Analysing the problem and main approaches for ontology population

Knowledge systems are a suitable computational approach to solve complex problems and to provide decision support. Ontologies are an approach for knowledge representation and Ontology Population looks for instantiating the constituent elements of an ontology, like properties and non-taxonomic relationships. Manual population by domain experts and knowledge engineers is an expensive and time consuming task. Thus, automatic or semi-automatic approaches are needed. This paper discusses the problem of Automatic Ontology Population and proposes a generic process specifying its phases and what kind of techniques can be used to perform the activities of each phase. Some techniques representing the state of the art of this field are also described along with the solutions they adopt for each phase of the AOP process with their advantages and limitations. This work is part of HERMES, a Brazil/Portugal research cooperation project looking for techniques and tools for automating the process of ontology learning and population.This work is supported by CNPq, CAPES and FAPEMA, research funding agencies of the Brazilian government

Um Processo Semi-Automático para o Povoamento de Ontologias a partir de Fontes Textuais

A aquisição de conhecimento é um processo de alto custo, complexo e caro que requer um especialista de domínio. Por isso, torna-se fundamental uma semi-automatização ou automatização desse processo. O povoamento de ontologias constitui uma abordagem para automatizar ou semi-automatizar a instanciação de classes, propriedades e relacionamentos de ontologias. O povoamento de ontologias com rapidez e baixo custo é crucial para o sucesso de aplicações baseadas em conhecimento. Este artigo propõe um processo semi-automático para o Povoamento de Ontologias (PSAPO) a partir de fontes textuais. Experimentos foram conduzidos na área do direito de família para avaliar o processo proposto e os resultados iniciais foram promissores

ERMHAN: A Context-Aware Service Platform to Support Continuous Care Networks for Home-Based Assistance

Continuous care models for chronic diseases pose several technology-oriented challenges for home-based continuous care, where assistance services rely on a close collaboration among different stakeholders such as health operators, patient relatives, and social community members. Here we describe Emilia Romagna Mobile Health Assistance Network (ERMHAN) a multichannel context-aware service platform designed to support care networks in cooperating and sharing information with the goal of improving patient quality of life. In order to meet extensibility and flexibility requirements, this platform has been developed through ontology-based context-aware computing and a service oriented approach. We also provide some preliminary results of performance analysis and user survey activity

Una revisión de la literatura sobre población de ontologías

The main goal of ontologies in computing is related to the definition of a common vocabulary for describing basic concepts and relationships on a specific domain. Main components of ontologies are classes—concepts—, instances, properties, relations, and axioms, among others elements. The ontology population process is intended to receive an ontology as input in order to extract and relate the instances of each ontology class from heterogenous information sources. In this paper we perform a systematic state-of-the-art review about ontology population. We select papers from specialized databases and we create a research question for driving paper search. The results of our review points out ontology population as an interesting topic for researchers. Even though we have several techniques for driving the process, fully automated tools are still missing and we also miss high levels of precision and recall.El principal objetivo de las ontologías en computación es la definición de un vocabulario común para describir conceptos básicos y sus relaciones en un dominio específico. Los principales componentes de las ontologías son clases (conceptos), instancias, propiedades, relaciones y axiomas, entre otros elementos. El proceso de población de ontologías se refiere a la recepción de una ontología como entrada, para luego extraer y relacionar las instancias a cada clase de la ontología desde fuentes de información heterogéneas. En este artículo se realiza una revisión sistemática de literatura sobre la población de ontologías. Se seleccionan artículos de bases de datos especializadas y se crea una pregunta de investigación que permita dirigir la búsqueda de los artículos. Los resultados de la revisión apuntan a que la población de ontologías es un tema de interés para los investigadores. A pesar de que existen muchas técnicas para realizar el proceso, hace falta crear herramientas automáticas y con altos niveles de precision y recall

