DocumentCode :
3282184
Title :
The maximal operator classifier
Author :
Yuqi Wang ; Wenqian Shang ; Shuchao Feng
Author_Institution :
Sch. of Comput. Sci., Commun. Univ. of China, Beijing, China
fYear :
2015
fDate :
June 28 2015-July 1 2015
Firstpage :
567
Lastpage :
570
Abstract :
The KNN is a classic text classification algorithm. In this paper, we propose a new text classification algorithm based on the KNN. We set a text similarity threshold to optimize the value of K. In this way, we can avoid the wrong result of classification led by the unbalance of sample size. In the meantime, we use the maximal operator to calculate the text similarity instead of cosine similarity. According to the experimental data, we have made a better classification result in this way.
Keywords :
pattern classification; text analysis; KNN; classic text classification algorithm; cosine similarity; maximal operator classifier; text similarity threshold; Algorithm design and analysis; Classification algorithms; Computer science; Correlation; Presses; Text categorization; Training; KNN; Maximal Operator; Similarity; Text Classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer and Information Science (ICIS), 2015 IEEE/ACIS 14th International Conference on
Conference_Location :
Las Vegas, NV
Type :
conf
DOI :
10.1109/ICIS.2015.7166657
Filename :
7166657
Link To Document :
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