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System and method for sentiment-based text classification and relevancy ranking

机译:基于情感的文本分类和相关性排序的系统和方法

摘要

The sentimental significance of a group of historical documents related to a topic is assessed with respect to change in an extrinsic metric for the topic. A unique sentiment binding label is included to the content of actions documents that are determined to have sentimental significance and the group of documents is inserted into a historical document sentiment vector space for the topic. Action areas in the vector space are defined from the locations of action documents and singular sentiment vector may be created that describes the cumulative action area. Newly published documents are sentiment-scored by semantically comparing them to documents in the space and/or to the singular sentiment vector. The sentiment scores for the newly published documents are supplemented by human sentiment assessment of the documents and a sentiment time decay factor is applied to the supplemented sentiment score of each newly published documents. User queries are received and a set of sentiment-ranked documents is returned with the highest age-adjusted sentiment scores.
机译:关于该主题的外部度量的变化,评估了与该主题相关的一组历史文档的情感意义。唯一的情感绑定标签包含在已确定具有情感重要性的动作文档的内容中,并将文档组插入到该主题的历史文档情感矢量空间中。向量空间中的动作区域是根据动作文档的位置定义的,并且可以创建描述累积动作区域的奇异情绪向量。通过在语义上将新发布的文档与空间中的文档和/或与奇异的情感向量进行比较,可以对情感进行评分。通过对文档的人类情感评估来补充新发布文档的情感得分,并将情感时间衰减因子应用于每个新发布文档的补充情感得分。收到用户查询,并以最高的年龄调整后的情绪分数返回一组情绪排名的文档。

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