short-paper

SPOT: Selecting occuPations frOm Trajectories

Authors:

Peipei Li,

Junjie Yao,

Liping Wang,

Xuemin LinAuthors Info & Claims

SIGIR '17: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval

Pages 813 - 816

https://doi.org/10.1145/3077136.3080651

Published: 07 August 2017 Publication History

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Abstract

With the pervasive availability of smart devices, billions of users' trajectories are recorded and collected. The aggregated human behaviors reveal users' interests and characteristics, becoming invaluable to reflect their demographic preference, i.e., gender, age, marital status and even personality, occupation. Occupation profiling from trajectory data is an attractive option for advertisement targeting and other applications, without severe privacy concerns. However, it carries great difficulties in sparsity and vagueness.

This paper proposes a novel approach, i.e., SPOT (Selecting occuPation frOm Trajectories). We first carefully analyze and report the trajectory pattern variance of different occupational categories in a large real dataset. And then we design novel ways to extract users content, location and transition preference, and finally illustrate a comprehensive occupation prediction method, Continuous Conditional Random Fields (C-CRF) based prediction model. Empirical studies confirm that the new approach works surprisingly well, and it shows the discriminative power of trajectory data to reveal occupational preference.

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Cited By

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Su YYao DZhou XZhang YFan YBai LBi JChen HDuh WHuang HKato MMothe JPoblete B(2023)TripSafe: Retrieving Safety-related Abnormal Trips in Real-time with Trajectory DataProceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3539618.3592074(2446-2450)Online publication date: 19-Jul-2023
https://dl.acm.org/doi/10.1145/3539618.3592074
Das MGhosh S(2020)Data-Driven Approaches for Spatio-Temporal Analysis: A Survey of the State-of-the-ArtsJournal of Computer Science and Technology10.1007/s11390-020-9349-035:3(665-696)Online publication date: 1-May-2020
https://dl.acm.org/doi/10.1007/s11390-020-9349-0

Index Terms

SPOT: Selecting occuPations frOm Trajectories
1. Information systems
  1. Information systems applications
    1. Data mining

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Information

Published In

SIGIR '17: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval

August 2017

1476 pages

ISBN:9781450350228

DOI:10.1145/3077136

General Chairs:
Noriko Kando
National Institute of Informatics
,
Tetsuya Sakai
Waseda University
,
Hideo Joho
University of Tsukuba
,
Program Chairs:
Hang Li
Huawei Noah's Ark Lab
,
Arjen P. de Vries
Radboud University
,
Ryen W. White
Microsoft Cortana

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 August 2017

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National Natural Science Foundation of China

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SIGIR '17

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SIGIR

SIGIR '17: The 40th International ACM SIGIR conference on research and development in Information Retrieval

August 7 - 11, 2017

Tokyo, Shinjuku, Japan

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SIGIR '17 Paper Acceptance Rate 78 of 362 submissions, 22%;

Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Cited By

View all

Su YYao DZhou XZhang YFan YBai LBi JChen HDuh WHuang HKato MMothe JPoblete B(2023)TripSafe: Retrieving Safety-related Abnormal Trips in Real-time with Trajectory DataProceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3539618.3592074(2446-2450)Online publication date: 19-Jul-2023
https://dl.acm.org/doi/10.1145/3539618.3592074
Das MGhosh S(2020)Data-Driven Approaches for Spatio-Temporal Analysis: A Survey of the State-of-the-ArtsJournal of Computer Science and Technology10.1007/s11390-020-9349-035:3(665-696)Online publication date: 1-May-2020
https://dl.acm.org/doi/10.1007/s11390-020-9349-0

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