Product-Advisory on the Web: An Information Extraction Approach

S. Schmidt, S. Mandl, B. Ludwig, and H. Stoyan (Germany)


Information Extraction, artificial intelligence, product advisory


We present a novel approach how to extract technical constraints of a technical product given the user’s intended application from the web. This is especially useful in domains where products and applications undergo a steady innovation. The user does not have to be a domain expert to find adequate products anymore. We evaluated our system in the domain of digital cameras and extracted technical constraints such as a short exposure time when the user is mainly interested in sports photography. The extracted constraints are meaningful, if there are enough search results from the search engine for the user’s application and the product domain.

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