User Centered and Ontology Based Information Retrieval System for Life Sciences

TL;DR

This paper presents a user-centered, ontology-based information retrieval system for life sciences that enhances document relevance assessment and user interaction through semantic maps, improving exploration and understanding of search results.

Contribution

It introduces a novel request method and environment that use ontology annotations and semantic maps to improve relevance assessment and user interaction in life sciences information retrieval.

Findings

Enhanced relevance assessment with ontology annotations

Interactive semantic maps for data exploration

Improved user understanding of search results

Abstract

Because of the increasing number of electronic data, designing efficient tools to retrieve and exploit documents is a major challenge. Current search engines suffer from two main drawbacks: there is limited interaction with the list of retrieved documents and no explanation for their adequacy to the query. Users may thus be confused by the selection and have no idea how to adapt their query so that the results match their expectations. This paper describes a request method and an environment based on aggregating models to assess the relevance of documents annotated by concepts of ontology. The selection of documents is then displayed in a semantic map to provide graphical indications that make explicit to what extent they match the user's query; this man/machine interface favors a more interactive exploration of data corpus.