Domain ontology learning from the web

El Aprendizaje de Ontologías se define como el conjunto de métodos utilizados para construir, enriquecer o adaptar una ontología existente de forma semiautomática, utilizando fuentes de información heterogéneas. En este proceso se emplea texto, diccionarios electrónicos, ontologías lingüísticas e información estructurada y semiestructurada para extraer conocimiento. Recientemente, gracias al enorme crecimiento de la Sociedad de la Información, la Web se ha convertido en una valiosa fuente de información para casi cualquier dominio. Esto ha provocado que los investigadores empiecen a considerar a la Web como un repositorio válido para Recuperar Información y Adquirir Conocimiento. No obstante, la Web presenta algunos problemas que no se observan en repositorios de información clásicos: presentación orientada al usuario, ruido, fuentes no confiables, alta dinamicidad y tamaño abrumador. Pese a ello, también presenta algunas características que pueden ser interesantes para la adquisición de conocimiento: debido a su enorme tamaño y heterogeneidad, se asume que la Web aproxima la distribución real de la información a nivel global. Este trabajo describe una aproximación novedosa para el aprendizaje de ontologías, presentando nuevos métodos para adquirir conocimiento de la Web. La propuesta se distingue de otros trabajos previos principalmente en la particular adaptación de algunas técnicas clásicas de aprendizaje al corpus Web y en la explotación de las características interesantes del entorno Web para componer una aproximación automática, no supervisada e independiente del dominio. Con respecto al proceso de construcción de la ontologías, se han desarrollado los siguientes métodos: i) extracción y selección de términos relacionados con el dominio, organizándolos de forma taxonómica; ii) descubrimiento y etiquetado de relaciones no taxonómicas entre los conceptos; iii) métodos adicionales para mejorar la estructura final, incluyendo la detección de entidades con nombre, atributos, herencia múltiple e incluso un cierto grado de desambiguación semántica. La metodología de aprendizaje al completo se ha implementado mediante un sistema distribuido basado en agentes, proporcionando una solución escalable. También se ha evaluado para varios dominios de conocimiento bien diferenciados, obteniendo resultados de buena calidad. Finalmente, se han desarrollado varias aplicaciones referentes a la estructuración automática de librerías digitales y recursos Web, y la recuperación de información basada en ontologías.Ontology Learning is defined as the set of methods used for building from scratch, enriching or adapting an existing ontology in a semi-automatic fashion using heterogeneous information sources. This data-driven procedure uses text, electronic dictionaries, linguistic ontologies and structured and semi-structured information to acquire knowledge. Recently, with the enormous growth of the Information Society, the Web has become a valuable source of information for almost every possible domain of knowledge. This has motivated researchers to start considering the Web as a valid repository for Information Retrieval and Knowledge Acquisition. However, the Web suffers from problems that are not typically observed in classical information repositories: human oriented presentation, noise, untrusted sources, high dynamicity and overwhelming size. Even though, it also presents characteristics that can be interesting for knowledge acquisition: due to its huge size and heterogeneity it has been assumed that the Web approximates the real distribution of the information in humankind. The present work introduces a novel approach for ontology learning, introducing new methods for knowledge acquisition from the Web. The adaptation of several well known learning techniques to the web corpus and the exploitation of particular characteristics of the Web environment composing an automatic, unsupervised and domain independent approach distinguishes the present proposal from previous works.With respect to the ontology building process, the following methods have been developed: i) extraction and selection of domain related terms, organising them in a taxonomical way; ii) discovery and label of non-taxonomical relationships between concepts; iii) additional methods for improving the final structure, including the detection of named entities, class features, multiple inheritance and also a certain degree of semantic disambiguation. The full learning methodology has been implemented in a distributed agent-based fashion, providing a scalable solution. It has been evaluated for several well distinguished domains of knowledge, obtaining good quality results. Finally, several direct applications have been developed, including automatic structuring of digital libraries and web resources, and ontology-based Web Information Retrieval

Relação de colaboração entre universidade e indústria de software com base na gestão do conhecimento: uma abordagem exploratória

