JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2012, Vol. 42 ›› Issue (5): 35-40.

• Articles • Previous Articles     Next Articles

Research on Web negative information mining based on event ontology

LIU Dong-hui1,2, JIANG Wei1*   

  1. 1. School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221000, China; 2. Department of Computers, Lianyungang Teachers’ College, Lianyungang 222000, China
  • Received:2012-05-10 Online:2012-10-20 Published:2012-05-10

PDF (PC)

1294

Abstract: In order to mine the negative information on the internet, the eventbased semantic analysis technology was applied. The methods of event ontologybased Web negative information mining, especially event ontology construction and text feature reconstitution were studied. Information clustering was used as an example to validate the methods proposed. A prototype system based on event ontology was implemented. Experimental results showed that the average accuracy obtained by the event ontologybased and kmeans method was 721％, which increased by 53％ compared with the traditional kmeans clustering method.

Key words: Web mining, negative information, clustering, event ontology, information retrieval

CLC Number: 

  • TP393
[1] ZHANG Peirui, YANG Yan, XING Huanlai, YU Xiuying. Incremental multi-view clustering algorithm based on kernel K-means [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(3): 48-53.
[2] DU Xixi, LIU Huafeng, JING Liping. An additive co-clustering for recommendation of integrating social network [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(3): 96-102.
[3] YANG Tianpeng, XU Kunpeng, CHEN Lifei. Coefficient of variation clustering algorithm for non-uniform data [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(3): 140-145.
[4] PANG Renming, WANG Bo, YE Hao, ZHANG Haifeng, LI Mingliang. Clustering of blast furnace historical data based on PCA similarity factor and spectral clustering [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(5): 143-149.
[5] ZHOU Wang, ZHANG Chenlin, WU Jianxin. Qualitative balanced clustering algorithm based on Hartigan-Wong and Lloyd [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(5): 37-44.
[6] JI Xingquan, HAN Guozheng, LI Kejun, FU Rongrong, ZHU Yanghe. Application of improved K-means clustering algorithm based on density in distribution network block partitioning [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(4): 41-46.
[7] LI Shuo, SHI Yuliang. The method of spot cluster recommendation in location-based social networks [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(3): 44-50.
[8] JIANG Feng, DU Junwei, LIU Guozhu, SUI Yuefei. A weight-based initial centers selection algorithm for K-modes clustering [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(2): 29-34.
[9] FAN Shuyan, DING Shifei. An improved multi-scale Graph cut algorithm [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(1): 28-33.
[10] XU Pingan, TANG Yan, SHI Jiaokai, ZHANG Huirong. K-Means clustering algorithm based on the Schrödinger equation [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(1): 34-41.
[11] ZHU Hong, DING Shifei. Twice clustering method based on variable granularity [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2015, 45(3): 1-6.
[12] DONG Hongbin, ZHANG Guangjiang, PANG Jinwei, HAN Qilong. A clustering ensemble algorithm based on co-evolution [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2015, 45(2): 1-9.
[13] HAO Qingbo, MU Shaomin, YIN Chuanhuan, CHANG Tengteng, CUI Wenbin. An algorithm of fast local support vector machine based on clustering [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2015, 45(1): 13-18.
[14] YAO Huachuan, WANG Lizhen, WU Pingping, ZOU Muquan. AC_SAR: actionable clustering algorithm based on strong association rule [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2014, 44(6): 38-46.
[15] SI Junshu, ZHU Wenxing*, SHA Yonghe. A comprehensive method for traffic lights detection in complex background [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2014, 44(2): 64-68.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright 2018 © Editorial office of Journal of Shandong University (Engineering Science)
Supported by Beijing Magtech Co.Ltd