Web Data Extraction, Applications and Techniques: A Survey

Web Data Extraction is an important problem that has been studied by means of different scientific tools and in a broad range of applications. Many approaches to extracting data from the Web have been designed to solve specific problems and operate in ad-hoc domains. Other approaches, instead, heavily reuse techniques and algorithms developed in the field of Information Extraction. This survey aims at providing a structured and comprehensive overview of the literature in the field of Web Data Extraction. We provided a simple classification framework in which existing Web Data Extraction applications are grouped into two main classes, namely applications at the Enterprise level and at the Social Web level. At the Enterprise level, Web Data Extraction techniques emerge as a key tool to perform data analysis in Business and Competitive Intelligence systems as well as for business process re-engineering. At the Social Web level, Web Data Extraction techniques allow to gather a large amount of structured data continuously generated and disseminated by Web 2.0, Social Media and Online Social Network users and this offers unprecedented opportunities to analyze human behavior at a very large scale. We discuss also the potential of cross-fertilization, i.e., on the possibility of re-using Web Data Extraction techniques originally designed to work in a given domain, in other domains.Comment: Knowledge-based System

Extracción de instancias de una clase desde textos en lenguaje natural independientes del dominio de aplicación

Las ontologías en computación se incluyen en el mundo de la inteligencia artificial y constituyen representaciones formales de un área de conocimiento o dominio. Las ontologías permiten modelar el conocimiento mediante una estructura de conceptos relacionados, lo cual proporciona un vocabulario común y que es de vital importancia para compartir información. La ingeniería ontológica es la disciplina que se encarga del estudio y construcción de herramientas para agilizar el proceso de creación de ontologías desde el lenguaje natural y tiene tres etapas cruciales: aprendizaje de ontologías (Ontology Learning), población de ontologías (Ontology Population) y enriquecimiento de ontologías (Ontology Enrichment). La literatura especializada muestra gran interés por las tres etapas y, para desarrollarlas, utiliza distintos métodos como estadística, extracción de información, procesamiento de lenguaje natural, aprendizaje de máquina (Machine Learning) y combinaciones entre ellos. Sin embargo, algunos problemas subsisten, tales como la dependencia del dominio de aplicación, la carencia de métodos completamente automáticos y la carencia de identificación de instancias de atributos. En consecuencia, el problema que se aborda en esta Tesis Doctoral es la extracción automática de instancias desde el lenguaje natural, sin importar el dominio de aplicación, con el fin de contribuir con el proceso de población de ontologías. En esta Tesis Doctoral se propone un método computacional que utiliza técnicas de extracción de información y procesamiento de lenguaje natural para extraer instancias de una clase y generar como resultado un archivo con una ontología completa en formato OWL, utilizando la herramienta GATE (General Architecture for Text Engineering). Los resultados son prometedores, pues se logra crear ontologías desde cero automáticamente, sin importar el dominio de aplicación y con buenos niveles de precision, recall y F-measure.Abstract: Ontologies in computation belong to artificial intelligence. Ontologies are formal representations of a knowledge area or domain. Ontologies can be used for modeling knowledge by using a structure of related concepts. Such structure provides a common vocabulary and it is crucial for sharing information. Ontological engineering is a discipline for studying and constructing tools for improving the process of ontology creation from natural language. Such a process has three crucial stages: ontology learning, ontology population, and ontology enrichment. The state of the art shows great concern with the three stages, which are developed by using methods like statistics, information extraction, natural language processing, machine learning, and combinations of them. However, some problems still remain—e.g., dependence on the application domain, lack of automation, and lack of attribute instance identification. Consequently, in this Ph.D. Thesis we address the problem of automated extraction of instances from natural language—regardless of the application domain—in order to contribute to the process of ontology population. In this Ph.D. Thesis we propose a computational method by using information extraction and natural language processing technologies in order to extract instances of a class and to generate as an output a file with a complete ontology in OWL format. We use the GATE (General Architecture for Text Engineering) tool for implementing the method. The results are promising, since we automatically create domain-independent ontologies from scratch. Also, our method exhibits satisfactory levels of precision, recall and F-measureDoctorad

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Virtual Heritage: new technologies for edutainment

