Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Similarity Measure Development for Case-Based Reasoning- A Data-driven
  Approach   In this paper, we demonstrate a data-driven methodology for modelling the
local similarity measures of various attributes in a dataset. We analyse the
spread in the numerical attributes and estimate their distribution using
polynomial function to showcase an approach for deriving strong initial value
ranges of numerical attributes and use a non-overlapping distribution for
categorical attributes such that the entire similarity range [0,1] is utilized.
We use an open source dataset for demonstrating modelling and development of
the similarity measures and will present a case-based reasoning (CBR) system
that can be used to search for the most relevant similar cases.

19
The categories of this paper are: eess
33
The categories of this paper are: plasm-ph
4
The categories of this paper are: cond-mat
25
The categories of this paper are: patt-sol
16
The categories of this paper are: stat
7
The categories of this paper are: hep-th
13
The categories of this paper are: quant-ph
22
The categories of this paper are: chao-dyn
34
The categories of this paper are: chem-ph
21
The categories of this paper are: adap-org
24
The categories of this paper are: dg-ga
18
The categories of this paper are: econ
10
The categories of this paper are: q-bio
15
The categories of this paper are: nucl-ex
27
The categories of this paper are: comp-gas
28
The categories of this paper are: alg-geom