The current environment that characterizes the software industry is extremely dynamic and somewhat complex demanding high-performance solutions, rapid development and cost efficiency. The collaboration relationship with universities has been represented a key resource, to the extent that together more easily can promote technological development that underpins innovation solutions. In addition, several studies point out knowledge sharing as an important and strongly influential factor in a collaboration relationship. In this context, the present thesis aims to identify a set of factors that can enhance and/or facilitate the collaboration relationship between the university and the software industry in a sustainable way, based on knowledge management. In line with the general objective three research questions were defined: (i) What are the main motivations that lead to the decision of establishing a collaboration relationship?; (ii) What are the management mechanisms used in the governance of collaboration relationships?; (iii) What are the principles and culture of knowledge management and of knowledge sharing in these organizations? In order to answer those questions and, consequently, achieve the general objective, an initial quantitative study based on a questionnaire was conducted. This study aims to explore and understand the practice of knowledge sharing and collaboration in the context of a university. Overall it was concluded that, knowledge sharing positively affects the collaboration behavior. The obtained results also showed that in order to promote and encourage knowledge sharing and, consequently, to foster collaboration relationships, it is important to work mechanisms based on intrinsic motivation and networking. Subsequently, it was conducted a qualitative study based on interviews in order to identify a set of factors that could enhance/facilitate the collaboration relationship between the university and the software industry in a sustainable way, based on knowledge management. Participants with complementary visions and different experiences in the two types of involved industries and simultaneously, with decisionmaking positions were interviewed. The results revealed that collaboration relationships established among these organizations are set-up only as a ‘connection’. This ‘connection’ is characterized by being a simple exchange, without building a sustainable collaboration relationship; although, those involved point to advantages in the existence of a sustainable collaboration relationship. The results also revealed that the collaboration relationships are usually conducted through informal communication channels, which makes it difficult to capture and disseminate knowledge to other remaining members of each involved organizations. In nutshell and in practical terms, this work contributes to the identification and analysis of a set of factors that enhance a collaboration relationship between university and software industry. This result can support organizations in the strategies definition for the development of actions, in order to promote a sustainable collaboration relationship. In theoretical terms, this work contributes to the increase of the body of knowledge in the area, with empirical results, since the literature point the lack of empirical studies as the main gap in this area of knowledge.O atual ambiente que carateriza a indústria de software é extremamente dinâmico e, de certa forma complexo, exigindo soluções de alto desempenho, de desenvolvimento rápido e eficientes em termos de custos. A relação de colaboração com as universidades pode representar um recurso fundamental, na medida em que juntas mais facilmente podem promover o desenvolvimento tecnológico que está na base de soluções de inovação. Adicionalmente, são os vários estudos que apontam a partilha de conhecimento como um fator importante e fortemente influenciador de uma relação de colaboração. Neste contexto, a presente tese tem como objetivo identificar um conjunto de fatores que possam potencializar e/ou facilitar a relação de colaboração entre a universidade e a indústria de software de forma sustentável, com base na gestão do conhecimento. Em consonância com o objetivo geral, foram definidas três questões de investigação: (i) Quais são as principais motivações que levam à decisão de estabelecer uma relação de colaboração?; (ii) Quais são os mecanismos de gerenciamento usados na governança das relações de colaboração?; (iii) Quais são os princípios e a cultura da gestão do conhecimento e da partilha de conhecimento nessas organizações? Por forma a responder àquelas questões e, consequentemente, ao objetivo geral, numa fase inicial foi conduzido um estudo quantitativo através da aplicação de um questionário cujo objetivo foi o de explorar e compreender a prática da partilha de conhecimento e de colaboração no contexto de uma universidade. De uma maneira geral, concluiu-se que a partilha de conhecimento afeta positivamente o comportamento de colaboração. Os resultados obtidos mostram ainda que, por forma a promover e incentivar a partilha de conhecimento e, consequentemente, fomentar as relações de colaboração, é importante trabalhar os mecanismos baseados na motivação intrínseca e no networking. Seguidamente, foi conduzido um estudo qualitativo com base em entrevistas, com o objetivo de identificar um conjunto de fatores que pudessem melhorar e/ou facilitar a relação de colaboração entre a universidade e a indústria de software de forma sustentável, com base na gestão do conhecimento. Foram entrevistados participantes com visões complementares e experiências diferentes nos dois tipos de indústria envolvidas e, simultaneamente, que ocupassem posições com poder de decisão. Os resultados revelaram que as relações de colaboração estabelecidas entre essas organizações são configuradas apenas como uma ‘conexão’. Esta ‘conexão’ é caracterizada por ser uma troca simples, sem construir uma relação de colaboração sustentável; embora os envolvidos apontem vantagens na existência de uma relação de colaboração sustentável. Os resultados revelaram ainda que as relações de colaboração são, normalmente, conduzidas através de canais informais de comunicação, o que dificulta a captura e disseminação do conhecimento pelos restantes membros de cada uma das organizações envolvidas. Em jeito de conclusão e em termos práticos este trabalho contribui com a identificação e análise de um conjunto de fatores potenciadores de uma relação de colaboração entre a universidade e a indústria de software, podendo auxiliar as organizações envolvidas na definição de estratégias para o desenvolvimento de ações futuras, a fim de promover uma relação de colaboração sustentável. Em termos teóricos, este trabalho contribui para o aumento do corpo de conhecimento na área, com resultados provenientes de estudos empíricos, uma vez que a literatura aponta como principal lacuna a ausência daqueles (estudos empíricos), por forma a complementar e validar a teoria existente.Programa Doutoral em Engenharia e Gestão Industria

