Semantic-based information retrieval in support of concept design

This research is motivated by the realisation that semantic technology can be used to develop computational tools in support of designers’ creativity by focusing on the inspirational stage of design. The paper describes a semantic-based image retrieval tool developed for the needs of concept cars designers from two renowned European companies. It is created to help them find and interpret sources of inspiration. The core innovation of the tool is its ability to provide a degree of diversity, ambiguity and uncertainty in the information gathering and idea generation process. The tool is based on the assumption that there is a semantic link between the images in a web page and the text around them. Furthermore, it uses the idea that the more frequently a term occurs in a document and the fewer documents it occurs in, the more representative this term is of that document. The new contribution is linking the most meaningful words in a document with ontological concepts, and then finding the most powerful set of concepts representing that document and consequently the images in it. This is based on the observation that monosemic words (with a single meaning) are more domain-oriented than polysemic ones (that have multiple meanings), and provide a greater amount of domain information. The tool tags images by first processing all significant words in the text around them, extracting all keywords and key phrases in it, ranking them according to their significance, and linking them to ontological concepts. It generates a set of concept numbers for each text, which is then used to retrieve information in a process called semantic expansion, where a keyword query is also processed semantically. The proposed approach is illustrated with examples using the tool developed for the needs of Stile Bertone and Fiat, Italy, two of the industrial partners in the TRENDS project sponsored by the European Community