Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Dynamic Discovery of Type Classes and Relations in Semantic Web Data   The continuing development of Semantic Web technologies and the increasing
user adoption in the recent years have accelerated the progress incorporating
explicit semantics with data on the Web. With the rapidly growing RDF (Resource
Description Framework) data on the Semantic Web, processing large semantic
graph data have become more challenging. Constructing a summary graph structure
from the raw RDF can help obtain semantic type relations and reduce the
computational complexity for graph processing purposes. In this paper, we
addressed the problem of graph summarization in RDF graphs, and we proposed an
approach for building summary graph structures automatically from RDF graph
data. Moreover, we introduced a measure to help discover optimum class
dissimilarity thresholds and an effective method to discover the type classes
automatically. In future work, we plan to investigate further improvement
options on the scalability of the proposed method.

26
The categories of this paper are: bayes-an
30
The categories of this paper are: q-alg
8
The categories of this paper are: hep-ex
24
The categories of this paper are: dg-ga
11
The categories of this paper are: hep-lat
32
The categories of this paper are: atom-ph
27
The categories of this paper are: comp-gas
31
The categories of this paper are: ao-sci
37
The categories of this paper are: supr-con
13
The categories of this paper are: quant-ph
2
The categories of this paper are: math
29
The categories of this paper are: funct-an
5
The categories of this paper are: gr-qc
4
The categories of this paper are: cond-mat
10
The categories of this paper are: q-bio
21
The categories of this paper are: adap-org