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    • 7. 发明授权
    • Personalization engine for classifying unstructured documents
    • 用于分类非结构化文档的个性化引擎
    • US08214346B2
    • 2012-07-03
    • US12362840
    • 2009-01-30
    • Tushar PradhanThomas OsborneJohn Potter
    • Tushar PradhanThomas OsborneJohn Potter
    • G06F7/00
    • G06F17/30011G06F17/30598G06F17/30699G06F17/30707
    • Unstructured electronic documents are classified for profiling and targeting users for additional relevant content. Behavioral data is gathered from user activity, and user documents and actions are categorized. Profile information is combined with collaborative and editorial data to provide users with credible information regarding products. Author-generated document classification information is analyzed and assigned a first taxonomic noun to characterize the document. User-generated tags characterizing a portion of the document are assigned a second taxonomic noun. Search terms that resulted in the user accessing the document are identified and assigned a third taxonomic noun. Attributes related to how the document was accessed are evaluated and assigned a fourth taxonomic noun. The document is processed using pattern rules to extract a fifth taxonomic noun. The taxonomic nouns are aggregated to determine term vectors representing the document, and the document is categorized using the term vectors, the taxonomic nouns, or the author-generated classification.
    • 非结构化电子文档被分类为用于分析和定位用户以获得更多相关内容。 从用户活动中收集行为数据,并对用户文档和操作进行分类。 简档信息与协作和编辑数据相结合,为用户提供有关产品的可靠信息。 作者生成的文档分类信息被分析并分配了第一个分类名词来表征文档。 表征文档的一部分的用户生成的标签被分配了第二个分类名词。 导致用户访问该文档的搜索字词被识别并分配了第三个分类名词。 与文档访问相关的属性被评估并分配了第四个分类名词。 使用模式规则处理文档以提取第五个分类名词。 聚合分类学名词以确定表示文档的术语向量,并使用术语向量,分类名词或作者生成的分类对文档进行分类。