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基于Web属性抽取训练分类模型的方法研究 被引量：3

The Method Research of Web-based Attribute Extraction for Training Classification Model
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摘要 针对通用搜索引擎信息量大、查询不准确、深度不够等问题,提出了基于Web的产品属性抽取这一新的搜索引擎服务模式。基于Web的产品属性抽取实际就是一个自动分类问题,其任务是:在给定的分类体系下,根据相关产品模板自动地判断属性的是非。完成此任务的关键在于寻找有效的特征值;确定相关分类规则,最终通过P、R和F指标来评价分类算法。 Carrying out Web-based product attribute extraction is one of the new search engine service patterns, it is put forward in relation that the general search engine is informative, inquiries inaccurate and not enough depth. Web-based product attribute extraction is a actual automatic classification problem, the task is： In a given classification system, in accordance with the relevant product template carry automatically attribute judge of right and wrong. Currently, the key is to search the effective feature value, determine the relevant classification rules, through P, R and F indicators assess the classification algorithm finally.
作者 吴月萍
机构地区 上海第二工业大学计算机与信息学院
出处 《上海第二工业大学学报》 2008年第1期29-34,共6页 Journal of Shanghai Polytechnic University
关键词 属性抽取 分类规则 特征值 最大熵 attribute extraction classification rule feature value maximum entropy
分类号 TP393.09 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献7

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共引文献103

同被引文献35

  • 1王海涛,曹存根,高颖.基于领域本体的半结构化文本知识自动获取方法的设计和实现[J].计算机学报,2005,28(12):2010-2018. 被引量：31
  • 2刘非凡,赵军,吕碧波,徐波,于浩,夏迎炬.面向商务信息抽取的产品命名实体识别研究[J].中文信息学报,2006,20(1):7-13. 被引量：47
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引证文献3

二级引证文献7

上海第二工业大学学报
2008年 第1期

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