Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: R-Rec: A rule-based system for contextual suggestion using
  tag-description similarity   Contextual Suggestion deals with search techniques for complex information
needs that are highly focused on context and user needs. In this paper, we
propose \emph{R-Rec}, a novel rule-based technique to identify and recommend
appropriate points-of-interest to a user given her past preferences. We try to
embody the information that the user shares in the form of rating and tags of
any previous point(s)-of-interest and use it to rank the unrated candidate
suggestions. The ranking function is computed based on the similarity between a
suggestion and the places that the user like and the dissimilarity between the
suggestion and the places disliked by the user. Experiments carried out on
TREC-Contextual Suggestion 2015 dataset reveal the efficacy of our method.

20
The categories of this paper are: acc-phys
36
The categories of this paper are: cmp-lg
31
The categories of this paper are: ao-sci
22
The categories of this paper are: chao-dyn
8
The categories of this paper are: hep-ex
29
The categories of this paper are: funct-an
0
The categories of this paper are: hep-ph
16
The categories of this paper are: stat
4
The categories of this paper are: cond-mat
34
The categories of this paper are: chem-ph
9
The categories of this paper are: nlin
19
The categories of this paper are: eess
13
The categories of this paper are: quant-ph
26
The categories of this paper are: bayes-an
28
The categories of this paper are: alg-geom
23
The categories of this paper are: solv-int