bluuebunny/crossref_metadata_2025_split huggingface dataset:
A question‐answering system for the French Yellow Pages
Authors: Herman P. , Sabah G. , Vilnat A. 
Published: April 2007

This paper describes a dialogue‐based system which is intended as an intelligent natural language interface to the French Yellow Pages. We do not assume that the user knows how the Yellow Pages are organized, and we paraphrase his request, if necessary, so as to better search for the desired information. We do, however, assume that the reason the user is on line is to find an address and phone number for some supplier.There are three basic modules used in our system: parser, dialogue manager, and generator. The first two exist (and are constantly being extended); the generation module is still only a set of functional specifications which will be outlined later in this article.
Processing of unknown words in a natural language question‐answering system
Authors: Fournier J. P. , Herman P. , Sabah G. , Vilnat A. , Burgaud N. , Gilloux M. 
Published: April 2007

We have developed a prototype of a question‐answering system which is intended to interact with an untrained user to give him information about the Yellow Pages of the French phone directory. We don't detail here the description of the system, because it is done in another paper in the same issue: “A question‐answering system for the French Yellow Pages”.In this paper we first present a typology of the different kinds of unforeseen situations the system may have to handle while interacting with an untrained user. Then, we detail different strategies we have developed to solve these problems, more specifically to correct misspelt words and to deal with the properly typed, but unknown, words. These mechanisms have been integrated into the parser, and try to maintain, as long as possible, its determinism.
Machine learning research at the Laboratoire de Recherche en Informatique at Orsay, France
Authors: Cornuejols Antoine P. 
Published: April 2007

This article provides a brief account with sketchy technical details of the major directions in machine learning research done at the Laboratoire de recherche en informatique (LRI) at Orsay University in France. References contain publications giving details on the projects described in this paper and on closely related works.Our research has several objectives: looking for a sound basis of the process of generalization from examples, using this to study conceptual clustering with automatic synthesis of descriptors; studying the nature and goodness of an explanation in the context of apprentice systems; and developing experimental learning systems based on these principles applied to various practical domains. The approach taken by our research group has evolved with time but is still mainly based on learning of concepts from examples using logic representations and techniques. It corresponds to a major goal of our group: to give a clear and rigorous picture, if not a theory, of the topics under investigation. Several aspects are persued at the same time: concept learning by generalization, developments of explanation‐based learning techniques, analogy reasoning, and automatic tuning of the description language. These different directions are related to or stimulated by different domains of tasks: learning of rule bases, games, computer‐aided teaching, learning in noisy environments, and so on. They are described in this article in the light of the main directions. The goal of a complete universal integrated system is still a far cry ahead, but as states a famous Chinese proverb: “The end lies in the way”.
Multivalued logics: a uniform approach to reasoning in artificial intelligence
Authors: Ginsberg Matthew L. 
Published: April 2007

This paper describes a uniform formalization of much of the current work in artificial intelligence on inference systems. We show that many of these systems, including first‐order theorem provers, assumption‐based truth maintenance systems (atmss), and unimplemented formal systems such as default logic or circumscription, can be subsumed under a single general framework.We begin by defining this framework, which is based on a mathematical structure known as abilattice.We present a formal definition of inference using this structure and show that this definition generalizes work involving atmss and some simple nonmonotonic logics.Following the theoretical description, we describe a constructive approach to inference in this setting; the resulting generalization of both conventional inference and atmss is achieved without incurring any substantial computational overhead. We show that our approach can also be used to implement a default reasoner, and discuss a combination of default and atms methods that enables us to formally describe an “incremental” default reasoning system. This incremental system does not need to perform consistency checks before drawing tentative conclusions, but can instead adjust its beliefs when a default premise or conclusion is overturned in the face of convincing contradictory evidence. The system is therefore much more computationally viable than earlier approaches.Finally, we discuss the implementation of our ideas. We begin by considering general issues that need to be addressed when implementing a multivalued approach such as that we are proposing, and then turn to specific examples showing the results of an existing implementation. This single implementation is used to solve a digital simulation task using first‐order logic, a diagnostic task using atmss as suggested by de Kleer and Williams, a problem in default reasoning as in Reiter's default logic or McCarthy's circumscription, and to solve the same problem more efficiently by combining default methods with justification information. All of these applications use the same general‐purpose bilattice theorem prover and differ only in the choice of bilattice being considered.
Discontinuous grammars1,2
Authors: Dahl Verónica 
Published: April 2007

