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

Bio-based composites from stone groundwood applied to new product development

This paper deals with the product design, engineering, and material selection intended for the manufacturing of an eco-friendly chair. The final product is expected to combine design attributes with technical and legal feasibility with the implementation of new bio-based materials. Considering the industrial design, a range of objectives and trends were determined after setting the market requirements, and the final concept was proposed and modeled. The product geometry, production technology, and legal specifications were the input data for product engineering. The material selection was based on the technical requirements. Polypropylene (PP) composite materials based on coupled-fiberglass, sized-fiberglass, and coupled-stone ground wood reinforcements were prepared and characterized. Final formulations based on these PP composites are proposed and justified