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Visibility Analysis on the Web Using Co-visibilities and Semantic Networks

机译:使用共可见性和语义网络的Web可见性分析

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Monitoring public attention for a topic is of interest for many target groups like social scientists or public relations. Several examples demonstrate how public attention caused by real-world events is accompanied by an accordant visibility of topics on the web. It is shown that the hitcount values of a search engine we use as initial visibility values have to be adjusted by taking the semantic relations between topics into account. We model these relations using semantic networks and present an algorithm based on Spreading Activation that adjusts the initial visibilities. The concept of co-visibility between topics is integrated to obtain an algorithm that mostly complies with an intuitive view on visibilities. The reliability of search engine hitcounts is discussed.
机译:对于许多目标群体(例如社会科学家或公共关系)而言,监视公众对某个主题的关注是很重要的。几个示例说明了由现实事件引起的公众关注如何与主题在网络上的一致可见性相伴随。结果表明,必须通过考虑主题之间的语义关系来调整用作初始可见性值的搜索引擎的点击计数值。我们使用语义网络对这些关系进行建模,并提出一种基于扩展激活的算法,该算法可调整初始可见性。集成主题之间的共同可见性概念以获得一种算法,该算法主要符合对可见性的直观视图。讨论了搜索引擎命中率的可靠性。

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