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Implementing an Image Search System with Integrating Social Tags and DBpedia

机译:通过整合社交标签和DBpedia实现图像搜索系统

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Although the number of recommending system has increased, many of the existing recommending systems often only offer general-purpose information. In the case of multimedia searches, novelty and unexpectedness are seen as particularly important. In this paper, we propose an image search method with a high degree of unexpectedness by integrating the social tag of Flickr and DBpedia, and using preference data from search logs. We also propose an image search system named Linked Flickr Search, which implemented the proposed method. By evaluation with an unexpectedness index, and by comparing the basic Flickr search functions and flickr wrappr, which is related research, we confirmed that particularly in the initial stages of the search, our proposed system was possible to recommend highly unexpected images.
机译:尽管推荐系统的数量有所增加,但是许多现有的推荐系统通常仅提供通用信息。在多媒体搜索的情况下,新颖性和意外性尤为重要。在本文中,我们通过整合Flickr和DBpedia的社交标签,并使用来自搜索日志的偏好数据,提出了一种具有高度意外性的图像搜索方法。我们还提出了一种名为Linked Flickr Search的图像搜索系统,该系统实现了所提出的方法。通过使用意外性指标进行评估,并通过比较基本的Flickr搜索功能和flickr wrappr(这是相关研究),我们确认,特别是在搜索的初始阶段,我们提出的系统可以推荐高度意外的图像。

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