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A domain specific ESA inspired approach for document semantic description

Mazzola, Luca; Siegfried, Patrick; Waldis, Andreas; Kaufmann, Michael; Denzler, Alexander

Document semantic similarity is a current research field, in particular when the concept-based characterization (or signature) of the entity should be extracted from its content.

Similarity measure and its usage for document retrieval and ranking.

In this work, our research goal is an expert system for job placement, based on skills, capabilities, areas of expertise, present in someone's curriculum vitae and personal preferences. The challenge is to take into account all the personal educational experiences (formal, informal, and on-the-job), but also work-related know-how, to create a concept based on the person. This will allow a reasoned matching process with existing job positions, but also towards additional educational experience for profile improvement.

Taking inspiration from the explicit semantic analysis (ESA), we developed a domain-specific approach to semantically characterize documents and compare them to similarity.

Thanks to an enriching and a filtering process, we transform the general purpose

The domain is as defined as a German knowledge base for educational experiences and for job offers.

Initial testing with a small set of documents. There are still issues that we would like to tackle in the next project steps.

Alongside, we have other research directions. We are going to take a look into the account of the theory for the optimization of our solution to a multi-lingual context.

+ ID der Publikation: hslu_56936 + Art des Beitrages: Wissenschaftliche Medien + Sprache: Englisch + Letzte Aktualisierung: 2019-03-25 11:05:48
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