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Extending HITS Algorithm for Ranking Locations by Using Geotagged Resources

机译:利用地理标记资源扩展HITS算法对位置进行排名

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The paper focuses on using geotagged resources from the social network service (SNS) for searching the famous places from keyword. We extend the HITS[9] algorithm in order to rank locations which are collected from geotagged resources on SNS. Our approach not only uses the similarity measurement between locations'tags for computing the value of locations but also calculate the term frequency of tags which occur in each location to modify the value of tags for ranking. We implement and show the experimental results with the set of locations from the geotagged resources.
机译:本文着重于利用来自社交网络服务(SNS)的地理标记资源从关键字中搜索著名景点。我们扩展HITS [9]算法,以便对从SNS上带有地理标签的资源收集的位置进行排名。我们的方法不仅使用位置标签之间的相似性度量来计算位置值,而且还计算出现在每个位置中的标签的词频,以修改标签的值以进行排名。我们使用地理标记资源中的一组位置来实现并显示实验结果。

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