Human-Centric Ontology-Based Context Modelling In Tourism

A lot of work has been done up to now in the so called context-aware research field on the one hand and on the ontology research field on the other. Research has been conducted both considering context-awareness and ontology as clearly distinct research disciplines and also utilizing ontologies as a tool for context management. However, context-based applications have only been possible at a laboratory environment so far and they have always worked under very certain, pre-established pre-requisites in a not very stable nor efficient manner, which actually does not fulfil the nature of Ubiquitous Computing vision. Representation and use of context plays a crucial role in many modern IT applications. The ability to process contextual information and perform context-based reasoning is essential not only for mobile and ubiquitous computing systems, but also for a wide range of tourism applications. This paper presents a novel semantic-based human-centric approach to the notion of context that represents an attempt to make Contextual Computing services available to the general public

Ontology Network for Social Network Analysis in a Knowledge Management Context

Organizational knowledge is one of the most valuable assets that companies own today. For several decades organizations have been developing strategies to manage knowledge with particular emphasis on tacit knowledge discovery. The particular dynamic that presents the evolution and transfer of tacit knowledge is closely tied to the relations between people. For this reason, Social Network Analysis (SNA) can be a powerful tool to support a Knowledge Management (KM) initiative. Despite usefulness recognition of SNA techniques within KM processes, there is still remains the initial problem of data collection and representation (problem shared by both initiatives). The aim of this paper is to analyze an ontology network usefulness to obtain the necessary knowledge structure to feed the SNA-KM integration architecture proposed.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Ontology Network for Social Network Analysis in a Knowledge Management Context

Organizational knowledge is one of the most valuable assets that companies own today. For several decades organizations have been developing strategies to manage knowledge with particular emphasis on tacit knowledge discovery. The particular dynamic that presents the evolution and transfer of tacit knowledge is closely tied to the relations between people. For this reason, Social Network Analysis (SNA) can be a powerful tool to support a Knowledge Management (KM) initiative. Despite usefulness recognition of SNA techniques within KM processes, there is still remains the initial problem of data collection and representation (problem shared by both initiatives). The aim of this paper is to analyze an ontology network usefulness to obtain the necessary knowledge structure to feed the SNA-KM integration architecture proposed.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Ontology Network for Social Network Analysis in a Knowledge Management Context

Organizational knowledge is one of the most valuable assets that companies own today. For several decades organizations have been developing strategies to manage knowledge with particular emphasis on tacit knowledge discovery. The particular dynamic that presents the evolution and transfer of tacit knowledge is closely tied to the relations between people. For this reason, Social Network Analysis (SNA) can be a powerful tool to support a Knowledge Management (KM) initiative. Despite usefulness recognition of SNA techniques within KM processes, there is still remains the initial problem of data collection and representation (problem shared by both initiatives). The aim of this paper is to analyze an ontology network usefulness to obtain the necessary knowledge structure to feed the SNA-KM integration architecture proposed.Sociedad Argentina de Informática e Investigación Operativa (SADIO

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

Semantic recommender systems Provision of personalised information about tourist activities.

