[Keywords]： computer application; Chinese information processing; automatic query classification; query intention classification; classification approach; dataset; feature extraction; machine learning; syntactic parsing; term proximity;
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为了提高化学主题搜索引擎的查询效果，采用距离加权七一近邻分类算法来进行自动分类。
In order to improve the performance of chemistry-focused search engines, an automatic text categorization algorithm is proposed based on the distance-weighted k-nearest neighbor algorithm.
然后根据标签间的相关度度量选出图片结果集中与查询标签高相关的标签集，接着采用一种自顶向下启发式的图划分算法来自动对次相关标签集进行分类。
The candidate tags can be shortlisted according to their tag relevances to the query tags. The shortlisted tags are then clustered on-the-fly using a graph partitioning algorithm.
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