Title :
An improved documents classification technique using association rules mining
Author :
Mohammad Naved Qureshi;Hassan Faisal Hamood Aldheleai;Yahya Kord Tamandani
Author_Institution :
Electrical Engineering Section, University Polytechnic, AMU, Aligarh 202002, India
Abstract :
Classification is gaining interest among the researchers in the area of data mining because of huge textual availability of data throughout the web. Document Classification technique aims to classify the documents to one or multiple classes labels based on their contents. Recently classification is being done using the association rules technique. Hence, Associative Classification can be applied for mining text documents. Associative classification methods can be applicable to different classification problems as it is simple and highly accurate. This paper provides an efficient approach for mining the rules from the text documents using Apriori algorithm and also an effective rule pruning method has been proposed and applied on the experimental datasets. Results on the huge set of text documents do show the suggested algorithms which boost the accuracy of classification as compared with. other normal classification techniques and also some other associative classification techniques.
Keywords :
"Training","Classification algorithms","Data mining","Algorithm design and analysis","Prediction algorithms","Predictive models","Buildings"
Conference_Titel :
Research in Computational Intelligence and Communication Networks (ICRCICN), 2015 IEEE International Conference on
DOI :
10.1109/ICRCICN.2015.7434283