AbstractThis article ties together previously scattered research on discontinuous grammars—logic grammars in which non‐explicit sequences of symbols can be alluded to in the rules and sometimes repositioned by them. After an introduction, we define them formally, present their background, and provide intuitive insight into their use. Next, we examine several motivating arguments, from both formal and natural language processing viewpoints, and we discuss the static discontinuity family of these grammars, in which (a) the nonexplicit strings are not allowed to move and (b) linguistic constraints specifically designed to suit, in particular, Government and Binding theory can be defined modularly and statically in terms of node domination in parse trees and are enforced dynamically. Finally, we discuss implementation issues, related work, and extensions.
A note on evidence and confirmation in machine learning
Authors: Delgrande James P. 
Published: April 2007

AbstractThis paper addresses the problem in inductive generalization of determining when a general hypothesis is supported by a particular instance. If we accept that, first, some facts do indeed support a general hypothesis and, second, that an instance that supports a hypothesis also supports all logical consequences of the hypothesis, then unintuitive and problematic results are immediately forthcoming. These assumptions lead, for example, to the conclusion that a blue Honda is confirming evidence for the hypothesis that ravens are black. This problem is variously known as the paradoxes of confirmation or Hempel's paradox. In this paper I develop a formal characterization of the problem. The assumption that whatever supports all classical consequences of the hypothesis is rejected. Rather, I argue that a weaker notion of consequence should be adopted for determining what consequences of a hypothesis are supported by the same evidence. An extant formal system for learning from examples is used to address these problems of evidential support, and it is shown that in this framework the problems do not arise.
Moments and points in an interval‐based temporal logic
Authors: Allen James F. , Hayes Patrick J. 
Published: April 2007

AbstractThis paper develops and explores a first‐order theory of time that appears useful as an underlying framework for a wide range of practical applications in artificial intelligence (AI). In particular, it presents a concise, formal axiomatization of “interval‐based” time as described by Allen and then explores the relationship between interval‐based and point‐based temporal theories in detail. This analysis should be useful to both theoretical and practical work in AI that involves the representation of time, since it shows what distinctions are actually substantive and what arise merely from formalisms being notational variants of one another.
Determining intended evidence relations in natural language arguments
Authors: YOUNG MARK A. , COHEN ROBIN 
Published: April 2007

When trying to understand a speaker's argument, it is necessary to determine what her claim is and what evidence she provides for it. It is necessary, therefore, to be able to recognize evidence relations in terms of the speaker's beliefs. This paper describes an implementation of anevidence oracle, which tests for evidence between statements and builds a model of the speaker based on the evidence relations found. This implementation is intended to be an advance in the development of practical discourse analysis systems, proposing a basis for verifying certain relationships between utterances. Another contribution of the work is a stratified speaker model which allows for varying levels of acceptance of beliefs attributed to the speaker. Integration of the implemented evidence oracle into a full discourse analyser is presented, together with output illustrating the analysis for several sample arguments. Some extensions of this approach for plan inference are also discussed.Lorsque l'on essaie de comprendre l'argument d'un locuteur, il importe de déterminer la nature de sa prétention et le type d'évidence qui l'accompagne. Par conséquent, il est nécessaire de pouvoir distinguer des relations d'évidence les croyances du locuteur. Cet article décrit la mise en oeuvre d'un oracle qui recherche l'évidence entre des énoncés et construit un modèle du locuteur en fonction des relations d'évidence constatées. Cette mise en oeuvre propose une base pour vérifier certaines relations entre des énoncés; elle se veut une contribution au développement d'un système pratique d'analyse du discours. Une autre contribution de cette recherche est l'élaboration d'un modèle de locuteur stratifyé qui tient compte de niveaux variables d'acceptation des croyances attributeés au locuteur. l'intégration de l'oracle d'évidence sous forme d'analyseur de discours est présentée, ainsi que des illustrations de l' analyse de plusieurs arguments types. Une extension de cette approche à l'inférence de plans est également discutée.
Making default inferences from logic programs
Authors: Li Liwu , YOU JIA‐HUAI 
Published: April 2007

