|本期目录/Table of Contents|

[1]高 翔,吴万琴.异质信息网络中基于聚类及链接分析的多样性挖掘技术[J].工业仪表与自动化装置,2014,(06):11-14.
　GAO Xiang,WU Wanqin.Cluster and link analysis based diversity data mining technology in heterogeneous information network[J].Industrial Instrumentation & Automation,2014,(06):11-14.
点击复制

异质信息网络中基于聚类及链接分析的多样性挖掘技术(PDF)

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2014年06期
页码:
11-14
栏目:
出版日期:
2014-12-15

文章信息/Info

Title:
Cluster and link analysis based diversity data mining technology in heterogeneous information network
作者:
高 翔; 吴万琴
（兰州文理学院 电子信息工程学院，兰州 730000）
Author(s):
GAO Xiang;  WU Wanqin
(School?of?Electronics?and?Information?Engineering，Lanzhou?University?of?Arts?and?Science， Lanzhou?730000，China)
关键词:
异质信息网络; 聚类算法; 链接分析; 排序模型; 多样性挖掘技术
Keywords:
heterogeneous information network;  clustering algorithm;  link analysis;  ranking model;  diversity data mining
分类号:
TP391.3
DOI:
-
文献标志码:
A
摘要:
提出基于聚类及链接分析的挖掘模型LinkNetClus，该模型将对象类型分为目标类型及属性类型，并假设目标对象属于每个簇的概率依赖于与之相关的其他对象，在目标对象上进行迭代的聚类操作，最终得到具有多样性的聚类结果。该模型充分利用了异质信息网络中的关联关系，得到多维的挖掘结果来解决数据冗余的问题，结果的可解释性也优于排序序列。通过实验证明了使用LinkNetClus得到的聚类结果比已有的基准方法提高大概30%～50%左右。
Abstract:
In this paper, the author proposes a mining model named LinkNetClus based on clustering and link analysis. Firstly, a star network is constructed, which has attribute objects and target objects. Assume that the generation probability of a target object is based on these associated attribute objects. Then these target objects will be clustered and get diversity results. The LinkNetClus model also uses the homogeneous and heterogeneous relationship between objects, and gets multidimensional ranking result to eliminate redundant information. Compared with the two-phrase ranking result, the result made by LinkNetClus is more understandable. Compared with the existing base method, Experiments show that the mining results based on LinkNetClus model is enhanced as many as 30%～50%.

参考文献/References:

[1] Edwards J, McCurley K S, Tomlin J A. An adaptive model for optimizing performance of an incremental web crawler [C]. Proceedings of the Tenth Conference on World Wide Web (Hong Kong: Elsevier Science): 106–113.

[2] 俞晓明,郭嘉丰,朱小飞,等.信息检索关键技术及高性能检索系统设计[J].信息技术快报,2010,8(4):39-50.
[3] L Page, S Brin, R Motwani, et al. The pagerank citation ranking: Bringing order to the web[C]. In Proceedings of the 7th International World Wide Web Conference,1998: 161-172.
[4] S Brin, L Page. The anatomy of a large-scale hypertextual web search engine[J]. Computer Networks and Isdn Systems, 1998,30(1-7):107-117.
[5] P Berkhin. Survey: A survey on pagerank computing[J]. Internet Mathematics,2005,2(1):112-134

相似文献/References:

备注/Memo

备注/Memo:
-
更新日期/Last Update: 1900-01-01