking Semantic Web Services Using Rules Evaluation and Constraint Programming

Current Semantic Web Services discovery and ranking proposals are based on user preferences descriptions whose expressiveness are limited by the underlying logical formalism used. Thus, highly expressive preference descriptions, such as utility functions, cannot be handled by the kind of reasoners traditionally used to perform Semantic Web Services tasks. in this work, we outline a hybrid approach to allow the introduction of utility functions in user preferences descriptions, where both rules evaluation and constraint programming are used to perform the ranking process. Our proposal extends the Web Service Modeling Ontology with these descriptions, providing a highly expressive framework to specify preferences, and enabling a more general ranking process, which can be performed by different engines

Integrating Semantic Web Services Ranking Mechanisms Using a Common Preference Model

Service ranking has been long-acknowledged to play a fundamental role in helping users to select the best o erings among services retrieved from a search request. There exist many ranking mechanisms, each one providing ad hoc preference models that o er di erent levels of expressiveness. Consequently, applying a single mechanism to a particular scenario constrains the user to de ne preferences based on that mechanism's facilities. Furthermore, a more exible solution that uses several independent mechanisms will face interoperability issues because of the di erences between preference models provided by each ranking mechanism. In order to overcome these issues, we propose a Preference- based Universal Ranking Integration (PURI) framework that enables the combination of several ranking mechanisms using a common, holistic preference model. Using PURI, di erent ranking mechanisms are seamlessly and transparently integrated, o ering a single fa cade to de ne 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 bene ts and applicability of PURI in further domains

A Service Ranker Based on Logic Rules Evaluation and Constraint Programming

Ranking of Semantic Web Services is usually performed based on user preferences descriptions. These descriptions are expressed in terms of an underlying logical formalism, which limits their expressiveness. Thus, there are some kind of descriptions, such as utility functions, that cannot be handled by reasoners currently being used to perform Semantic Web Services tasks, though utility functions provide a higher level of expressiveness. in this work, we present a hybrid solution to allow the introduction of utility functions in user preferences descriptions, using both Logic Programming rules evaluation and Constraint Programming to perform the ranking process. This proposal is based on the Web Service Modeling Ontology, extending it with a highly expressive framework to specify user preferences, and enabling the integration of different engines to perform the ranking process

Non-functional Property based service selection: A survey and classification of approaches

In recent years there has been much effort dedicated to developing approaches for service selection based on non-functional properties. It is clear that much progress has been made, and by considering the individual approaches there is some overlap in functionality, but obviously also some divergence. In this paper we contribute a classification of approaches, that is, we define a number of criteria which allow to differentiate approaches. We use this classification to provide a comparison of existing approaches and in that sense provide a survey of the state of the art of the field. Finally we make some suggestions as to where the research in this area might be heading and which new challenges need to be addressed

Two-fold Semantic Web service matchmaking – applying ontology mapping for service discovery

Semantic Web Services (SWS) aim at the automated discovery and orchestration of Web services on the basis of comprehensive, machine-interpretable semantic descriptions. Since SWS annotations usually are created by distinct SWS providers, semantic-level mediation, i.e. mediation between concurrent semantic representations, is a key requirement for SWS discovery. Since semantic-level mediation aims at enabling interoperability across heterogeneous semantic representations, it can be perceived as a particular instantiation of the ontology mapping problem. While recent SWS matchmakers usually rely on manual alignments or subscription to a common ontology, we propose a two-fold SWS matchmaking approach, consisting of (a) a general-purpose semantic-level mediator and (b) comparison and matchmaking of SWS capabilities. Our semantic-level mediation approach enables the implicit representation of similarities across distinct SWS by grounding service descriptions in so-called Mediation Spaces (MS). Given a set of SWS and their respective grounding, a SWS matchmaker automatically computes instance similarities across distinct SWS ontologies and matches the request to the most suitable SWS. A prototypical application illustrates our approach

ACTAS: Adaptive Composition and Trading with Agents for Services

Mainly in business domains, the vision of gaining flexible, adaptive service environments is based on the standardization and practical proliferation of (Semantic) Web Services, ontologies, and agents. The standards of Web Services and their Service-oriented Architectures (SOA) became the standard paradigm for software component integration. Dynamic changes and the permanently increasing amount of available e-services of different domains are a challenge of Service Discovery and Composition. Mediation between different approaches and expert knowledge is often necessary for the composition of services of different domains. Semantic enhancements, Autonomic Service Discovery, and the research for more holistic concepts for the classification of e-services are current attempts of overcoming this challenge, in order to reach the ultimate goal of Autonomic SOC