Abstract:
Classification is a data mining or machine learning
technique used to predict group membership for data
instances. Several major kinds of classification
method including decision tree induction method,
Bayesian networks method, k-nearest neighbor
classification method, case-based reasoning, genetic
algorithm and fuzzy logic techniques. Classification
is the task of deciding whether a paper belongs to a
set of pre-specified classes of papers. Automatic
classification schemes can greatly facilitate the
process of categorization. Categorization of
documents is challenging, as the number of
discriminating words can be very large. In this paper,
we presented categorization of publication papers
by applying k-nearest neighbor classification using
the Euclidean Distance measure.K-nearest neighbor
method is the simplest and most straightforward
method among all classification methods. Hence, knearest
neighbor method is used to classify different
number of nearest neighbors for different categories,
rather than a fixed number across all categories in
this system.This system is intended to classify
different categories from different papers in data sets
and to save time for searching papers.
