Innovation typology in tourism

Innovation is a research topic with a broad tradition. However, learning processes, from which innovations emerge, and the dynamics of change and development have traditionally been studied in relation with the manufacturing sector. Moreover, the objects of study have been usually process and tangible product innovations. Although recently researchers have focused their attention in other sectors, more research on service innovation should be carried out. Furthermore, regarding innovation in tourism, there is a need to adapt generic theories to the tourism sector and to contribute with new ideas. In order to find out, which are the origins of innovation processes, it is necessary to look into two fundamental subjects that are inherent to innovation, which are learning and interaction. Both are closely related. The first appears to be an intrinsic condition of individuals. Moreover, it can also be identified in organizations. Thus, learning allows individuals as well as organizations to develop. However, learning and development is not possible without taking the environment into account. Hence, it is necessary that interactions take place between individuals, groups of individuals, organizations, etc. Furthermore, the concept of interaction implies the transfer of knowledge, which is the basis for innovations. The purposes of this master thesis are to study in detail several of these topics and to develop a conceptual framework for the research on innovation in tourism

Informed recommender: basing recommendations on consumer product reviews

Recommender systems attempt to predict items in which a user might be interested, given some information about the user's and items' profiles. Most existing recommender systems use content-based or collaborative filtering methods or hybrid methods that combine both techniques (see the sidebar for more details). We created Informed Recommender to address the problem of using consumer opinion about products, expressed online in free-form text, to generate product recommendations. Informed recommender uses prioritized consumer product reviews to make recommendations. Using text-mining techniques, it maps each piece of each review comment automatically into an ontology

Recommender System Based on Consumer Product Reviews

Consumer reviews, opinions and shared experiences in the use of a product is a powerful source of information about consumer preferences that can be used in recommender systems. Despite the importance and value of such information, there is no comprehensive mechanism that formalizes the opinions selection and retrieval process and the utilization of retrieved opinions due to the difficulty of extracting information from text data. In this paper, a new recommender system that is built on consumer product reviews is proposed. A prioritizing mechanism is developed for the system. The proposed approach is illustrated using the case study of a recommender system for digital cameras

Studies about the atomic capabilities concept for linear control systems in physical multi-agent environments

This paper shows the impact of the atomic capabilities concept to include control-oriented knowledge of linear control systems in the decisions making structure of physical agents. These agents operate in a real environment managing physical objects (e.g. their physical bodies) in coordinated tasks. This approach is presented using an introspective reasoning approach and control theory based on the specific tasks of passing a ball and executing the offside manoeuvre between physical agents in the robotic soccer testbed. Experimental results and conclusions are presented, emphasising the advantages of our approach that improve the multi-agent performance in cooperative systems