Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Local Music Event Recommendation with Long Tail Artists   In this paper, we explore the task of local music event recommendation. Many
local artists tend to be obscure long-tail artists with a small digital
footprint. That is, it can be hard to find social tag and artist similarity
information for many of the artists who are playing shows in the local music
community. To address this problem, we explore using Latent Semantic Analysis
(LSA) to embed artists and tags into a latent feature space and examine how
well artists with small digital footprints are represented in this space. We
find that only a relatively small digital footprint is needed to effectively
model artist similarity. We also introduce the concept of a Music Event Graph
as a data structure that makes it easy and efficient to recommend events based
on user-selected genre tags and popular artists. Finally, we conduct a small
user study to explore the feasibility of our proposed system for event
recommendation.

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The categories of this paper are: econ
6
The categories of this paper are: astro-ph
13
The categories of this paper are: quant-ph
19
The categories of this paper are: eess
14
The categories of this paper are: math-ph
28
The categories of this paper are: alg-geom
34
The categories of this paper are: chem-ph
4
The categories of this paper are: cond-mat
25
The categories of this paper are: patt-sol
2
The categories of this paper are: math
12
The categories of this paper are: nucl-th
15
The categories of this paper are: nucl-ex
35
The categories of this paper are: mtrl-th
26
The categories of this paper are: bayes-an
33
The categories of this paper are: plasm-ph
37
The categories of this paper are: supr-con