Aquesta tesi estudia com millorar els sistemes de recomanació utilitzant informació semàntica sobre un determinat domini (en el cas d’aquest treball, Turisme). Les ontologies defineixen un conjunt de conceptes relacionats amb un determinat domini, així com les relacions entre ells. Aquestes estructures de coneixement poden ser utilitzades no només per representar d'una manera més precisa i refinada els objectes del domini i les preferències dels usuaris, sinó també per millorar els procediments de comparació entre els objectes i usuaris (i també entre els mateixos usuaris) amb l'ajuda de mesures de similitud semàntica. Les millores al nivell de la representació del coneixement i al nivell de raonament condueixen a recomanacions més precises i a una millora del rendiment dels sistemes de recomanació, generant nous sistemes de recomanació semàntics intel•ligents. Les dues tècniques bàsiques de recomanació, basades en contingut i en filtratge col•laboratiu, es beneficien de la introducció de coneixement explícit del domini. En aquesta tesi també hem dissenyat i desenvolupat un sistema de recomanació que aplica els mètodes que hem proposat. Aquest recomanador està dissenyat per proporcionar recomanacions personalitzades sobre activitats turístiques a la regió de Tarragona. Les activitats estan degudament classificades i etiquetades d'acord amb una ontologia específica, que guia el procés de raonament. El recomanador té en compte molts tipus diferents de dades: informació demogràfica, les motivacions de viatge, les accions de l'usuari en el sistema, les qualificacions proporcionades per l'usuari, les opinions dels usuaris amb característiques demogràfiques similars o gustos similars, etc. Un procés de diversificació que calcula similituds entre objectes s'aplica per augmentar la varietat de les recomanacions i per tant augmentar la satisfacció de l'usuari. Aquest sistema pot tenir un impacte positiu a la regió en millorar l'experiència dels seus visitants.Esta tesis estudia cómo mejorar los sistemas de recomendación utilizando información semántica sobre un determinado dominio, en el caso de este trabajo el Turismo. Las ontologías definen un conjunto de conceptos relacionados con un determinado dominio, así como las relaciones entre ellos. East estructuras de conocimiento pueden ser utilizadas no sólo para representar de una manera más precisa y refinada los objetos del dominio y las preferencias de los usuarios, sino también para aplicar mejor los procedimientos de comparación entre los objetos y usuarios (y también entre los propios usuarios) con la ayuda de medidas de similitud semántica. Las mejoras al nivel de la representación del conocimiento y al nivel de razonamiento conducen a recomendaciones más precisas y a una mejora del rendimiento de los sistemas de recomendación, generando nuevos sistemas de recomendación semánticos inteligentes. Las dos técnicas de recomendación básicas, basadas en contenido y en filtrado colaborativo, se benefician de la introducción de conocimiento explícito del dominio. En esta tesis también hemos diseñado y desarrollado un sistema de recomendación que aplica los métodos que hemos propuesto. Este recomendador está diseñado para proporcionar recomendaciones personalizadas sobre las actividades turísticas en la región de Tarragona. Las actividades están debidamente clasificadas y etiquetadas de acuerdo con una ontología específica, que guía el proceso de razonamiento. El recomendador tiene en cuenta diferentes tipos de datos: información demográfica, las motivaciones de viaje, las acciones del usuario en el sistema, las calificaciones proporcionadas por el usuario, las opiniones de los usuarios con características demográficas similares o gustos similares, etc. Un proceso de diversificación que calcula similitudes entre objetos se aplica para generar variedad en las recomendaciones y por tanto aumentar la satisfacción del usuario. Este sistema puede tener un impacto positivo en la región al mejorar la experiencia de sus visitantes.This dissertation studies how new improvements can be made on recommender systems by using ontological information about a certain domain (in the case of this work, Tourism). Ontologies define a set of concepts related to a certain domain as well as the relationships among them. These knowledge structures may be used not only to represent in a more precise and refined way the domain objects and the user preferences, but also to apply better matching procedures between objects and users (or between users themselves) with the help of semantic similarity measures. The improvements at the knowledge representation level and at the reasoning level lead to more accurate recommendations and to an improvement of the performance of recommender systems, paving the way towards a new generation of smart semantic recommender systems. Both content-based recommendation techniques and collaborative filtering ones certainly benefit from the introduction of explicit domain knowledge. In this thesis we have also designed and developed a recommender system that applies the methods we have proposed. This recommender is designed to provide personalized recommendations of touristic activities in the region of Tarragona. The activities are properly classified and labelled according to a specific ontology, which guides the reasoning process. The recommender takes into account many different kinds of data: demographic information, travel motivations, the actions of the user on the system, the ratings provided by the user, the opinions of users with similar demographic characteristics or similar tastes, etc. A diversification process that computes similarities between objects is applied to produce diverse recommendations and hence increase user satisfaction. This system can have a beneficial impact on the region by improving the experience of its visitors