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In recent years, with the rapid proliferation of digital images, the need to search and retrieve the images accurately, efficiently, and conveniently is becoming more acute. Automatic image annotation with image semantic content has attracted increasing attention, as it is the preprocess of annotation based image retrieval which provides users accurate, efficient, and convenient image retrieval with...
In a multiagent system, coalition formation is a coordination method for agents aiming to form groups of interest. In this paper, we focus on the particular context of hedonic games. In hedonic games, the objective of the agents is to form coalitions, which are groups of agents. The satisfaction of an agent depends on other members of its coalition. In this context, autonomous agents need strategical...
Emotions play a key role in any purchasing process even more when it is done through web portals. In this paper, we present a fuzzy-logic based system aimed to generate emotions for a virtual seller or avatar. The 3D avatar is integrated within the e-Zoco e-commerce portal and its behaviour depends on the product search results. Moreover, the mood of the avatar not only depend on the products that...
This paper introduces an approach which aims at improving information access (skills, services) in large networks. A self-organized multiagent analysis of the problem, reducing the number of messages transmitted for a skill search is proposed. The MWAC (Multi-Wireless-Agent Communication) model is extended here to take some specificities of social networks into account, like the information held by...
In this paper, we report a classifier ensemble technique using the search capability of genetic algorithm (GA) for Named Entity Recognition (NER) in biomedical domain. We use Maximum Entropy (ME) framework to build a number of classifiers depending upon the various representations of a set of features. The proposed technique is evaluated with the JNLPBA 2004 data sets that yield the overall recall,...
In this paper, we present an analysis of different approaches relative to the correction of belief functions based on the results given by a confusion matrix. Three different mechanisms based on discountings are detailed. These methods have the objective to assess the discounting rates to be assigned to a source of information. These discounting rates allow to correct raw data, based on learnt decisions...
The Quantified Constraint Satisfaction Problem(QCSP) is a generalization of the classical constraint satisfaction problem in which some variables can be universally quantified. This additional expressiveness can help model problems in which a subset of the variables take value assignments that are outside the control of the decision maker. Typical examples of such domains are game-playing, conformant...
The existence of powerful constraint satisfaction algorithms is not the sole reason of the wide success of the CSP framework. The interest of this framework is also that it offers a generic and simple way for the modeling of real world applications. Nevertheless these applications call for tasks that often differ from a classical search for a solution. The aim of the present paper is not to provide...
The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds...
We present a general method of designing fast approximation algorithms for cut-based minimization problems in undirected graphs. In particular, we develop a technique that given any such problem that can be approximated quickly on trees, allows approximating it almost as quickly on general graphs while only losing a poly-logarithmic factor in the approximation guarantee. To illustrate the applicability...
Estimating agent's skill ratings from team competition results has many applications in the real world. Existing models assume skills are the same for all contexts. However, skills are context-sensitive in a variety of cases. In this paper, we present a Factor-Based Context-Sensitive Skill Rating System(FBCS-SRS). Instead of estimating agent skills under every context, which is hard due to data sparisity,...
The new Internet terminals are at the same time mobile and multihomed since they are able to change their point of attachment to the network, and embed several network interfaces. Each one can be attached to a different network. Multihoming and mobility are generally considered as two separate concepts and thus are handled by different protocols. Nontheless, mobility and multihoming share the same...
In this paper, we present the problem of appropriate feature selection for constructing a Maximum Entropy (ME) based Named Entity Recognition (NER) system under the multiobjective optimization (MOO) framework. Two conflicting objective functions are simultaneously optimized using the search capability of MOO. These objectives are (i). the dimensionality of features, which is tried to be minimized,...
We construct the first general secure computation protocols that require no trusted infrastructure other than authenticated communication, and that satisfy a meaningful notion of security that is preserved under universal composition- assuming only the existence of enhanced trapdoor permutations. The notion of security fits within a generalization of the "angelbased" framework of Prabhakaran...
We say that a cryptographic scheme is Continuous Leakage-Resilient (CLR), if it allows users to refresh their secret keys, using only fresh local randomness, such that: 1. The scheme remains functional after any number of key refreshes, although the public key never changes. Thus, the “outside world'' is neither affected by these key refreshes, nor needs to know about their frequency. 2. The scheme...
Multiple instances of activity makes workflow management more flexible on handling process, but it causes some problems, such as synchronizing schedule and data sharing confliction. This paper proposes a scheme mode of object pool with lock. In the mode, object pool is constructed for each activity, all instances of the activity are deposited in respective pool, and the schedule scheme is implemented...
Automatic Chinese Term Extraction is an important issue in Natural Language Processing. This paper has proposed an improved method based on C/NC-value to extract Chinese term. We delete the linguistic part in C/NC-value method, and add two improved statistical parameters: mutual information and log-likelihood ratio, to calculate the statistical features of the candidate string. The results of the...
Conventional approaches to image annotation tackle the problem based on the low-level visual information. Considering the importance of the information on the constrained interaction among the objects in a real world scene, contextual information has been utilized to recognize scene and object categories. In this paper, we propose a Bayesian approach to region-based image annotation, which integrates...
It is now widely accepted that in order to optimize both their usage and their design and maintenance ontologies should comply to design quality criteria, e.g., absence of redundancies and appropriate level of abstraction. Yet given the variety and scope of activities comprised in the life-cycle of an ontological model (OM), such as adapting, splitting, populating, this quality is easily compromised,...
Neural networks are often selected as tool for software effort prediction because of their capability to approximate any continuous function with arbitrary accuracy. A major drawback of neural networks is the complex mapping between inputs and output, which is not easily understood by a user. This paper describes a rule extraction technique that derives a set of comprehensible IF-THEN rules from a...
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