Improving semantic Web services discovery and ranking: A lightweight, integrated approach

Semantic Web services frameworks provide the means to automatically discover, rank, compose and invoke services according to user requirements and preferences. However, current preference models offer limited expressiveness and they are tightly coupled with underlying discovery and ranking mechanisms. Furthermore, these mechanisms present performance, interoperability and integration issues that prevent the uptake of semantic technologies in these scenarios. In this work, we discuss three interrelated contributions on preference modeling, discovery optimization, and flexible, integrated ranking, tackling specifically the identified challenges on those areas using a lightweight approach.Junta de Andalucía P12-TIC-1867Ministerio de Economía y Competitividad TIN2012-32273Junta de Andalucía TIC-590

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

A Model of User Preferences for Semantic Services Discovery and Ranking

Current proposals on Semantic Web Services discovery and ranking are based on user preferences descriptions that often come with insufficient expressiveness, consequently making more difficult or even preventing the description of complex user desires. There is a lack of a general and comprehensive preference model, so discovery and ranking proposals have to provide ad hoc preference descriptions whose expressiveness depends on the facilities provided by the corresponding technique, resulting in user preferences that are tightly coupled with the underlying formalism being used by each concrete solution. In order to overcome these problems, in this paper an abstract and sufficiently expressive model for defining preferences is presented, so that they may be described in an intuitively and user-friendly manner. The proposed model is based on a well-known query preference model from database systems, which provides highly expressive constructors to describe and compose user preferences semantically. Furthermore, the presented proposal is independent from the concrete discovery and ranking engines selected, and may be used to extend current Semantic Web Service frameworks, such as wsmo, sawsdl, or owl-s. In this paper, the presented model is also validated against a complex discovery and ranking scenario, and a concrete implementation of the model in wsmo is outlined.Comisión Interministerial de Ciencia y Tecnología TIN2006-00472Comisión Interministerial de Ciencia y Tecnología TIN2009-07366Junta de Andalucía TIC-253

SEMANTIC SIMILARITY BASED INFORMATION RETRIEVAL AS APPLIED TO MOOCs

Over the last few years there has been a significant development in the e-learning industry that provides online courses to the public. Due to the drastic improvement in technology and the Internet, this form of education reaches many people across boundaries. There is vast set of courses currently provided by various sources, which range from the latest technologies in the field of computer science to any topic in history. Since the invention of e-learning, there has been constant improvement of user friendly tools to enhance the learning process. In the span of the last three years, many websites have come into existence that provide online courses. Some of the best universities in the United States and other universities throughout the world have also started to provide online courses that students can easily attend. It has become very difficult for a student to pick the right online course. Hence, an application that can integrate the courses provided by various e-learning websites like Coursera, Udacity and Edx would be very helpful. The student can compare the regular courses provided by his or her university with the courses offered by the e-learning websites and can enroll in similar online courses to get a better understanding of the subject. The objective of this project is to use semantic similarity techniques to identify the MOOCs [massive open online courses] offered by the e-learning websites which are similar to the regular courses offered by the university

SLA management of non-computational services.

