238 research outputs found
Features of an Error Correction Memory to Enhance Technical Texts Authoring in LELIE
International audienceIn this paper, we investigate the notion of error correction memory applied to technical texts. The main purpose is to introduce flexibility and context sensitivity in the detection and the correction of errors related to Constrained Natural Language (CNL) principles. This is realized by enhancing error detection paired with relatively generic correction patterns and contextual correction recommendations. Patterns are induced from previous corrections made by technical writers for a given type of text. The impact of such an error correction memory is also investigated from the point of view of the technical writer"s cognitive activity. The notion of error correction memory is developed within the framework of the LELIE project an experiment is carried out on the case of fuzzy lexical items and negation, which are both major problems in technical writing. Language processing and knowledge representation aspects are developed together with evaluation directions
Argument Compound Mining in Technical Texts: linguistic structures, implementation and annotation schemas
International audienceIn this paper, we motivate and develop the linguistic characteristics of argument compounds. The discourse structures that refine or elaborate arguments are analysed and their cognitive impact in argumentation is developed. An implementation is then presented. It is carried out in Dislog on the TextCoop platform. Dislog allows high level specifications in logic for fast and easy prototyping at a high level of linguistic adequacy. Elements of an indicative evaluation are provided
An exploration of the relatedness problem between arguments: combining the generative lexicon with inference
International audienceGiven a controversial issue, argument mining from natural language texts is extremely challenging: domain knowledge is often required together with appropriate forms of inferences. This contribution explores the use of the Generative Lexicon viewed as both a lexicon and a domain knowledge representation
Discourse structure analysis for requirement mining
International audienceIn this work, we first introduce two main approaches to writing requirements and then propose a method based on Natural Language Processing to improve requirement authoring and the overall coherence, cohesion and organization of requirement documents. We investigate the structure of requirement kernels, and then the discourse structure associated with those kernels. This will then enable the system to accurately extract requirements and their related contexts from texts (called requirement mining). Finally, we relate a first experimentation on requirement mining based on texts from seven companies. An evaluation that compares those results with manually annotated corpora of documents is given to conclude
Construction de réponses coopératives : du corpus à la modélisation informatique
Les stratégies utilisées pour la recherche d’information dans le cadre du Web diffèrent d’un moteur de recherche à un autre, mais en général, les résultats obtenus ne répondent pas directement et simplement à la question posée. Nous présentons une stratégie qui vise à définir les fondements linguistiques et de communication d’un système d’interrogation du Web qui soit coopératif avec l’usager et qui tente de lui fournir la réponse la plus appropriée possible dans sa forme et dans son contenu. Nous avons constitué et analysé un corpus de questions-réponses coopératives construites à partir des sections Foire Aux Questions (FAQ) de différents services Web aux usagers. Cela constitue à notre sens une bonne expérimentation de ce que pourrait être une communication directe en langue naturelle sur le Web. Cette analyse de corpus a permis d’extraire les caractéristiques majeures du comportement coopératif et de construire l’architecture de notre système informatique webcoop, que nous présentons à la fin de cet article.Algorithms and strategies used on the Web for information retrieval differ from one search engine to another, but, in general, results do not lead to very accurate and informative answers. In this paper, we describe our strategy for designing a cooperative question answering system that aims at producing the most appropriate answers to natural language questions. To characterize these answers, we collected a corpus of cooperative question in our opinion answer pairs extracted from Frequently Asked Questions. The analysis of this corpus constitutes a good experiment on what a cooperative natural language communication on the Web could be. This analysis allows for the elaboration of a general architecture for our cooperative question answering system webcoop, which we present at the end of this paper
LELIE - An Intelligent Assistant for Improving Requirement Authoring
International audienceWhen writing or revising a set of requirements, or any technical document, it is particularly challenging to make sure that texts read easily and are unambiguous for any domain actor. Experience shows that even with several levels of proofreading and validation, most texts still contain a large number of language errors (lexical, grammatical, style, business, w.r.t. authoring recommendations), and lack of overall cohesion and coherence. LELIE [a] has been designed to track these errors and, whenever possible, to suggest corrections. LELIE has obviously an impact on the technical writer behavior: LELIE rapidly becomes an essential and user-friendly authoring companion
Vers la modélisation des processus sociotechniques : analyse du processus collectif de conception des procédures d'une entreprise
International audienceCe papier présente l'analyse d'un processus collectif de conception de documents procéduraux en contexte industriel. Nous mobilisons un outil de modélisation qui permet de synthétiser la structure organisationnelle globale du processus sociotechnique et d'interpréter les rôles individuels des acteurs qui y participent. En pratique, la modélisation proposée est basée sur la traduction de la procédure générale définissant le processus de mise à jour des procédures de l'entreprise. Notre modèle est une traduction des actions de ce processus, sous la forme de nœuds et de liens qui définissent un graphe. Les résultats permettent de montrer que cette modélisation est un outil puissant pour l'analyse du processus étudié. Les entités participant au processus sont clairement définies. Leurs relations dans la chaîne d'action qui compose le processus sont explicitées. Leurs positions structurales sont établies sur la base d'une méthode algorithmique validée. Sur la base de ces résultats, nous concluons sur des perspectives possibles à ce travail
Features of an Error Correction Memory to Enhance Technical Texts Authoring in LELIE
In this paper, we investigate the notion of error correction memory applied to technical texts. The main purpose is to introduce flexibility and context sensitivity in the detection and the correction of errors related to Constrained Natural Language (CNL) principles. This is realized by enhancing error detection paired with relatively generic correction patterns and contextual correction recommendations. Patterns are induced from previous corrections made by technical writers for a given type of text. The impact of such an error correction memory is also investigated from the point of view of the technical writer's cognitive activity. The notion of error correction memory is developed within the framework of the LELIE project an experiment is carried out on the case of fuzzy lexical items and negation, which are both major problems in technical writing. Language processing and knowledge representation aspects are developed together with evaluation directions.URL: http://ijkcdt.net/xml/05535/05535.pd
Some Challenges of Advanced Question-Answering: an Experiment with How-to Questions
PACLIC / The University of the Philippines Visayas Cebu College Cebu City, Philippines / November 20-22, 200
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