Combining chemical structure data with unstructured data for predictive analytics in a cognitive system
Abstract:
According to embodiments of the present invention, an entity may be represented by an unstructured feature vector comprising a plurality of features extracted from unstructured data using semantic analysis and a structural feature vector comprising a plurality of features from chemical structure data. A similarity matrix may be used to compare entities and generate a similarity score, based on both the unstructured feature vector and the structural feature vector for each entity. In some aspects, a user may enter a query (from which a chemical structural feature vector is dynamically generated) to compare against entities having unstructured and/or structural feature vectors, stored in a database.
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