Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: TraLFM: Latent Factor Modeling of Traffic Trajectory Data   The widespread use of positioning devices (e.g., GPS) has given rise to a
vast body of human movement data, often in the form of trajectories.
Understanding human mobility patterns could benefit many location-based
applications. In this paper, we propose a novel generative model called TraLFM
via latent factor modeling to mine human mobility patterns underlying traffic
trajectories. TraLFM is based on three key observations: (1) human mobility
patterns are reflected by the sequences of locations in the trajectories; (2)
human mobility patterns vary with people; and (3) human mobility patterns tend
to be cyclical and change over time. Thus, TraLFM models the joint action of
sequential, personal and temporal factors in a unified way, and brings a new
perspective to many applications such as latent factor analysis and next
location prediction. We perform thorough empirical studies on two real
datasets, and the experimental results confirm that TraLFM outperforms the
state-of-the-art methods significantly in these applications.

19
The categories of this paper are: eess
13
The categories of this paper are: quant-ph
31
The categories of this paper are: ao-sci
2
The categories of this paper are: math
12
The categories of this paper are: nucl-th
10
The categories of this paper are: q-bio
15
The categories of this paper are: nucl-ex
26
The categories of this paper are: bayes-an
6
The categories of this paper are: astro-ph
17
The categories of this paper are: q-fin
8
The categories of this paper are: hep-ex
4
The categories of this paper are: cond-mat
36
The categories of this paper are: cmp-lg
30
The categories of this paper are: q-alg
20
The categories of this paper are: acc-phys
27
The categories of this paper are: comp-gas