[1]吴潇[],王磊[][]. 基于购物领域词典扩建的评论情感研究[J].计算机技术与发展,2017,27(07):194-199.
 WU Xiao[],WANG Lei[][]. Investigation on Sentiment of Reviews with Shopping Field Dictionary Construction[J].,2017,27(07):194-199.
点击复制

 基于购物领域词典扩建的评论情感研究()
分享到:

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
27
期数:
2017年07期
页码:
194-199
栏目:
应用开发研究
出版日期:
2017-07-10

文章信息/Info

Title:
 Investigation on Sentiment of Reviews with Shopping Field Dictionary Construction
文章编号:
1673-629X(2017)07-0194-06
作者:
 吴潇[1]王磊[1][2]
1. 南京邮电大学 宽带无线通信与传感网技术教育部重点实验室;2.东南大学 移动通信国家重点实验室
Author(s):
 WU Xiao[1] WANG Lei[1][2]
关键词:
 购物评论情感研究情感分类领域情感词典情感特征
Keywords:
 research on sentiment of shopping reviewssentiment classificationdomain emotional dictionaryemotional characteristics
分类号:
TP39
文献标志码:
A
摘要:
 针对购物评论中如何高效提取有用的情感信息,提出了构建领域情感词典进行评论情感分类方法.对购物评论语料进行分词去重,就各领域评论文本进行词性标注,选择词性为名词、形容词及部分其他词性的词语,通过计算该部分词语的PTF-IDF进行排序,设置阈值筛选后得到购物评论语料的领域情感词,从而构建领域情感词典.将该词典作为情感特征应用于购物评论情感分类实验中,并与基于普通情感词典分类方法的性能进行了分析比较.实验结果表明,利用提出方法进行购物评论情感分类的效果,尤其是在分类准确率方面要明显高于基于普通情感词典的情感分类方法,且所提出的方法可适用于各领域的购物评论,有效降低了情感特征空间的维度,具有普适性和可扩展性等优点.
Abstract:
 Aiming at effectively extracting sentimental information from the shopping reviews,a sentiment classification method has been proposed for online shopping reviews based on the construction of domain emotional dictionary,which segments words from the reviews corpus,nouns,adjectives and words of some other lexical category in the reviews after part of speech tagging.Sorting by calculating the PTF-IDF of words and setting threshold,selection of domain emotional words has been obtained to construct the domain emotional dictionary which has been applied to the sentiment classification of shopping reviews compared with the performance of the classification method based on the general sentiment dictionary.The experimental results show that the proposed method of shopping review sentiment classification is better than one based on general sentiment dictionary,and it can be applied to various fields for effectively reducing the dimension of the feature space,with universality and extensibility.

相似文献/References:

[1]张志宏,吴庆波,邵立松,等.基于飞腾平台TOE协议栈的设计与实现[J].计算机技术与发展,2014,24(07):1.
 ZHANG Zhi-hong,WU Qing-bo,SHAO Li-song,et al. Design and Implementation of TCP/IP Offload Engine Protocol Stack Based on FT Platform[J].,2014,24(07):1.
[2]梁文快,李毅. 改进的基因表达算法对航班优化排序问题研究[J].计算机技术与发展,2014,24(07):5.
 LIANG Wen-kuai,LI Yi. Research on Optimization of Flight Scheduling Problem Based on Improved Gene Expression Algorithm[J].,2014,24(07):5.
[3]黄静,王枫,谢志新,等. EAST文档管理系统的设计与实现[J].计算机技术与发展,2014,24(07):13.
 HUANG Jing,WANG Feng,XIE Zhi-xin,et al. Design and Implementation of EAST Document Management System[J].,2014,24(07):13.
[4]侯善江[],张代远[][][]. 基于样条权函数神经网络P2P流量识别方法[J].计算机技术与发展,2014,24(07):21.
 HOU Shan-jiang[],ZHANG Dai-yuan[][][]. P2P Traffic Identification Based on Spline Weight Function Neural Network[J].,2014,24(07):21.
[5]李璨,耿国华,李康,等. 一种基于三维模型的文物碎片线图生成方法[J].计算机技术与发展,2014,24(07):25.
 LI Can,GENG Guo-hua,LI Kang,et al. A Method of Obtaining Cultural Debris’ s Line Chart Based on Three-dimensional Model[J].,2014,24(07):25.
[6]翁鹤,皮德常. 混沌RBF神经网络异常检测算法[J].计算机技术与发展,2014,24(07):29.
 WENG He,PI De-chang. Chaotic RBF Neural Network Anomaly Detection Algorithm[J].,2014,24(07):29.
[7]刘茜[],荆晓远[],李文倩[],等. 基于流形学习的正交稀疏保留投影[J].计算机技术与发展,2014,24(07):34.
 LIU Qian[],JING Xiao-yuan[,LI Wen-qian[],et al. Orthogonal Sparsity Preserving Projections Based on Manifold Learning[J].,2014,24(07):34.
[8]尚福华,李想,巩淼. 基于模糊框架-产生式知识表示及推理研究[J].计算机技术与发展,2014,24(07):38.
 SHANG Fu-hua,LI Xiang,GONG Miao. Research on Knowledge Representation and Inference Based on Fuzzy Framework-production[J].,2014,24(07):38.
[9]叶偲,李良福,肖樟树. 一种去除运动目标重影的图像镶嵌方法研究[J].计算机技术与发展,2014,24(07):43.
 YE Si,LI Liang-fu,XIAO Zhang-shu. Research of an Image Mosaic Method for Removing Ghost of Moving Targets[J].,2014,24(07):43.
[10]余松平[][],蔡志平[],吴建进[],等. GSM-R信令监测选择录音系统设计与实现[J].计算机技术与发展,2014,24(07):47.
 YU Song-ping[][],CAI Zhi-ping[] WU Jian-jin[],GU Feng-zhi[]. Design and Implementation of an Optional Voice Recording System Based on GSM-R Signaling Monitoring[J].,2014,24(07):47.

更新日期/Last Update: 2017-08-24