Cultural heritage represents an enormous amount of information and knowledge. Accessing this treasure chest allows not only to discover the legacy of physical and intangible attributes of the past but also to provide a better understanding of the present. Museums and cultural institutions have to face the problem of providing access to and communicating these cultural contents to a wide and assorted audience, meeting the expectations and interests of the reference end-users and relying on the most appropriate tools available. Given the large amount of existing tangible and intangible heritage, artistic, historical and cultural contents, what can be done to preserve and properly disseminate their heritage significance? How can these items be disseminated in the proper way to the public, taking into account their enormous heterogeneity? Answering this question requires to deal as well with another aspect of the problem: the evolution of culture, literacy and society during the last decades of 20th century. To reflect such transformations, this period witnessed a shift in the museum’s focus from the aesthetic value of museum artifacts to the historical and artistic information they encompass, and a change into the museums’ role from a mere "container" of cultural objects to a "narrative space" able to explain, describe, and revive the historical material in order to attract and entertain visitors. These developments require creating novel exhibits, able to tell stories about the objects and enabling visitors to construct semantic meanings around them. The objective that museums presently pursue is reflected by the concept of Edutainment, Education + Entertainment. Nowadays, visitors are not satisfied with ‘learning something’, but would rather engage in an ‘experience of learning’, or ‘learning for fun’, being active actors and players in their own cultural experience. As a result, institutions are faced with several new problems, like the need to communicate with people from different age groups and different cultural backgrounds, the change in people attitude due to the massive and unexpected diffusion of technology into everyday life, the need to design the visit by a personal point of view, leading to a high level of customization that allows visitors to shape their path according to their characteristics and interests. In order to cope with these issues, I investigated several approaches. In particular, I focused on Virtual Learning Environments (VLE): real-time interactive virtual environments where visitors can experience a journey through time and space, being immersed into the original historical, cultural and artistic context of the work of arts on display. VLE can strongly help archivists and exhibit designers, allowing to create new interesting and captivating ways to present cultural materials. In this dissertation I will tackle many of the different dimensions related to the creation of a cultural virtual experience. During my research project, the entire pipeline involved into the development and deployment of VLE has been investigated. The approach followed was to analyze in details the main sub-problems to face, in order to better focus on specific issues. Therefore, I first analyzed different approaches to an effective recreation of the historical and cultural context of heritage contents, which is ultimately aimed at an effective transfer of knowledge to the end-users. In particular, I identified the enhancement of the users’ sense of presence in VLE as one of the main tools to reach this objective. Presence is generally expressed as the perception of 'being there', i.e. the subjective belief of users that they are in a certain place, even if they know that the experience is mediated by the computer. Presence is related to the number of senses involved by the VLE and to the quality of the sensorial stimuli. But in a cultural scenario, this is not sufficient as the cultural presence plays a relevant role. Cultural presence is not just a feeling of 'being there' but of being - not only physically, but also socially, culturally - 'there and then'. In other words, the VLE must be able to transfer not only the appearance, but also all the significance and characteristics of the context that makes it a place and both the environment and the context become tools capable of transferring the cultural significance of a historic place. The attention that users pay to the mediated environment is another aspect that contributes to presence. Attention is related to users’ focalization and concentration and to their interests. Thus, in order to improve the involvement and capture the attention of users, I investigated in my work the adoption of narratives and storytelling experiences, which can help people making sense of history and culture, and of gamification approaches, which explore the use of game thinking and game mechanics in cultural contexts, thus engaging users while disseminating cultural contents and, why not?, letting them have fun during this process. Another dimension related to the effectiveness of any VLE is also the quality of the user experience (UX). User interaction, with both the virtual environment and its digital contents, is one of the main elements affecting UX. With respect to this I focused on one of the most recent and promising approaches: the natural interaction, which is based on the idea that persons need to interact with technology in the same way they are used to interact with the real world in everyday life. Then, I focused on the problem of presenting, displaying and communicating contents. VLE represent an ideal presentation layer, being multiplatform hypermedia applications where users are free to interact with the virtual reconstructions by choosing their own visiting path. Cultural items, embedded into the environment, can be accessed by users according to their own curiosity and interests, with the support of narrative structures, which can guide them through the exploration of the virtual spaces, and conceptual maps, which help building meaningful connections between cultural items. Thus, VLE environments can even be seen as visual interfaces to DBs of cultural contents. Users can navigate the VE as if they were browsing the DB contents, exploiting both text-based queries and visual-based queries, provided by the re-contextualization of the objects into their original spaces, whose virtual exploration can provide new insights on specific elements and improve the awareness of relationships between objects in the database. Finally, I have explored the mobile dimension, which became absolutely relevant in the last period. Nowadays, off-the-shelf consumer devices as smartphones and tablets guarantees amazing computing capabilities, support for rich multimedia contents, geo-localization and high network bandwidth. Thus, mobile devices can support users in mobility and detect the user context, thus allowing to develop a plethora of location-based services, from way-finding to the contextualized communication of cultural contents, aimed at providing a meaningful exploration of exhibits and cultural or tourist sites according to visitors’ personal interest and curiosity