The modeling of simple analogic and inductive processes in a semantic memory system

"It is part of our thesis that concepts in the strict sense of the term, as we know them- which, since Euler, the great mathematician (1707-1.783), ore represented by circles, a fact which means far more than meets the eye- are foreign to the Chinese mind. "- Gustav Herdan, Linguistics No. 28 Summary In this paper w. present a general data structure for a semantic memory, and we give a definition of "analogy " between items of semanti

Un modèle de recherche d'information basé sur les graphes et les similarités structurelles pour l'amélioration du processus de recherche d'information

The main objective of IR systems is to select relevant documents, related to a user's information need, from a collection of documents. Traditional approaches for document/query comparison use surface similarity, i.e. the comparison engine uses surface attributes (indexing terms). We propose a new method which uses a special kind of similarity, namely structural similarities (similarities that use both surface attributes and relation between attributes). These similarities were inspired from cognitive studies and a general similarity measure based on node comparison in a bipartite graph. We propose an adaptation of this general method to the special context of information retrieval. Adaptation consists in taking into account the domain specificities: data type, weighted edges, normalization choice. The core problem is how documents are compared against queries. The idea we develop is that similar documents will share similar terms and similar terms will appear in similar documents. We have developed an algorithm which traduces this idea. Then we have study problem related to convergence and complexity, then we have produce some test on classical collection and compare our measure with two others that are references in our domain. The Report is structured in five chapters: First chapter deals with comparison problem, and related concept like similarities, we explain different point of view and propose an analogy between cognitive similarity model and IR model. In the second chapter we present the IR task, test collection and measures used to evaluate a relevant document list. The third chapter introduces graph definition: our model is based on graph bipartite representation, so we define graphs and criterions used to evaluate them. The fourth chapter describe how we have adopted, and adapted the general comparison method. The Fifth chapter describes how we evaluate the ordering performance of our method, and also how we have compared our method with two others.Cette thèse d'informatique s'inscrit dans le domaine de la recherche d'information (RI). Elle a pour objet la création d'un modèle de recherche utilisant les graphes pour en exploiter la structure pour la détection de similarités entre les documents textuels d'une collection donnée et une requête utilisateur en vue d'améliorer le processus de recherche d'information. Ces similarités sont dites « structurelles » et nous montrons qu'elles apportent un gain d'information bénéfique par rapport aux seules similarités directes. Le rapport de thèse est structuré en cinq chapitres. Le premier chapitre présente un état de l'art sur la comparaison et les notions connexes que sont la distance et la similarité. Le deuxième chapitre présente les concepts clés de la RI, notamment l'indexation des documents, leur comparaison, et l'évaluation des classements retournés. Le troisième chapitre est consacré à la théorie des graphes et introduit les notations et notions liées à la représentation par graphe. Le quatrième chapitre présente pas à pas la construction de notre modèle pour la RI, puis, le cinquième chapitre décrit son application dans différents cas de figure, ainsi que son évaluation sur différentes collections et sa comparaison à d'autres approches

Decision-making: creativity, judgment, and systems

(print) x, 276 p. : ill. : 24 cmThe essays assembled in this volume were prepared by the authors for presentation on the campus of the Ohio State University at the Thomas A. Boyd interdisciplinary conference on decision-making aids. Through the financial support of the College of Engineering, the Thomas A. Boyd Lecture Fund, and the School of Architecture, the conference was established as a means for bringing together an interdisciplinary group of scientists and scholars for a wide-ranging discussion of the many aspects of emerging decision-aid research and applications along with their implications for professional activities and professional education. Consonant with the excellence and achievement stimulated by Thomas A. Boyd's support for higher education, the conference and the papers presented in this volume are dedicated to the advancement of the use of scientific methods for decision-making within the several disciplines concerned with enhancing environment and the well-being of people.Preface. p.ix -- Introduction. p.3 -- PART 1: Decision-making strategies. -- Personalistic decision theory: exposition and critique. p.19 -- The Study of collective decisions. p.42 -- PART 2: Decision-making aids -- Information science as an aid to decision-making. p.69 -- Toward a working theory of automated design. p.85 -- The Generation of form by geometric methods. p.112 -- PART 3: Decision aid applications -- Decision aids for the planning and development of university facilities. p.127 -- Analytic approaches to facility layout and design. p.137 -- Development action sequencing under highly constrained conditions. p.147 -- Adaptive diagnosis of problems. p.157 -- PART 4: Human creativity and judgment -- Managing visual information. p.173 -- Matching decision aids with intuitive styles. p.190 -- Conceptual models in design. p.205 -- PART 5: Implications -- Who looks at the whole system? p.223 -- Decision aids: needs and prospects. p.247 -- Epilogue. p.261 -- Notes on the contribution. p.265 -- Index. p.26