浏览全部资源
扫码关注微信
1. 浙江工商大学现代商贸研究中心,浙江 杭州310018
2. 浙江工商大学计算机与信息工程学院,浙江 杭州310018
3. 浙江工商大学工商管理学院,浙江 杭州310018
[ "琚春华(1962-),男,博士,浙江工商大学教授、博士生导师、校长助理,计算机与信息工程学院院长,主要研究方向为智能信息处理、数据挖掘、电子商务与物流优化等。。" ]
[ "鲍福光(1986-),男,浙江工商大学博士生,主要研究方向为智能信息处理、数据挖掘和供应链协同合作。" ]
[ "戴俊彦(1990-),男,浙江工商大学硕士生,主要研究方向为数据挖掘、智能信息处理等。" ]
网络出版日期:2016-07,
纸质出版日期:2016-07-15
移动端阅览
琚春华, 鲍福光, 戴俊彦. 一种融入公众情感投入分析的微博话题发现与细分方法[J]. 电信科学, 2016,32(7):97-105.
Chunhua JU, Fuguang BAO, Junyan DAI. Discovery and segmentation method in micro-blog topics based on public emotional engagement analysis[J]. Telecommunications science, 2016, 32(7): 97-105.
琚春华, 鲍福光, 戴俊彦. 一种融入公众情感投入分析的微博话题发现与细分方法[J]. 电信科学, 2016,32(7):97-105. DOI: 10.11959/j.issn.1000-0801.2016158.
Chunhua JU, Fuguang BAO, Junyan DAI. Discovery and segmentation method in micro-blog topics based on public emotional engagement analysis[J]. Telecommunications science, 2016, 32(7): 97-105. DOI: 10.11959/j.issn.1000-0801.2016158.
为了提升微博话题发现效率以及发现质量问题,提出了一种融入公众情感投入分析的微博话题快速发现与细分方法,促使话题演化,进而产生新话题及其情感变化趋势。首先,基于情感词典和TFDF值在历史语料库中挖掘常用情感词并构建情感词库;其次,快速抽取情感文本,结合Sigmoid函数检测情感投入密集期,保证话题事件挖掘的质量;最后,通过改进的模糊C-均值聚类算法在新的微博数据中发现高质量话题。实验结果表明,本文方法能够有效提升移动环境下的话题发现效率及质量。
To improve the discovery efficiency and quality of micro-blog topic
a method of rapid discovery and segmentation in micro-blog topics based on public emotional engagement analysis was proposed
it would prompt evolution of the topics
then generate new topics and gain emotional change trend.Firstly
common emotional words were mined from corpus to build emotional thesaurus based on emotional word dictionary and TFDF.Then
emotional text was extracted quickly and sigmoid function was utilized to detect the intensive period of emotional engagement
ensuring the validity of topic mining.Besides
an improved adaptive FCM was used to cluster and discover topics.The experimental results show that this method can enhance the efficiency and quality of topic discovery in mobile environment.
陈舜华 , 王晓彤 , 郝志峰 . 基于微博API的分布式抓取技术 [J ] . 电信科学 , 2013 , 29 ( 8 ): 146 - 149 .
CHEN S H , WANG X T , HAO Z F . A distributed data-crawling technology for microblog API [J ] . Telecommunications Science , 2013 , 29 ( 8 ): 146 - 149 .
张晓艳 , 王挺 . 话题发现与追踪技术研究 [J ] . 计算机科学与探索 , 2009 , 3 ( 4 ): 347 - 357 .
ZHANG X Y , WANG T . Research of technologies on topic detection and tracking [J ] . Journal of Frontiers of Computer Science & Technology , 2009 , 3 ( 4 ): 347 - 357 .
MCANDREW A J , MOSHFEGHI Y , JOSE J M . Building a large-scale corpus for evaluating event detection on Twitter [C ] // The 22nd ACM International Conference on Information &Knowledge Management , October 27 - November 1 , 2013 , San Francisco,USA . New York : ACM Press , 2013 : 409 - 418 .
李生琦 , 田巧燕 , 汤承 . 基于《<知网>》词汇语义相关度计算的消歧方法 [J ] . 情报学报 , 2009 , 28 ( 5 ): 706 - 711 .
