A Fuzzy Petri Net Model towards Context-Awareness Based Personalized Recommendation

Jian Ye, Jintao Li, Hongzhou Shi, Xiaoguang Gu, Zhenmin Zhu
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引用次数: 6

Abstract

In a personalized recommender system of a ubiquitous computing environment, the decision on recommendation depends on some uncertain factors. Fuzzy system has an ability of solving the reasoning uncertainty, and gets widely used in the context awareness based personalized recommender system. In this paper, we present a fuzzy reasoning model based on the Fuzzy Petri Net. The model considers the requirements of task fulfillment, user's preferences and QoS of the system. With difference from those existing recommender systems, we focus on the formalized modeling of fuzzy reasoning of the personalized recommendation. Through formalization of fuzzy reasoning, we propose an approach to construct a rule-based reasoning system. The feasibility of the proposed approach is validated by an example of the personalized recommender engine.
基于上下文感知的个性化推荐模糊Petri网模型
在泛在计算环境下的个性化推荐系统中,推荐决策依赖于一些不确定因素。模糊系统具有解决推理不确定性的能力,在基于上下文感知的个性化推荐系统中得到了广泛的应用。本文提出了一种基于模糊Petri网的模糊推理模型。该模型综合考虑了任务实现的要求、用户的偏好和系统的QoS。与现有的推荐系统不同,我们着重于个性化推荐的模糊推理形式化建模。通过对模糊推理的形式化,提出了一种构建基于规则的推理系统的方法。通过个性化推荐引擎的实例验证了该方法的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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