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Many real world phenomena can be naturally modeled as graph structures whose nodes representing entities and whose edges representing interactions or relationships between entities. The analysis of the graph data have many practical implications. However, the release of the data often poses considerable privacy risk to the individuals involved. In this paper, we address the edge privacy problem in...
It is very important to know how fast a BDI agent can react to and process incoming event sequences if we want to apply such autonomous agents into time-sensitive applications like the Close-In weapon system in air-carriers. In, we proposed an analysis method for traditional sequential agents. In this paper we extend the theoretical analysis method to parallel BDI agents. Our method can estimate the...
Agent technology is a good approach for solving a number of problems concerned with personalized learning. In personal learning contexts individual students are given an environment that takes into account of their needs, interests and aspirations, and this is intended to lead to an enhanced learning experience. The aim of this paper is to show how agent systems can not only form a good framework...
In this paper the problem of performing external validation of the semantic coherence of topic models is considered. The Fowlkes-Mallows index, a known clustering validation metric, is generalized for the case of overlapping partitions and multi-labeled collections, thus making it suitable for validating topic modeling algorithms. In addition, we propose new probabilistic metrics inspired by the concepts...
We propose the Tag Allocation Model (TAM) to model social annotation data. TAM is a probabilistic generative model, its key feature is finding the latent reason for each tag. A latent reason can be any discrete features of the document (such as words) or a global noise variable. Inferring the reason for each tag helps TAM reduce the ambiguity of a document with multiple tags. By introducing noise...
In this study, under multi-agent environment, we introduce a notion of probabilistic Nash equilibrium into reinforcement learning method. Here we take an approach of mixed Nash strategy based on correlated technique in terms of Local Effect functions. We examine some experiment results to show some ideal properties for cooperative approach.
User-generated reviews play an important role for potential consumers in making purchase decisions. However, the quality and helpfulness of user-generated reviews are unavailable unless consumers read through them. Automatically predicting the helpfulness of user-generated reviews can assist consumers in discovering helpful reviews. Existing helpfulness assessing models make use of the positive vote...
This paper addresses missing edges and vertices in a network. We discuss interchangeability and duality between vertices and edges in a graph. We use covariate information associated with vertices to estimate the probability of missing edges; likewise, we use covariate information associated with edges to estimate the probability of missing vertices. In order to predict missing vertices, we apply...
More and more content on the Web is generated by users. To organize this information and make it accessible via current search technology, tagging systems have gained tremendous popularity. Especially for multimedia content they allow to annotate resources with keywords (tags) which opens the door for classic text-based information retrieval. To support the user in choosing the right keywords, tag...
Online reviews, which are getting increasingly prevalent with the rapid growth of Web 2.0, have been shown to be second only to "word-of-mouth" in terms of influencing purchase decisions. It is therefore imperative to analyze them and distill useful knowledge that could be of economic values to vendors and other interested parties. Previous studies have confirmed that the sentiments expressed...
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