: In a traditional database system, the result of a query is a set of values (those values that satisfy the query). In other data servers, such as a system with queries based on image content, or many text retrieval systems, the result of a query is a sorted list. For example, in the case of a system with queries based on image content, the query might ask for objects that are a particular shade of red, and the result of the query would be a sorted list of objects in the database, sorted by how well the color of the object matches that given in the query. A multimedia system must somehow synthesize both types of queries (those whose result is a set, and those whose result is a sorted list) in a consistent manner. In this paper we discuss the solution adopted by Garlic, a multimedia information system being developed at the IBM Almaden Research Center. This solution is based on "graded" (or "fuzzy") sets. Issues of efficient query evaluation in a multimedia system are very different fro...

Abstract-This paper presents a person identification system based on acoustic and visual features. The system is organized as a set of non-homogeneous classifiers whose outputs are integrated after a normalization step. In particular, two classifiers based on acoustic features and three based on visual ones provide data for an integration module whose performance is evaluated. A novel technique for the integration of multiple classifiers at an hybrid ranWmeasurement level is introduced using HyperBF networks. Two different methods for the rejection of an unknown person are introduced. The performance of the integrated system is shown to be superior to that of the acoustic and visual subsystems. The resulting identification system can be used to log personal access and, with minor modifications, as an identity verification system. Index Tenns-Template matching, robust statistics, correlation, face recognition, speaker recognition, learning, classification. I.

There are essential differences between multimedia databases (which may contain complicated objects, such as images), and traditional databases. These differences lead to interesting new issues, and in particular cause us to consider new types of queries. For example, in a multimedia database it is reasonable and natural to ask for images that are somehow "similar to" some fixed image. Furthermore, there are different ways of obtaining and accessing information in a multimedia database than information in a traditional database. For example, in a multimedia database, it might be reasonable to have a query that asks for, say, the top 10 images that are similar to a fixed image. This is in contrast to a relational database, where the answer to a query is simply a set. (Of course, in a relational database, the result to a query may be sorted in some way for convenience in presentation, such as sorting department members by salary, but logically speaking, the result is still simply a set, ...

There are many formal approaches to specifying how the mental state of an agent entails that it perform particular actions. These approaches put the agent at the center of analysis. For some questions and purposes, it is more realistic and convenient for the center of analysis to be the task environment, domain, or society of which agents will be a part. This paper presents such a task environment-oriented modeling framework that can work hand-in-hand with more agent-centered approaches. Our approach features careful attention to the quantitative computational interrelationships between tasks, to what information is available (and when) to update an agent's mental state, and to the general structure of the task environment rather than single-instance examples. A task environment model can be used for both analysis and simulation, it avoids the methodologicalproblems of relying solely on single-instance examples, and provides concrete, meaningful characterizations with which ...

Abstract—The aim of this paper is to model the processes of the aggregation of weighted information in a linguistic framework. Three aggregation operators of weighted linguistic information are presented: linguistic weighted disjunction (LWD) operator, linguistic weighted conjunction (LWC) operator, and linguistic weighted averaging (LWA) operator. A study of their axiomatics is presented to demonstrate their rational aggregation. Index Terms — Aggregation operators, fuzzy linguistic quantifier, linguistic modeling. I.

Coordination, as the act of managing interdependencies between activities, is one of the central research issues in Distributed Artificial Intelligence. Many researchers have shown that there is no single best organization or coordination mechanism for all environments. Problems in coordinating the activities of distributed intelligent agents appear in many domains: the control of distributed sensor networks; multi-agent scheduling of people and/or machines; distributed diagnosis of errors in local-area or telephone networks; concurrent engineering; `software agents' for information gathering. The design of coordination mechanisms for group...

The fuzzy linguistic approach has been applied successfully to many problems. However, there is a limitation on this approach, the loss of information. It appears due to its information representation model (discrete terms) and the computational methods used when fusion and combination processes are performed on linguistic variables. In this contribution we propose a new fuzzy linguistic representation model based on the concept of "Symbolic Translation" for dealing with linguistic information in a continuous domain. Together with this representation model we shall develop a computational technique for fusing linguistic variables without loss of information. Keywords: Linguistic variables, linguistic modeling, fusion of linguistic information. 1 Introduction The problems depending on their aspects can deal with dierent types of information. Usually, the problems present quantitative aspects that can be assessed by means of precise numerical values, but in other cases the problems p...

There are many formal approaches to specifying how the mental state of an agent entails the particular actions it will perform. These approaches put the agent at the center of analysis. For some questions and purposes, it is more realistic and convenient for the center of analysis to be the task environment, domain, or society of which agents will be a part. This paper presents such a task environment-oriented modeling framework that can work hand-in-hand with more agent-centered approaches. Our approach features careful attention to the quantitative computational interrelationships between tasks, to what information is available (and when) to update an agent's mental state, and to the general structure of the task environment rather than single-instance examples. A task environment model can be used for both analysis and simulation, it avoids the methodological problems of relying solely on single-instance examples, and provides concrete, meaningful characterizations with which to sta...

In a linguistic framework, several group decision making processes by direct approach are presented. These processes are designed using the linguistic ordered weighted averaging (LOWA) operator. To do so, first a study is made of the properties and the axiomatic of LOWA operator, showing the rationality of its aggregation way. And secondly, we present the use of LOWA operator to solve group decision making problems from individual linguistic preference relations. Keywords: Group decision making, linguistic preference relation, fuzzy linguistic quantifier, OWA operators. 1 Introduction Decision making is a usual task in human activities. It consists of finding the best option from a feasible set. Many decision making processes, in the real world, take place in an environment in which the goals, contraints and consequences of possible actions are not precisely known. In these cases, probability theory has always allowed to deal quantitatively with that lack of precision. However, when ...

This paper presents a consensus model in group decision making under linguistic assessments. It is based on the use of linguistic preferences to provide individuals' opinions, and on the use of fuzzy majority of consensus, represented by means of a linguistic quantifier. Several linguistic consensus degrees and linguistic distances are defined, acting on three levels. The consensus degrees indicate how far a group of individuals is from the maximum consensus, and linguistic distances indicate how far each individual is from current consensus labels over the preferences. This consensus model allows to incorporate more human consistency in decision support systems. Keywords: Group decision making, linguistic modelling, consensus degree. 1. Introduction Decision making problems basically consist of finding the best option from a feasible option set. As human beings are constantly making decisions in the real world, in many situations, the use of computerized decision support systems, may...