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

Entrepreneurship, ties and relational networks: the case of a public-private cross-border tourism product

The thesis aims to understand the processes of entrepreneurship that try to create businesses or products with a high degree of complexity. This complexity comes from the fact that these products or initiatives can only be viable with the concurrence of a large number of heterogeneous actors (public, private, from different regions, etc..) which interact in a relational context. A case with these characteristics is the Camí dels Bons Homes. The thesis analyzes the evolution of the relational network from the point of view of its structure and content of its links. The results show and explain the observed changes in the network structure and the changes in the ties content. This analysis of the content of ties contributes to a new systematization and operationalization of ties’ content. Moreover this analysis takes in account negative ties, a less discussed issue in literature.