El incremento en el uso de arquitecturas orientadas a servicios en los últimos 15 años ha propiciado la propuesta de numerosas técnicas para automatizar y dar soporte al uso de dichos servicios. Un elemento fundamental en la provisión de servicios es el Acuerdo de Nivel de Servicio (ANS), donde se formalizan los requisitos y garantías de consumidor y proveedor respecto del rendimiento del servicio. Las propuestas para servicios computacionales, además de proveer modelos formales para describirlos, proponen la automatización de las diferentes etapas del ciclo de vida del ANS, tales como la negociación de las garantías para crear un ANS, el despliegue de servicios basados en el ANS, o la gestión de los recursos para cumplir las garantías provistas en el mismo. Sin embargo, en los servicios tradicionales, no computacionales, es decir, los servicios que no son ejecutados por recursos computacionales, tales como los servicios de logística o de desarrollo de software, la gestión de sus ANSs todavía se realiza por medios ad-hoc. Así, las soluciones existentes no pueden ser reutilizadas por diferentes servicios. Y, en la mayoría de los casos, esta gestión se hace de manera manual (p.e. revisión de los objetivos acordados en los ANSs de servicios de transporte), por lo que la evaluación de estos ANSs es susceptible a errores y se suele retrasar respecto a la ejecución del servicio (p.e. cuando el ANS ha finalizado), por lo que no se pueden tomar acciones preventivas para evitar el incumplimiento del ANS o estas acciones no son rentables. En estos escenarios, aparecen, además, acuerdos marco para un periodo largo (p.e. 1 aõ), durante el cual pueden aparecen ANSs relacionados con éste para un periodo más específico y el análisis de la coherencia entre acuerdos marco y acuerdos específicos es complicada de hacer durante la ejecución del servicio. En esta tesis, nos proponemos automatizar parcialmente la gestión de los ANSs de servicios no computacionales. Así, por un lado, proponemos que los modelos para servicios computacionales se extiendan a servicios no computacionales, de manera que permitan describir la operativa del servicio y sus garantías. Y, por otro lado, basado en estos modelos, proporcionamos el diseño de operaciones para gestionar el ciclo de vida de los ANS. Concretamente, estas operaciones se basan en las fases de despligue y evaluación del ANS. De forma específica, esta tesis propone tres contribuciones principales. Primero, (A) extender iAgree para dar soporte al modelado de los ANS de servicios no computacionales. Segundo, (B) dar soporte al ciclo de vida de dichos ANS mediante la formalización de las operaciones citadas (configuración del servicio basada en el ANS y monitorización del mismo) y, a partir de estas operaciones, implementamos una arquitectura de referencia para estas operaciones. Y, por último, (C) proveemos el modelado de la relación entre acuerdos marco y específicos que relacione sus términos junto con la formalización de las operaciones para el análisis que aparecen entre ellos. Otros aspectos del ciclo de vida del servicio y del ANS, como la gestión de los recursos para mejorar el rendimiento del servicio o el uso de técnicas (como machine learning) para la predicción del cumplimiento de los ANSs están fuera del contexto de esta tesis, pero se plantean como futuras líneas de extensión. Este trabajo se ha basado en ANSs reales de diferentes dominios, tales como servicios de Transporte y Logística, proveedores de Cloud or outsourcing de desarrollo TIC, que se han utilizado para validar las propuestas. Además, las contribuciones presentadas se han aplicado en el contexto de proyectos reales de soporte de sistemas TIC.The rise of computational services in the last 15 years brought the proposal of a number of techniques to automate and support their enactment. One key element in services is the Service Level Agreement (SLA), where the requirements of service customer are matched with the performance levels from the service provider to define service level guarantees and related responsibilities. The proposals from computational domains are oriented to automate the different stages in the SLA Lifecycle, such as the negotiation of terms which will form the SLA, the deployment of services based on the SLA artifact or the management of computational resources to accomplish SLA goals on runtime. However, traditional non-computational services, that is, services which are not performed by computational resources, such as logistics or software development services, are still supported by ad-hoc mechanisms. Therefore, the existing solutions for the management of their SLAs cannot be reused for other services. This management is usually manually performed (e.g.: reviewing of the goals of an SLA in transport service), so their evaluation is error-prone and delayed regarding the service execution (e.g.: when the SLA is finished), so preemptive actions to avoid SLA violations cannot be taken or/and are expensive to perform. Furthermore, these SLAs are sometimes described on a long term basis (frame agreements), and related SLAs can appear for a shorter term (specific agreements) and the analysis of the validity among them is complex to perform on runtime. In this dissertation, we aim at partially automate the management of SLAs in noncomputational services. On the one hand, we suggest that existing models for computational services can be extended to non computational services and enable the description of the service operative and their guarantees. And, on the other hand, we provide a design for operations to partially support the SLA Lifecycle, based on the previous models. Specifically, these operations are mainly focused on the deployment and fulfillment stages of the SLA. Therefore, the contributions of this dissertation are three. First, (A) providing a model to describe Service Level Agreements of non computational services, as an extension of iAgree, an existing model for SLAs of computational services. Second side, (B) supporting the SLA Lifecycle with the design of the aforementioned operations (service configuration based on SLA and monitoring of SLA) and implementing a reference architecture for such operations. And, lastly, (C) providing a model for frame and specific agreements which relates their terms and formalises the analysis operations among them. Other related operations of the service lifecycle as the management of resources to improve service performance or the use of novel techniques (such as machine learning) to predict the SLA accomplishment are out of the scope of this thesis but planned as future line of extension. The current dissertation has been based on real SLAs from different domains, such as Transport & Logistics, public Cloud providers or IT Maintenance outsourcing, which have been used to validate the proposal. And, furthermore, the contributions have been applied in the context of real IT Maintenance outsourcing projects

Mining a Small Medical Data Set by Integrating the Decision Tree and t-test

[[abstract]]Although several researchers have used statistical methods to prove that aspiration followed by the injection of 95% ethanol left in situ (retention) is an effective treatment for ovarian endometriomas, very few discuss the different conditions that could generate different recovery rates for the patients. Therefore, this study adopts the statistical method and decision tree techniques together to analyze the postoperative status of ovarian endometriosis patients under different conditions. Since our collected data set is small, containing only 212 records, we use all of these data as the training data. Therefore, instead of using a resultant tree to generate rules directly, we use the value of each node as a cut point to generate all possible rules from the tree first. Then, using t-test, we verify the rules to discover some useful description rules after all possible rules from the tree have been generated. Experimental results show that our approach can find some new interesting knowledge about recurrent ovarian endometriomas under different conditions.[[journaltype]]國外[[incitationindex]]EI[[booktype]]紙本[[countrycodes]]FI

Correctness-aware high-level functional matching approaches for semantic web services

Existing service matching approaches trade precision for recall, creating the need for humans to choose the correct services, which is a major obstacle for automating the service matching and the service aggregation processes. To overcome this problem, the matchmaker must automatically determine the correctness of the matching results according to the defined users' goals. That is, only service(s)-achieving users' goals are considered correct. This requires the high-level functional semantics of services, users, and application domains to be captured in a machine-understandable format. Also this requires the matchmaker to determine the achievement of users' goals without invoking the services. We propose the G+ model to capture the high-level functional specifications of services and users (namely goals, achievement contexts and external behaviors) providing the basis for automated goal achievement determination; also we propose the concepts substitutability graph to capture the application domains' semantics. To avoid the false negatives resulting from adopting existing constraint and behavior matching approaches during service matching, we also propose new constraint and behavior matching approaches to match constraints with different scopes, and behavior models with different number of state transitions. Finally, we propose two correctness-aware matching approaches (direct and aggregate) that semantically match and aggregate semantic web services according to their G+ models, providing the required theoretical proofs and the corresponding verifying simulation experiments

Improving Semantic Web Services Discovery and Ranking: a Liggtweight, integrated approach

Los Servicios Web Semánticos (SWSs) se han convertido en un área de investigación muy activa, en la que diversos frameworks, como WSMO u OWL-S, definen ont ... Para solucionar estos problemas, la investigación se centra actualmente en el desarrollo de d