Peut-on évaluer les outils d'acquisition de connaissances à partir de textes ?

National audienceMalgré les années de recul et d'expériences accumulées, il est difficile de se faire une idée claire de l'état d'avancement des recherches en acquisition de connaissances à partir de textes. Le manque de protocoles d'évaluation ne facilite pas la comparaison des résultats. Nous développons, dans cet article, la question de l'évaluation des outils d'acquisition de terminologies et d'ontologies en soulignant les princi- pales difficultés et en décrivant nos premières propositions dans ce domaine

Dispatching Requests for Agent-Based Online Vehicle Routing Problems with Time Windows

Vehicle routing problems are highly complex problems. The proposals to solve them traditionally concern the optimization of conventional criteria, such as the number of mobilized vehicles and the total costs. However, in online vehicle routing problems, the optimization of the response time to the connected travelers is at least as important as the optimization of the classical criteria. Multi-agent systems on the one hand and greedy insertion heuristics on the other are among the most promising approaches to this end. In this paper, we propose a multi-agent system coupled with a regret insertion heuristic. We focus on the real-time dispatching of the travelers\u27 requests to the vehicles and its efficiency. A dispatching protocol determines which agents perform the computation to answer the travelers\u27 requests. We evaluate three dispatching protocols: centralized, decentralized and hybrid. We compare them experimentally based on their response time to online travelers. Two computational types are implemented: a sequential implementation and a distributed implementation. The results show the superiority of the centralized dispatching protocol in the sequential implementation (32.80% improvement in average compared to the distributed dispatching protocol) and the superiority of the hybrid dispatching protocol in the distributed implementation (59.66% improvement in average, compared with the centralized dispatching protocol)

Generic model for resource allocation in transportation: Application to urban parking management

In this paper, we define the online localized resource allocation problem, especially relevant for modeling transportation applications. The problem modeling takes into account simultaneously the geographical location of consumers and resources together with their online nondeterministic appearance. We use urban parking management as an illustration of this problem. In fact, urban parking management is an online localized resource allocation problem, where the question is how to find an efficient allocation of parking spots to drivers, while they all have dynamic geographical positions and appear nondeterministically. We define this problem and propose a multiagent system to solve it. The objective of the system is to decrease, for private vehicles drivers, the parking spots search time. The drivers are organized in communities and share information about spots availability. We have defined two cooperative models and compared them: a fully cooperative model, where agents share all the available information, and a 'coopetitive' model, where drivers do not share information about the spot that they have chosen. Results show the superiority of the first model

Evaluating semantic classes used for ontology building and learning from texts

International audienceA large effort has been devoted to the development of ontology building tools but it is still difficult to assess their strengths and limitations. Proposed evaluations are hardly reproducible and there is a lack of well- accepted protocols and data. In this paper, we propose to decompose the evaluation of ontology acquisition process into independent functionalities. We focus on the evaluation of semantic class acquisition considered as a main step in the ontology acquisition process. We propose an approach to automatically evaluate semantic classes of ontologies that offer lexical entries for concepts. It is based on the comparative paradigm (to a gold standard). Its main focus is to compare how similar the generated semantic classes are to the gold standard concerning the disposition of concepts frontiers. This comparison relies on the lexical level and on the hierarchical structure of the "gold" concepts. The propositions are implemented, two experiments are settled on different domains and prove that the measures give a more accurate information on quality of systems' performances

Une cartographie de domaine pour guider la construction d'une ressource sémantique

National audienceDans cet article, nous proposons une méthode d'aide à l'ingénieur de la connaissance pour construire un modèle sémantique (terminologie ou ontologie) pour un domaine particulier. Cette méthode repose sur l'utilisation de ressources sémantiques disponibles pour représenter une vue synthétique du domaine à modéliser. La méthode proposée se fonde sur les phases suivantes : modularisation, alignement et raisonnement. Le texte sert de support aux différentes phases

Alignment-based Partitioning of Large-scale Ontologies

Ontology alignment is an important task for information integration systems that can make different resources, described by various and heterogeneous ontologies, interoperate. However very large ontologies have been built in some domains such as medicine or agronomy and the challenge now lays in scaling up alignment techniques that often perform complex tasks. In this paper, we propose two partitioning methods which have been designed to take the alignment objective into account in the partitioning process as soon as possible. These methods transform the two ontologies to be aligned into two sets of blocks of a limited size. Furthermore, the elements of the two ontologies that might be aligned are grouped in a minimal set of blocks and the comparison is then enacted upon these blocks. Results of experiments performed by the two methods on various pairs of ontologies are promising

