协同上下文预测的一种方法

Christian Voigtmann, Sian Lun Lau, K. David
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引用次数: 9

摘要

上下文预测方法基于已知的上下文模式预测未来的上下文,以提前适应,例如服务。在用户的上下文历史没有为观察到的上下文模式提供合适的上下文信息的情况下,据我们所知,上下文预测算法将无法预测合适的未来上下文。为了克服用户上下文历史中上下文信息缺失的缺陷,我们提出了协作上下文预测(CCP)方法。CCP利用了现有社交网络推荐系统的协作特性。为了评估CCP方法,将该方法与局部对齐上下文预测器进行了实验比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An approach to Collaborative Context Prediction
Context prediction approaches forecast future contexts based on known context patterns to adapt e.g., services in advance. In the case of the user's context history not providing suitable context information for the observed context pattern, to the best of our knowledge context prediction algorithms will fail to forecast the appropriate future context. To overcome the gap of missing context information in the user's context history, we propose the Collaborative Context Prediction (CCP) approach. CCP utilises the collaborative characteristics of existing recommendation systems of social networks. To evaluate the CCP method an experimental comparison of the proposed method against the local Alignment context predictor is carried out.
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