The DELICES project: Indexing scientific literature through semantic expansion

TL;DR

The DELICES project aims to enhance scientific literature indexing by leveraging semantic relations, thereby improving search relevance and expanding coverage beyond traditional keyword-based methods.

Contribution

It introduces a novel approach that uses semantic representations to enrich and extend indexing of scientific articles, surpassing current limitations.

Findings

Improved relevance of keyphrase extraction

Extended indexing with semantically similar terms

Enhanced retrieval performance

Abstract

Scientific digital libraries play a critical role in the development and dissemination of scientific literature. Despite dedicated search engines, retrieving relevant publications from the ever-growing body of scientific literature remains challenging and time-consuming. Indexing scientific articles is indeed a difficult matter, and current models solely rely on a small portion of the articles (title and abstract) and on author-assigned keyphrases when available. This results in a frustratingly limited access to scientific knowledge. The goal of the DELICES project is to address this pitfall by exploiting semantic relations between scientific articles to both improve and enrich indexing. To this end, we will rely on the latest advances in semantic representations to both increase the relevance of keyphrases extracted from the documents, and extend indexing to new terms borrowed from semantically similar documents.