Distributed agent-based traffic simulations

Modeling and simulation play an important role in transportation networks analysis. With the widespread of personalized real-time information sources, it is relevant for the simulation model to be individual-centered. The agent-based simulation is the most promising paradigm in this context. However, representing the movements of realistic numbers of travelers within reasonable execution times requires significant computational resources. It also requires relevant methods, architectures and algorithms that respect the characteristics of transportation networks. In this paper, we tackle the problem of using high-performance computing for agent-based traffic simulations. To do so, we define two generic agent-based simulation models, representing the existing sequential agent-based traffic simulations. The first model is macroscopic, in which travelers do not interact directly and use a fundamental diagram of traffic flow to continuously compute their speeds. The second model is microscopic, in which travelers interact with their neighbors to adapt their speeds to their surrounding environment. We define patterns to distribute these simulations in a high-performance environment. The first distributes agents equally between available computation units. The second pattern splits the environment over the different units. We finally propose a diffusive method to dynamically balance the load between units during execution. The results show that agent-based distribution is more efficient with macroscopic simulations, with a speedup of 6 compared to the sequential version, while environmentbased distribution is more efficient with microscopic simulations, with a speedup of 14. Our diffusive load-balancing algorithm improves further the performance of the environment based approach by 150%

Construction collaborative d'une Ressource Termino-Ontologique (RTO) pour le droit des collectivités territoriales

National audienceLa construction collaborative de ressources sémantiques est devenue un domaine de recherche en plein essor et une solution pratique notamment dans les grands projets de construction à grande échelle. En effet, contrairement à une construction centralisée, une construction collaborative permet de tracer les différents points de vue et de mettre en place une modélisation consensuelle. De plus, la construction collaborative permet de faire communiquer des acteurs aux profils différents dans une approche distribuée. Nous présentons dans ce papier une construction collaborative d'une RTO mise en place dans le projet LégiLocal, qui vise à proposer des fonctionnalités d'accès à l'information juridique locale pour les citoyens et les élus et personnels de mairie. Dans ce projet, une RTO est nécessaire pour permettre un accès sémantique ciblé qui prend en compte les aspects de réglementation locale en rapport avec le droit. La construction de cette RTO nécessite la collaboration de plusieurs acteurs du projet, avec des profils différents : des ingénieurs de la connaissance, des terminologues et des juristes (spécialistes en droit des collectivités). Nous terminons en présentant les deux scénarios de collaboration que nous mettons en place pour la construction de cette RTO dans le cadre du projet LégiLocal

Evaluation des outils terminologiques : enjeux, difficultés et propositions

International audienceCas particulier parmi les tâches de traitement automatique des langues, l'acquisition terminologique n'a guère fait l'objet d'évaluation systématique jusqu'à présent. Les campagnes qui ont eu lieu sont récentes et limitées. Il est cependant nécessaire de conduire des évaluations pour faire le bilan des recherches passées, mesurer les progrès accomplis et les angles morts. Cet article défend l'idée qu'on peut définir des protocoles d'évaluation comparative même pour des tâches complexes comme la terminologie computationnelle. La méthode proposée s'appuie sur une décomposition des outils d'analyse terminologique en fonctionnalités élémentaires ainsi que sur la définition de mesures de précision et de rappel adaptées aux problèmes terminologiques, à savoir la complexité des produits terminologiques, la dépendance aux applications, le rôle de l'interaction avec l'utilisateur et la variabilité des terminologies de référence

Détection et classification non supervisées de relations sémantiques dans des articles scientifiques

International audienceDans cet article, nous abordons une tâche encore peu explorée, consistant à extraire automatiquement l'état de l'art d'un domaine scientifique à partir de l'analyse d'articles de ce domaine. Nous la ramenons à deux sous-tâches élémentaires : l'identification de concepts et la reconnaissance de relations entre ces concepts. Une extraction terminologique permet d'identifier les concepts candidats, qui sont ensuite alignés à des ressources externes. Dans un deuxième temps, nous cherchons à reconnaître et classifier automatiquement les relations sémantiques entre concepts de manière non-supervisée, en nous appuyant sur différentes techniques de clustering et de biclustering. Nous mettons en oeuvre ces deux étapes dans un corpus extrait de l'archive de l'ACL Anthology. Une analyse manuelle nous a permis de proposer une typologie des relations sémantiques, et de classifier un échantillon d'instances de relations. Les premières évaluations suggèrent l'intérêt du biclustering pour détecter de nouveaux types de relations dans le corpus. ABSTRACT Unsupervised Classification of Semantic Relations in Scientific Papers In this article, we tackle the yet unexplored task of automatically building the "state of the art" of a scientific domain from a corpus of research papers. This task is defined as a sequence of two basic steps : finding concepts and recognizing the relations between them. First, candidate concepts are identified using terminology extraction, and subsequently linked to external resources. Second, semantic relations between entities are categorized with different clustring and biclustering algorithms. Experiences were carried out on the ACL Anthology Corpus. Results are evaluated against a hand-crafted typology of semantic relations and manually categorized examples. The first results indicate that biclustering techniques may indeed be useful for detecting new types of relations. MOTS-CLÉS : analyse de la littérature scientifique, extraction de relations, clustering, biclustering