Context-based traffic recommendation system

Khac Hoai Nam Bui; Xuan Hau Pham; Jason J. Jung; O. Joun Lee; Min Sung Hong

doi:10.1007/978-3-319-29236-6_13

Context-based traffic recommendation system

Khac Hoai Nam Bui, Xuan Hau Pham, Jason J. Jung, O. Joun Lee, Min Sung Hong

Department of Artificial Intelligence

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

2 Scopus citations

Abstract

In this paper, we propose a new traffic system recommendation based on support real-time flows in highly unpredictable sensor network environments. The approach system is real-time recommendation system which meet various demands of users. The proposed algorithm include two phases. First phase is proposed to deal with the real-time problem. By this way, the drivers are able to transfer on the way with the shortest-time. For second phase, a research algorithm based on Depth First Search (DFS) algorithm will recommend the paths which meet demands of drivers based their context such as the paths with include the famous landscapes or the paths where they can find out good restaurants for their break while driving.

Original language	English
Title of host publication	Context-Aware Systems and Applications - 4th International Conference, ICCASA 2015, Revised Selected Papers
Editors	Phan Cong Vinh, Vangalur Alagar
Publisher	Springer Verlag
Pages	122-131
Number of pages	10
ISBN (Print)	9783319292359
DOIs	https://doi.org/10.1007/978-3-319-29236-6_13
State	Published - 2016
Event	4th International Conference on Context-Aware Systems and Applications, ICCASA 2015 - Vung Tau, Viet Nam Duration: 26 Nov 2015 → 27 Nov 2015

Publication series

Name	Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume	165
ISSN (Print)	1867-8211

Conference

Conference	4th International Conference on Context-Aware Systems and Applications, ICCASA 2015
Country/Territory	Viet Nam
City	Vung Tau
Period	26/11/15 → 27/11/15

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NRF-2014R1A2A2A05007154). Also, this research was supported by the MSIP Ministry of Science, ICT and Future Planning), Korea, under the ITRC(Information Technology Research Center) support program (IITP-2015-H8501-15-1018) supervised by the IITP(Institute for Information and communications Technology Promotion).

Publisher Copyright:
© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2016.

Keywords

DFS algorithm
Recommendation system
Sensor network

Access to Document

10.1007/978-3-319-29236-6_13

Cite this

Bui, K. H. N., Pham, X. H., Jung, J. J., Lee, O. J., & Hong, M. S. (2016). Context-based traffic recommendation system. In P. C. Vinh, & V. Alagar (Eds.), Context-Aware Systems and Applications - 4th International Conference, ICCASA 2015, Revised Selected Papers (pp. 122-131). (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 165). Springer Verlag. https://doi.org/10.1007/978-3-319-29236-6_13

Bui, Khac Hoai Nam ; Pham, Xuan Hau ; Jung, Jason J. et al. / Context-based traffic recommendation system. Context-Aware Systems and Applications - 4th International Conference, ICCASA 2015, Revised Selected Papers. editor / Phan Cong Vinh ; Vangalur Alagar. Springer Verlag, 2016. pp. 122-131 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST).

@inproceedings{873899f09d444e6fb2b972e195229889,

title = "Context-based traffic recommendation system",

abstract = "In this paper, we propose a new traffic system recommendation based on support real-time flows in highly unpredictable sensor network environments. The approach system is real-time recommendation system which meet various demands of users. The proposed algorithm include two phases. First phase is proposed to deal with the real-time problem. By this way, the drivers are able to transfer on the way with the shortest-time. For second phase, a research algorithm based on Depth First Search (DFS) algorithm will recommend the paths which meet demands of drivers based their context such as the paths with include the famous landscapes or the paths where they can find out good restaurants for their break while driving.",

keywords = "DFS algorithm, Recommendation system, Sensor network",

author = "Bui, {Khac Hoai Nam} and Pham, {Xuan Hau} and Jung, {Jason J.} and Lee, {O. Joun} and Hong, {Min Sung}",

note = "Funding Information: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NRF-2014R1A2A2A05007154). Also, this research was supported by the MSIP Ministry of Science, ICT and Future Planning), Korea, under the ITRC(Information Technology Research Center) support program (IITP-2015-H8501-15-1018) supervised by the IITP(Institute for Information and communications Technology Promotion). Publisher Copyright: {\textcopyright} ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2016.; 4th International Conference on Context-Aware Systems and Applications, ICCASA 2015 ; Conference date: 26-11-2015 Through 27-11-2015",

year = "2016",

doi = "10.1007/978-3-319-29236-6_13",

language = "English",

isbn = "9783319292359",

series = "Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST",

publisher = "Springer Verlag",

pages = "122--131",

editor = "Vinh, {Phan Cong} and Vangalur Alagar",

booktitle = "Context-Aware Systems and Applications - 4th International Conference, ICCASA 2015, Revised Selected Papers",