A benefit-oriented framework for the decision-making process on the application of KMS in SME

The result of the presented PhD project is an artifact providing the SME practitioner with the KinS conceptual framework including method support. Therefore concepts from KM and KMS are newly combined and validated applying the perceived benefit approach of the KMS Success Model. The KinS framework uses the demand for support as the starting point for the perceived benefit and analyzes it with regard to the support opportunities by knowledge services. With the help of the framework, the gap in the knowledge base can be addressed and benefit-orientation in the KMS support can be provided

Opinion mining with the SentWordNet lexical resource

Sentiment classification concerns the application of automatic methods for predicting the orientation of sentiment present on text documents. It is an important subject in opinion mining research, with applications on a number of areas including recommender and advertising systems, customer intelligence and information retrieval. SentiWordNet is a lexical resource of sentiment information for terms in the English language designed to assist in opinion mining tasks, where each term is associated with numerical scores for positive and negative sentiment information. A resource that makes term level sentiment information readily available could be of use in building more effective sentiment classification methods. This research presents the results of an experiment that applied the SentiWordNet lexical resource to the problem of automatic sentiment classification of film reviews. First, a data set of relevant features extracted from text documents using SentiWordNet was designed and implemented. The resulting feature set is then used as input for training a support vector machine classifier for predicting the sentiment orientation of the underlying film review. Several scenarios exploring variations on the parameters that generate the data set, outlier removal and feature selection were executed. The results obtained are compared to other methods documented in the literature. It was found that they are in line with other experiments that propose similar approaches and use the same data set of film reviews, indicating SentiWordNet could become an important resource for the task of sentiment classification. Considerations on future improvements are also presented based on a detailed analysis of classification results

Computer-based tools for supporting forest management. The experience and the expertise world-wide

Report of Cost Action FP 0804 Forest Management Decision Support Systems (FORSYS)Computer-based tools for supporting forest management. The experience and the expertise world-wide answers a call from both the research and the professional communities for a synthesis of current knowledge about the use of computerized tools in forest management planning. According to the aims of the Forest Management Decision Support Systems (FORSYS) (http://fp0804.emu.ee/) this synthesis is a critical success factor to develop a comprehensive quality reference for forest management decision support systems. The emphasis of the book is on identifying and assessing the support provided by computerized tools to enhance forest management planning in real-world contexts. The book thus identifies the management planning problems that prevail world-wide to discuss the architecture and the components of the tools used to address them. Of importance is the report of architecture approaches, models and methods, knowledge management and participatory planning techniques used to address specific management planning problems. We think that this synthesis may provide effective support to research and outreach activities that focus on the development of forest management decision support systems. It may contribute further to support forest managers when defining the requirements for a tool that best meets their needs. The first chapter of the book provides an introduction to the use of decision support systems in the forest sector and lays out the FORSYS framework for reporting the experience and expertise acquired in each country. Emphasis is on the FORSYS ontology to facilitate the sharing of experiences needed to characterize and evaluate the use of computerized tools when addressing forest management planning problems. The twenty six country reports share a structure designed to underline a problem-centric focus. Specifically, they all start with the identification of the management planning problems that are prevalent in the country and they move on to the characterization and assessment of the computerized tools used to address them. The reports were led by researchers with background and expertise in areas that range from ecological modeling to forest modeling, management planning and information and communication technology development. They benefited from the input provided by forest practitioners and by organizations that are responsible for developing and implementing forest management plans. A conclusions chapter highlights the success of bringing together such a wide range of disciplines and perspectives. This book benefited from voluntary contributions by 94 authors and from the involvement of several forest stakeholders from twenty six countries in Europe, North and South America, Africa and Asia over a three-year period. We, the chair of FORSYS and the editorial committee of the publication, acknowledge and thank for the valuable contributions from all authors, editors, stakeholders and FORSYS actors involved in this project