SMILK, linking natural language and data from the web
This work addresses knowledge extraction and text annotation for web users, but it is incremental as it builds on existing NLP and ontology methods.
The researchers tackled linking natural language and web data by creating an ontology and populating a knowledge base, with evaluation showing improved brand-related information retrieval in cosmetics.
As part of the SMILK Joint Lab, we studied the use of Natural Language Processing to: (1) enrich knowledge bases and link data on the web, and conversely (2) use this linked data to contribute to the improvement of text analysis and the annotation of textual content, and to support knowledge extraction. The evaluation focused on brand-related information retrieval in the field of cosmetics. This article describes each step of our approach: the creation of ProVoc, an ontology to describe products and brands; the automatic population of a knowledge base mainly based on ProVoc from heterogeneous textual resources; and the evaluation of an application which that takes the form of a browser plugin providing additional knowledge to users browsing the web.