Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Energy saving in smart homes based on consumer behaviour: A case study   This paper presents a case study of a recommender system that can be used to
save energy in smart homes without lowering the comfort of the inhabitants. We
present an algorithm that uses consumer behavior data only and uses machine
learning to suggest actions for inhabitants to reduce the energy consumption of
their homes. The system mines for frequent and periodic patterns in the event
data provided by the Digitalstrom home automation system. These patterns are
converted into association rules, prioritized and compared with the current
behavior of the inhabitants. If the system detects an opportunities to save
energy without decreasing the comfort level it sends a recommendation to the
residents.

9
The categories of this paper are: nlin
23
The categories of this paper are: solv-int
35
The categories of this paper are: mtrl-th
34
The categories of this paper are: chem-ph
27
The categories of this paper are: comp-gas
5
The categories of this paper are: gr-qc
28
The categories of this paper are: alg-geom
20
The categories of this paper are: acc-phys
13
The categories of this paper are: quant-ph
0
The categories of this paper are: hep-ph
29
The categories of this paper are: funct-an
31
The categories of this paper are: ao-sci
37
The categories of this paper are: supr-con
18
The categories of this paper are: econ
14
The categories of this paper are: math-ph
22
The categories of this paper are: chao-dyn