Proximity and Direction-Based Subgroup Familiarity-Analysis Model

Jung In Choi; Hwan Seung Yong

doi:10.1007/978-981-10-6520-0_34

Proximity and Direction-Based Subgroup Familiarity-Analysis Model

Jung In Choi, Hwan Seung Yong

Computer Science & Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper, we have reported an effective model for familiarity analysis in indoor environments based on proximity and direction. We employ the positioning data of users; thus, we avoid recording the action or any conversation pertaining to the users. We use the beacon signal to find a user’s location and choose a subgroup, which is a temporary group obtained using the location of the users. The proposed method analyzes the familiarity using two different methods. The proximity-based method is used to calculate the familiarity based on the time for which the user has stayed in the subgroup. The direction-based method is used to calculate the familiarity based on the direction of each user in the subgroup. This study addressed situations arising in an event or a group activity in indoors to analyze the degree of familiarity by determining the location of a user.

Original language	English
Title of host publication	Proceedings of the 7th International Conference on Emerging Databases - Technologies, Applications, and Theory
Editors	Wonik Choi, Wookey Lee, Min Song, Sungwon Jung
Publisher	Springer Verlag
Pages	309-318
Number of pages	10
ISBN (Print)	9789811065194
DOIs	https://doi.org/10.1007/978-981-10-6520-0_34
State	Published - 2018
Event	7th International Conference on Emerging Databases: Technologies, Applications, and Theory, EDB 2017 - Busan, Korea, Republic of Duration: 7 Aug 2017 → 9 Aug 2017

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	461
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	7th International Conference on Emerging Databases: Technologies, Applications, and Theory, EDB 2017
Country/Territory	Korea, Republic of
City	Busan
Period	7/08/17 → 9/08/17

Keywords

Bluetooth low-energy beacon
Familiarity analysis
Indoor positioning
Subgroup analysis

Access to Document

10.1007/978-981-10-6520-0_34

Cite this

Choi, J. I., & Yong, H. S. (2018). Proximity and Direction-Based Subgroup Familiarity-Analysis Model. In W. Choi, W. Lee, M. Song, & S. Jung (Eds.), Proceedings of the 7th International Conference on Emerging Databases - Technologies, Applications, and Theory (pp. 309-318). (Lecture Notes in Electrical Engineering; Vol. 461). Springer Verlag. https://doi.org/10.1007/978-981-10-6520-0_34

@inproceedings{f15dc2dcdb6d4df7bac63da13b35b474,

title = "Proximity and Direction-Based Subgroup Familiarity-Analysis Model",

abstract = "In this paper, we have reported an effective model for familiarity analysis in indoor environments based on proximity and direction. We employ the positioning data of users; thus, we avoid recording the action or any conversation pertaining to the users. We use the beacon signal to find a user{\textquoteright}s location and choose a subgroup, which is a temporary group obtained using the location of the users. The proposed method analyzes the familiarity using two different methods. The proximity-based method is used to calculate the familiarity based on the time for which the user has stayed in the subgroup. The direction-based method is used to calculate the familiarity based on the direction of each user in the subgroup. This study addressed situations arising in an event or a group activity in indoors to analyze the degree of familiarity by determining the location of a user.",

keywords = "Bluetooth low-energy beacon, Familiarity analysis, Indoor positioning, Subgroup analysis",

author = "Choi, {Jung In} and Yong, {Hwan Seung}",

note = "Publisher Copyright: {\textcopyright} 2018, Springer Nature Singapore Pte Ltd.; 7th International Conference on Emerging Databases: Technologies, Applications, and Theory, EDB 2017 ; Conference date: 07-08-2017 Through 09-08-2017",

year = "2018",

doi = "10.1007/978-981-10-6520-0_34",

language = "English",

isbn = "9789811065194",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer Verlag",

pages = "309--318",

editor = "Wonik Choi and Wookey Lee and Min Song and Sungwon Jung",

booktitle = "Proceedings of the 7th International Conference on Emerging Databases - Technologies, Applications, and Theory",

}

Choi, JI & Yong, HS 2018, Proximity and Direction-Based Subgroup Familiarity-Analysis Model. in W Choi, W Lee, M Song & S Jung (eds), Proceedings of the 7th International Conference on Emerging Databases - Technologies, Applications, and Theory. Lecture Notes in Electrical Engineering, vol. 461, Springer Verlag, pp. 309-318, 7th International Conference on Emerging Databases: Technologies, Applications, and Theory, EDB 2017, Busan, Korea, Republic of, 7/08/17. https://doi.org/10.1007/978-981-10-6520-0_34

Proximity and Direction-Based Subgroup Familiarity-Analysis Model. / Choi, Jung In; Yong, Hwan Seung.
Proceedings of the 7th International Conference on Emerging Databases - Technologies, Applications, and Theory. ed. / Wonik Choi; Wookey Lee; Min Song; Sungwon Jung. Springer Verlag, 2018. p. 309-318 (Lecture Notes in Electrical Engineering; Vol. 461).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Proximity and Direction-Based Subgroup Familiarity-Analysis Model

AU - Choi, Jung In

AU - Yong, Hwan Seung

PY - 2018

Y1 - 2018

N2 - In this paper, we have reported an effective model for familiarity analysis in indoor environments based on proximity and direction. We employ the positioning data of users; thus, we avoid recording the action or any conversation pertaining to the users. We use the beacon signal to find a user’s location and choose a subgroup, which is a temporary group obtained using the location of the users. The proposed method analyzes the familiarity using two different methods. The proximity-based method is used to calculate the familiarity based on the time for which the user has stayed in the subgroup. The direction-based method is used to calculate the familiarity based on the direction of each user in the subgroup. This study addressed situations arising in an event or a group activity in indoors to analyze the degree of familiarity by determining the location of a user.

AB - In this paper, we have reported an effective model for familiarity analysis in indoor environments based on proximity and direction. We employ the positioning data of users; thus, we avoid recording the action or any conversation pertaining to the users. We use the beacon signal to find a user’s location and choose a subgroup, which is a temporary group obtained using the location of the users. The proposed method analyzes the familiarity using two different methods. The proximity-based method is used to calculate the familiarity based on the time for which the user has stayed in the subgroup. The direction-based method is used to calculate the familiarity based on the direction of each user in the subgroup. This study addressed situations arising in an event or a group activity in indoors to analyze the degree of familiarity by determining the location of a user.

KW - Bluetooth low-energy beacon

KW - Familiarity analysis

KW - Indoor positioning

KW - Subgroup analysis

UR - http://www.scopus.com/inward/record.url?scp=85032501550&partnerID=8YFLogxK

U2 - 10.1007/978-981-10-6520-0_34

DO - 10.1007/978-981-10-6520-0_34

M3 - Conference contribution

AN - SCOPUS:85032501550

SN - 9789811065194

T3 - Lecture Notes in Electrical Engineering

SP - 309

EP - 318

BT - Proceedings of the 7th International Conference on Emerging Databases - Technologies, Applications, and Theory

A2 - Choi, Wonik

A2 - Lee, Wookey

A2 - Song, Min

A2 - Jung, Sungwon

PB - Springer Verlag

T2 - 7th International Conference on Emerging Databases: Technologies, Applications, and Theory, EDB 2017

Y2 - 7 August 2017 through 9 August 2017

ER -