Using Wikipedia concepts and frequency in language to extract key terms from support documents

In this paper, we present a new key term extraction system able to handle with the particularities of “support documents”. Our system takes advantages of frequency-based and thesaurus-based approaches to recognize two different classes of key terms. On the one hand, it identifies multi-domain key terms of the collection using Wikipedia as knowledge resource. On the other hand, the system extracts specific key terms highly related with the context of a support document. We use the frequency in language as a criterion to detect and rank such terms. To prove the validity of our system we have designed a set of experiment using a Frequently Asked Questions (FAQ) collection of documents. Since our approach is generic, minor modifications should be undertaken to adapt the system to other kind of support documents. The empirical results evidence the validity of our approach.

► Able to deal with the specific characteristics of the support documents.
► Hybrid system based on frequency-based and thesaurus-based approaches.
► Frequency in language of terms as a criterion to detect support domain dependant key terms.
► Dictionary of concepts drawn from Wikipedia designed to detect multidomain key terms.