Violaine Prince

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A large part of the time allocated to software maintenance is dedicated to the program comprehension. Many approaches that uses the program structure or the external documentation have been created to assist program comprehension. However, the identifiers of the program are an important source of information that is still not widely used for this purpose.(More)
Information retrieval needs to match relevant texts with a given query. Selecting appropriate parts is useful when documents are long, and only portions are interesting to the user. In this paper, we describe a method that extensively uses natural language techniques for text segmentation based on topic change detection. The method requires a NLP-parser and(More)
Synonymy is a pivot relation in NLP but remains problematic. Putting forward, we introduce the notion of relative synonymy, to circumvent some diÆculties among which possible polysemy and contextual interpretation. In the framework of conceptual vectors, it is then possible to formalize test functions for synonymy and to experiment their use in thematic(More)
This paper deals with an acronym/definition extraction approach from textual data (corpora) and the disambiguation of these definitions (or expansions). Both steps of our global process of acquisition and management of acronyms are precisely described. The first step consists in using markers such as brackets to identify expansion candidates. The alignment(More)
The originality of this work leads in tackling text compression using an unsupervised method, based on a deep linguistic analysis, and without resorting on a learning corpus. This work presents a system for dependent tree pruning, while preserving the syntactic coherence and the main informational contents, and led to an operational software, named COLIN.(More)
This paper describes a system facilitating information retrieval in a set of textual documents by tackling the automatic titling and subtitling issue. Automatic titling here consists in extracting relevant noun phrases from texts as candidate titles. An original approach combining statistical criteria and noun phrases positions in the text helps collecting(More)
In this paper, we focus on lexical semantics, a key issue in Natural Language Processing (NLP) that tends to converge with conceptual Knowledge Representation (KR) and ontologies. When ontological representation is needed, hyperonymy, the closest approximation to the is-a relation, is at stake. In this paper we describe the principles of our vector model(More)
We propose an automated text summarization through sentence compression. Our approach uses constituent syntactic function and position in the sentence syntactic tree. We first define the idea of a constituent as well as its role as an information provider, before analyzing contents and discourse consistency losses caused by deleting such a constituent. We(More)