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Precise Photo Retrieval on the Web with a Fuzzy LogicNeural Network-Based Meta-search Engine

机译:用基于模糊的逻辑网络的元搜索引擎在网上进行精确的照片检索

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Nowadays most web pages contain both text and images. Nevertheless, search engines index documents based on their disseminated content or their meta-tags only. Although many search engines offer image search, this service is based over textual information filtering and retrieval. Thus, in order to facilitate effective search for images on the web, text analysis and image processing must work in complement. This paper presents an enhanced information fusion version of the meta-search engine proposed in [1], which utilizes up to 9 known search engines simultaneously for content information retrieval while 3 of them can be used for image processing in parallel. In particular this proposed meta-search engine is combined with fuzzy logic rules and a neural network in order to provide an additional search service for human photos in the web.
机译:如今,大多数网页包含文本和图像。然而,搜索引擎仅基于其传播内容或其元标记的索引文档。虽然许多搜索引擎提供图像搜索,但此服务基于文本信息过滤和检索。因此,为了便于有效地搜索Web上的图像,文本分析和图像处理必须以补充方式工作。本文提高了[1]中提出的元搜索引擎的增强信息融合版本,其利用多达9个已知的搜索引擎,同时用于内容信息检索,而其中3只能用于并行图像处理。特别地,该提出的元搜索引擎与模糊逻辑规则和神经网络组合,以便为网络中的人类照片提供额外的搜索服务。

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