CFTDISM:Clustering Financial Text Documents Using Improved Similarity Measure

被引:0
作者
Srikanth, Panigrahi [1 ]
Deverapalli, Dharmaiah [2 ]
机构
[1] VNR Vignana Jyothi Inst Engn & Technol, Dept IT, Hyderabad, India
[2] Shri Vishnu Engn Coll Woman, Fac Informat Technol, Bhimavaram, India
来源
2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMPUTING RESEARCH (ICCIC) | 2017年
关键词
Financial Text Documents; Clustering; Financial System Features; Information Gain and Clustering Algorithm; FEATURE-SELECTION METHODS;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Financial Text Documents is one of the research domain build variety of applications. Mostly text processing techniques solve financial text problems. Dimensionality reduction process one the major challenging in text processing. Text features retained it helps to performing defines text clustering. Text clustering of similarity measure treats as the similarity between two text documents. The Main objective this paper defines and design suitable similarity measure motived from [18-21] and proposed similarity measure improves the previous measure [34]. This processes representation of financial system features initialized process based defined as Clusters.
引用
收藏
页码:865 / 868
页数:4
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