您的位置:山东大学 -> 科技期刊社 -> 《山东大学学报(理学版)》

J4 ›› 2011, Vol. 46 ›› Issue (5): 58-62.

• SEWM 2011 会议 • 上一篇    下一篇

结合相关类别信息的大规模文本层次分类研究

何世柱,王明文,周军军,石松   

  1. 江西师范大学计算机信息工程学院, 江西 南昌 330022
  • 收稿日期:2010-12-06 发布日期:2011-05-25
  • 作者简介:何世柱(1987- ),男,硕士研究生,主要研究方向为信息检索、文本挖掘等. Email:shizhuhe@gmail.com
  • 基金资助:

    国家自然科学基金资助项目(60963014);江西省自然科学基金资助项目(2008GZS0052)

Research on large-scale text hierarchies combining relevant category information

HE Shi-zhu, WANG Ming-wen, ZHOU Jun-jun, SHI Song   

  1. School of Computer Information Engineering, Jiangxi Normal University, Nanchang 330022, Jiangxi, China
  • Received:2010-12-06 Published:2011-05-25

摘要:

深层分类模型是一种解决大规模文本层次分类问题的有效范式。本文基于该范式提出一种改进型模型,首先将一种新方法用于单独评价搜索阶段的效果;然后利用类别和文档信息共同选择候选类别;最后基于类中心训练Rocchio分类器,同时利用相关类别的分类结果确定最终类别。在ODP数据集上的实验表明,相对于最新型的深层分类方法,该模型具有一定优势。

关键词: 深层分类;大规模层次;分层分类;Rocchio

Abstract:

The deep classification model is an effective paradigm for solving largescale classification problems. An improved model was proposed based on the paradigm. First, a new method was used to evaluate the effectiveness of search stage independently. Second, the category and document information were collectively used to select category candidates. Finally, the classifier of Rocchio was trained based on the class centroid, and at the same time the information of related categories was used to determine the final category. Experiments on the corpus ODP show that the proposed approach outperforms the other new  methods.

Key words:  outperforms deep classification; large scale hierarchy; hierarchical classification; rocchio

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!