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}

Bui, KHN, Pham, XH, Jung, JJ, Lee, OJ & Hong, MS 2016, Context-based traffic recommendation system. in PC Vinh & V Alagar (eds), Context-Aware Systems and Applications - 4th International Conference, ICCASA 2015, Revised Selected Papers. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol. 165, Springer Verlag, pp. 122-131, 4th International Conference on Context-Aware Systems and Applications, ICCASA 2015, Vung Tau, Viet Nam, 26/11/15. https://doi.org/10.1007/978-3-319-29236-6_13

Context-based traffic recommendation system. / Bui, Khac Hoai Nam; Pham, Xuan Hau; Jung, Jason J. et al.
Context-Aware Systems and Applications - 4th International Conference, ICCASA 2015, Revised Selected Papers. ed. / Phan Cong Vinh; Vangalur Alagar. Springer Verlag, 2016. p. 122-131 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 165).

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

TY - GEN

T1 - Context-based traffic recommendation system

AU - Bui, Khac Hoai Nam

AU - Pham, Xuan Hau

AU - Jung, Jason J.

AU - Lee, O. Joun

AU - Hong, Min Sung

N1 - Funding Information: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NRF-2014R1A2A2A05007154). Also, this research was supported by the MSIP Ministry of Science, ICT and Future Planning), Korea, under the ITRC(Information Technology Research Center) support program (IITP-2015-H8501-15-1018) supervised by the IITP(Institute for Information and communications Technology Promotion). Publisher Copyright: © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2016.

PY - 2016

Y1 - 2016

N2 - In this paper, we propose a new traffic system recommendation based on support real-time flows in highly unpredictable sensor network environments. The approach system is real-time recommendation system which meet various demands of users. The proposed algorithm include two phases. First phase is proposed to deal with the real-time problem. By this way, the drivers are able to transfer on the way with the shortest-time. For second phase, a research algorithm based on Depth First Search (DFS) algorithm will recommend the paths which meet demands of drivers based their context such as the paths with include the famous landscapes or the paths where they can find out good restaurants for their break while driving.

AB - In this paper, we propose a new traffic system recommendation based on support real-time flows in highly unpredictable sensor network environments. The approach system is real-time recommendation system which meet various demands of users. The proposed algorithm include two phases. First phase is proposed to deal with the real-time problem. By this way, the drivers are able to transfer on the way with the shortest-time. For second phase, a research algorithm based on Depth First Search (DFS) algorithm will recommend the paths which meet demands of drivers based their context such as the paths with include the famous landscapes or the paths where they can find out good restaurants for their break while driving.

KW - DFS algorithm

KW - Recommendation system

KW - Sensor network

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DO - 10.1007/978-3-319-29236-6_13

M3 - Conference contribution

AN - SCOPUS:84964031090

SN - 9783319292359

T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST

SP - 122

EP - 131

BT - Context-Aware Systems and Applications - 4th International Conference, ICCASA 2015, Revised Selected Papers

A2 - Vinh, Phan Cong

A2 - Alagar, Vangalur

PB - Springer Verlag

T2 - 4th International Conference on Context-Aware Systems and Applications, ICCASA 2015

Y2 - 26 November 2015 through 27 November 2015

ER -

Bui KHN, Pham XH, Jung JJ, Lee OJ, Hong MS. Context-based traffic recommendation system. In Vinh PC, Alagar V, editors, Context-Aware Systems and Applications - 4th International Conference, ICCASA 2015, Revised Selected Papers. Springer Verlag. 2016. p. 122-131. (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST). doi: 10.1007/978-3-319-29236-6_13

Context-based traffic recommendation system

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