The relationship between Reiter's default logic and general logic programs, which may contain negative subgoals in rule bodies, has been discussed in the literature by translating logic programs to default logic theories. Here, we present a method to translate some default logic theories to general logic programs, and study the extensions of default logic theories with the stable model semantics of logic programming. Based on the translation method, we show that another semantics of logic programming, the well‐founded semantics, can be used to define a new version of default logic, which is more cautious than the original one. This enables the existing proof procedures for the well‐founded semantics to perform default inference. We also study the property of cumulative monotonicity for both default logic theories and general logic programs under the two different semantics. As a direct application of the translation method, logic programs can be used to make default inference for semantic networks with exceptions.La relation entre la logique par défaut de Reiter et les programmes logiques généraux, qui peuvent comporter des sous‐buts négatifs dans les ensembles de règies, a déjàété discutée en traduisant les programmes logiques en théories de la logique par défaut. Dans cet article, les auteurs proposent une méthode pour traduire certaines théories de la logique par defaut en programmes logiques généraux et étudient les extensions des theories de la logique par defaut avec la sémantique de modéle stable de la programmation logique. En se basant sur la méthode de traduction, les auteurs démontrent qu'une autre sémantique de la programmation logique, la sémantique bien fondée, peut ětre utilisée pour définir une nouvelle version de la logique par défaut, qui est plus prudente que la première. Cela permet aux procédures de preuve existantes de la sémantique bien fondée d' effectuer l' inférence par défaut. Les auteurs examinent également les caracteristiques de la monotonicité cumulative pour les theories de la logique par défaut et les programmes logiques généraux selon les deux différentes sémantiques. Une application directe de la méthode de traduction est la possibilityé d' utiliser les programmes logiques pour effectuer de l' inférence par défaut pour les réseaux sémantiques avec exceptions.
Uncertainty, belief, and probability1
Authors: FAGIN RONALD , HALPERN JOSEPH Y. 
Published: April 2007

We introduce a new probabilistic approach to dealing with uncertainty, based on the observation that probability theory does not require that every event be assigned a probability. For anonmeasurableevent (one to which we do not assign a probability), we can talk about only theinner measureandouter measureof the event. In addition to removing the requirement that every event be assigned a probability, our approach circumvents other criticisms of probability‐based approaches to uncertainty. For example, the measure of belief in an event turns out to be represented by an interval (defined by the inner and outer measures), rather than by a single number. Further, this approach allows us to assign a belief (inner measure) to an eventEwithout committing to a belief about its negation‐E(since the inner measure of an event plus the inner measure of its negation is not necessarily one). Interestingly enough, inner measures induced by probability measures turn out to correspond in a precise sense to Dempster‐Shafer belief functions. Hence, in addition to providing promising new conceptual tools for dealing with uncertainty, our approach shows that a key part of the important Dempster‐Shafer theory of evidence is firmly rooted in classical probability theory.Cet article présente une nouvelle approche probabiliste en ce qui concerne le traitement de l'incertitude; celle‐ci est basée sur l'observation que la théorie des probabilityés n'exige pas qu'une probabilityé soit assignée à chaque événement. Dans le cas d'un événementnon mesurable(un événement pour lequel on n'assigne aucune probabilityé), nous ne pouvons discuter que de lamesure intérieureet de lamesure extérieurede l'évenément. En plus d'éliminer la nécessité d'assigner une probabilityéà l'événement, cette nouvelle approche apporte une réponse aux autres critiques des approches à l'incertitude basées sur des probabilityés. Par exemple, la mesure de croyance dans un événement est représentée par un intervalle (défini par la mesure intérieure et extérieure) plut&#x006f;&#x030c;t que par un nombre unique. De plus, cette approche nous permet d'assigner une croyance (mesure intérieure) à un événementEsans se compromettre vers une croyance à propos de sa négation‐E(puisque la mesure intérieure d'un événement et la mesure intérieure de sa négation ne sont pas nécessairement une seule et unique mesure). II est intéressant de noter que les mesures intérieures qui résultent des mesures de probabilityé correspondent d'une manière précise aux fonctions de croyance de Dempster‐Shafer. En plus de constituer un nouvel outil conceptuel prometteur dans le traitement de l'incertitude, cette approche démontre qu'une partie importante de la théorie de l'évidence de Dempster‐Shafer est fermement ancrée dans la theorie classique des probabilityés.
On the need for domain communication knowledge
Authors: Kittredge Richard , Korelsky Tanya , Rambow Owen 
Published: April 2007

