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US08484245B2 Large scale unsupervised hierarchical document categorization using ontological guidance 有权
使用本体论指导的大规模无监督层级文件分类

Large scale unsupervised hierarchical document categorization using ontological guidance
Abstract:
A classification method includes constructing queries from category descriptors representing categories of a taxonomy of hierarchically organized categories. The query constructed for a category c includes a query component based on descriptors of the category c and at least one query component based on descriptors of an ancestor or descendant category of the category c. A documents database is queried using the constructed queries to retrieve pseudo-relevant documents. Language models for the categories of the taxonomy are extracted from the pseudo-relevant documents by inferring a hierarchical topic model representing the taxonomy. An input document is classified by optimizing mixture weights of a weighted combination of categories of the hierarchical topic model respective to the input document.
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