LI S Q , TIAN Q Y , TANG C . Disambiguating method for computing relevancy based on HowNet semantic knowledge [J ] . Journal of the China Society for Scientific Andtechnical Information , 2009 , 28 ( 5 ): 706 - 711 .
O' CONNOR B , BALASUB R , ROUTLEDGE B R , et al . From tweets to polls: linking text sentiment to public opinion time series [C ] // The Fourth International AAAI Conference on Weblogs and Social Media , May 23 - 26 , 2010 , Washington,DC,USA . Palo Alto : AAAI Press , 2010 : 122 - 129 .
孙宏纲 , 陆余良 , 刘金红 , 等 . 基于HowNet的VSM模型扩展在文本分类中的应用研究 [J ] . 中文信息学报 , 2007 , 21 ( 6 ): 101 - 108 .
SUN H G , LU Y L , LIU J H , et al . A study of the application of VSM expansion in text categorization based on HowNet [J ] . Journal of Chinese Information Processing , 2007 , 21 ( 6 ): 101 - 108 .
KALEEL S B , ABHARI A . Cluster-discovery of Twitter messages for event detection and trending [J ] . Journal of Computational Science , 2015 ( 6 ): 47 - 57 .
张鲁民 , 贾焰 , 周斌 , 等 . 一种基于情感符号的在线突发事件检测方法 [J ] . 计算机学报 , 2013 , 36 ( 8 ): 1659 - 1667 .
ZHANG L M , JIA Y , ZHOU B , et al . Online bursty events detection based on emoticons [J ] . Chinese Journal of Computers , 2013 , 36 ( 8 ): 1659 - 1667 .
桂斌 , 杨小平 , 张中夏 , 等 . 基于微博表情符号的情感词典构建研究 [J ] . 北京理工大学学报 , 2014 ( 5 ): 537 - 541 .
GUI B , YANG X P , ZHANG Z X , et al . Research on building lexicon for sentiment analysis based on the Chinese microblogging [J ] . Journal of Beijing Institute of Technology , 2014 ( 5 ): 537 - 541 .
冯时 , 付永陈 , 阳锋 , 等 . 基于依存句法的博文情感倾向分析研究 [J ] . 计算机研究与发展 , 2012 ( 11 ): 2395 - 2406 .
FENG S , FU Y C , YANG F , et al . Blog sentiment orientation analysis based on dependency parsing [J ] . Journal of Computer Research and Development , 2012 ( 11 ): 2395 - 2406 .
陈旻 , 朱凡微 , 吴明晖 , 等 . 观点挖掘综述 [J ] . 浙江大学学报 ( 工学版 ), 2014 ( 8 ): 1461 - 1472 .
CHEN M , ZHU F W , WU M H , et al . Survey of opinion mining [J ] . Journal of Zhejiang University ( Engineering Science ), 2014 ( 8 ): 1461 - 1472 .
齐淼 , 张化祥 . 改进的模糊C-均值聚类算法研究 [J ] . 计算机工程与应用 , 2009 , 45 ( 20 ): 133 - 135 .
QI M , ZHANG H X . Research on modified fuzzy C-means clustering algorithm [J ] . Computer Engineering and Applications , 2009 , 45 ( 20 ): 133 - 135 .
范云满 , 马建霞 . 基于LDA与新兴主题特征分析的新兴主题探测研究 [J ] . 情报学报 , 2014 , 33 ( 7 ): 698 - 711 .
FAN Y M , MA J X . Detection of emerging topics based on LDA and feature analysis of emerging topics [J ] . Journal of the China Society for Scientific and Technical Information , 2014 , 33 ( 7 ): 698 - 711 .
贺亮 , 李芳 . 基于话题模型的科技文献话题发现和趋势分析 [J ] . 中文信息学报 , 2012 , 26 ( 2 ): 109 - 115 .
HE L , LI F . Topic discovery and trend analysis in scientific literature based on topic model [J ] . Journal of Chinese Information Processing , 2012 , 26 ( 2 ): 109 - 115 .
李庆虎 , 陈玉健 , 孙家广 . 一种中文分词词典新机制——双字哈希机制 [J ] . 中文信息学报 , 2003 , 17 ( 4 ): 13 - 18 .
LI Q H , CHEN Y J , SUN J G . A new dictionary mechanism for Chinese word segmentation [J ] . Journal of Chinese Information Processing , 2003 , 17 ( 4 ): 13 - 18 .
0
浏览量
740
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构