Much research in text planning has been oriented towards identifying the rhetorical component of communication knowledge that allows for the structuring of coherent multi‐sentential or even multi‐paragraph text. However, several researchers have recently found rhetoric‐based top‐down approaches to be inadequate for their particular needs. In this paper, we explore the issue by introducing the concept of “domain communication knowledge” as a new analytical tool. By analyzing two existing rhetoric‐based text planners, and by closely analyzing a particular genre, namely reports, we conclude that domain‐specific knowledge about communication is pervasive and should be represented explicitly for the text planning task.La plupart des travaux de recherche dans la planification de textes ont été orientés vers ľ identification de la composante rhétorique de la connaissance de la communication, qui permet de structurer de manière cohérente un texte à phrases ou à paragraphes multiples. ?autre part, plusieurs chercheurs ont récemment constaté que les approches descendantes basées sur la rhétorique ne convenaient pas à leurs besoins particuliers. Dans cet article, les auteurs examinent la question en utilisant un nouvel outil analytique, soit le concept de 〈〈 connaissance du domaine reliée à la communication 〉〉 En étudiant deux planificateurs de textes existants et an analysant de très près un genre particulier, soit des rapports, les auteurs concluent que la connaissance spécifique du domaine à propos de la communication est subtile et devrait faire ľobjet ?une representation explicite pour la planification de textes.
STORY GENERATION BASED ON DYNAMICS OF THE MIND
Authors: Okada Naoyuki , Endo Tsutomu 
Published: April 2007

A story generation system based on dynamics of the mind is presented. Semantic theories until now avoided discussing a linkage of language with encyclopedic human knowledge. This paper attacks the problem of how to make clear the complicated, wide‐ranging dynamics of the mind and how to connect it to language.First, the background of this study is shown, in which our model of the mind, with both five levels along the concept formation process and eight domains according to the contents of mental activities, is surveyed.Based on this model, then, the dynamics of mind are discussed, along an Aesop fable. A unit of data processing in the mind is called a “module,” and the mental dynamics are considered as a chain activation of those modules, represented by a dynamic network. Next, a method for story generation is discussed. Propositional information of a sentence is embedded in a slot of activated, frame‐structured modules, and the discourse structure of a generated story basically depends on the dynamic network. Both the chain activation and the generation processes are verified by experiments.Lastly, residual problems of our research, a comparison with related research, and its applications are discussed.This case study would be expected to give a basis to integrated systems for problem solving, natural language and image understandings, their generations, and intelligent robots.
INTELLIGENT BEHAVIOR IN MACHINES EMERGING FROM A COLLECTION OF INTERACTIVE CONTROL STRUCTURES
Authors: Cherian Sunil , Troxell Wade 
Published: April 2007

Control strategies that decompose the competence of an agent into independent, task‐achieving control structures are emerging as viable alternatives to the notion that a robot is an explicit symbol processing device with input and output extensions in the form of sensors and actuators. This approach draws inspiration from ethology and the cognitive sciences, where the competence of biological creatures is seen to be a result of the successful combination of several distinct behavior patterns that enable them to interact effectively with their environments.The distinction between classical approaches that view intelligent behavior as the outcome of symbolic manipulations and an alternate approach that asserts that it is the careful integration of distributed, goal‐competent control structures that lead to intelligent behavior is analyzed in detail. It is found that this dichotomy can be said to arise from the paradigm that is chosen to represent the knowledge at the disposal of the agent. Structurally encoded knowledge requiring an active interpreter for the knowledge to be exhibited in action leads to the symbol processing paradigm for intelligent behavior, whereas the interactive model for knowledge representation assumes that the knowledge at the disposal of an active agent resides within goal‐competent, interactive control structures.A formalism is developed for representing the goal‐directed nature of these interactive control structures with clear control‐module boundaries. An implementation is then presented to demonstrate some of the basic features of this methodology.
Changes in sub‐water table fluid flow at the end of the Proterozoic and its implications for gas pulsars and MVT lead–zinc deposits
Authors: CATHLES L. M. 
Published: April 2007

AbstractA fundamental change in the nature of sub‐water table fluid flow occurred at roughly the Proterozoic–Phanerozoic boundary when organic matter began to be buried in sufficient quantities that nonaqueous fluids could occupy a significant fraction of the pore space. This allowed the formation of remarkably durable capillary seals that could trap gas in large portions (hundreds of kilometers) of a basin for hundreds of millions of years. Gas loss from these gas zones can be highly dynamic, especially during gas generation. Under the right circumstances, hundreds of cubic kilometers of gas can be rapidly discharged into adjacent permeable aquifers. In Pennsylvanian/Permian time, the Arkoma Basin may have repeatedly discharged such volumes of gas into the very permeable Cambrian sandstone and karstic carbonate aquifers of the mid‐continent of the United States. This could have displaced brines rapidly enough to form the Mississippi Valley‐type (MVT) lead–zinc deposits of this age that are associated with the Arkoma Basin, heating them only briefly as required by maturity indicators. Sea level rise accompanying the melting of Permian continental glaciers may have triggered the gas expulsion events. This radically new mechanism for the formation of MVT deposits is just one example of the nonlinear dynamics of gas accumulations that are possible since Late Proterozoic time.