Enhancing Group Recommendation by Knowledge Graph

Weiwei Deng; Peihu Zhu; Jian Ma

Enhancing Group Recommendation by Knowledge Graph

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

7 Citations (Scopus)

Abstract

With the rapid development of IT, more and more information/knowledge sharing and discovery activities are moved from offline to online and many online groups have been created to facilitate such activities. However, due to the information asymmetric and information overload problems, information/knowledge holders face difficulty disseminating their information/knowledge to online groups whose members are of interests. It is also difficult for groups of users to find the most related information/knowledge. Traditional individual recommendation techniques cannot solve this problem effectively because they cannot capture the preferences of a group of users. To generate recommendations for a group of users, this paper proposes a knowledge graph-enhanced group recommendation method in which knowledge graph is used to construct comprehensive profiles for groups and information/knowledge to be recommended. The proposed group recommendation method is evaluated with real-world data and the evaluation results demonstrate the effectiveness of the proposed method. © PACIS 2018.

Original language	English
Title of host publication	PACIS 2018 Proceedings
Subtitle of host publication	Opportunities and Challenges for the Digitized Society: Are We Ready?
Editors	Motonari Tanabu, Dai Senoo
Publisher	Association for Information Systems
ISBN (Print)	9784902590838
Publication status	Published - 2018
Event	22nd Pacific Asia Conference on Information Systems (PACIS 2018) - Yokohama Royal Park Hotel, Yokohama, Japan Duration: 26 Jun 2018 → 30 Jun 2018 https://aisel.aisnet.org/pacis2018/ http://pacis2018.org/index.html

Publication series

Name	Proceedings of the Pacific Asia Conference on Information Systems

Conference

Conference	22nd Pacific Asia Conference on Information Systems (PACIS 2018)
Abbreviated title	PACIS 2018
Country/Territory	Japan
City	Yokohama
Period	26/06/18 → 30/06/18
Internet address	https://aisel.aisnet.org/pacis2018/ http://pacis2018.org/index.html

Research Keywords

Group recommendation
knowledge graph
profile construction
recommendation service design

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https://aisel.aisnet.org/pacis2018/214

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Deng, W., Zhu, P., & Ma, J. (2018). Enhancing Group Recommendation by Knowledge Graph. In M. Tanabu, & D. Senoo (Eds.), PACIS 2018 Proceedings: Opportunities and Challenges for the Digitized Society: Are We Ready? Article 214 (Proceedings of the Pacific Asia Conference on Information Systems). Association for Information Systems. https://aisel.aisnet.org/pacis2018/214

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title = "Enhancing Group Recommendation by Knowledge Graph",

abstract = "With the rapid development of IT, more and more information/knowledge sharing and discovery activities are moved from offline to online and many online groups have been created to facilitate such activities. However, due to the information asymmetric and information overload problems, information/knowledge holders face difficulty disseminating their information/knowledge to online groups whose members are of interests. It is also difficult for groups of users to find the most related information/knowledge. Traditional individual recommendation techniques cannot solve this problem effectively because they cannot capture the preferences of a group of users. To generate recommendations for a group of users, this paper proposes a knowledge graph-enhanced group recommendation method in which knowledge graph is used to construct comprehensive profiles for groups and information/knowledge to be recommended. The proposed group recommendation method is evaluated with real-world data and the evaluation results demonstrate the effectiveness of the proposed method. {\textcopyright} PACIS 2018.",

keywords = "Group recommendation, knowledge graph, profile construction, recommendation service design",

author = "Weiwei Deng and Peihu Zhu and Jian Ma",

year = "2018",

language = "English",

isbn = "9784902590838",

series = "Proceedings of the Pacific Asia Conference on Information Systems",

publisher = "Association for Information Systems",

editor = "Motonari Tanabu and Dai Senoo",

booktitle = "PACIS 2018 Proceedings",

address = "United States",

note = "22nd Pacific Asia Conference on Information Systems (PACIS 2018), PACIS 2018 ; Conference date: 26-06-2018 Through 30-06-2018",

url = "https://aisel.aisnet.org/pacis2018/, http://pacis2018.org/index.html",

}

Deng, W , Zhu, P & Ma, J 2018, Enhancing Group Recommendation by Knowledge Graph. in M Tanabu & D Senoo (eds), PACIS 2018 Proceedings: Opportunities and Challenges for the Digitized Society: Are We Ready?., 214, Proceedings of the Pacific Asia Conference on Information Systems, Association for Information Systems, 22nd Pacific Asia Conference on Information Systems (PACIS 2018), Yokohama, Japan, 26/06/18. <https://aisel.aisnet.org/pacis2018/214>

Enhancing Group Recommendation by Knowledge Graph. / Deng, Weiwei ; Zhu, Peihu ; Ma, Jian.
PACIS 2018 Proceedings: Opportunities and Challenges for the Digitized Society: Are We Ready?. ed. / Motonari Tanabu; Dai Senoo. Association for Information Systems, 2018. 214 (Proceedings of the Pacific Asia Conference on Information Systems).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Enhancing Group Recommendation by Knowledge Graph

AU - Deng, Weiwei

AU - Zhu, Peihu

AU - Ma, Jian

PY - 2018

Y1 - 2018

N2 - With the rapid development of IT, more and more information/knowledge sharing and discovery activities are moved from offline to online and many online groups have been created to facilitate such activities. However, due to the information asymmetric and information overload problems, information/knowledge holders face difficulty disseminating their information/knowledge to online groups whose members are of interests. It is also difficult for groups of users to find the most related information/knowledge. Traditional individual recommendation techniques cannot solve this problem effectively because they cannot capture the preferences of a group of users. To generate recommendations for a group of users, this paper proposes a knowledge graph-enhanced group recommendation method in which knowledge graph is used to construct comprehensive profiles for groups and information/knowledge to be recommended. The proposed group recommendation method is evaluated with real-world data and the evaluation results demonstrate the effectiveness of the proposed method. © PACIS 2018.

AB - With the rapid development of IT, more and more information/knowledge sharing and discovery activities are moved from offline to online and many online groups have been created to facilitate such activities. However, due to the information asymmetric and information overload problems, information/knowledge holders face difficulty disseminating their information/knowledge to online groups whose members are of interests. It is also difficult for groups of users to find the most related information/knowledge. Traditional individual recommendation techniques cannot solve this problem effectively because they cannot capture the preferences of a group of users. To generate recommendations for a group of users, this paper proposes a knowledge graph-enhanced group recommendation method in which knowledge graph is used to construct comprehensive profiles for groups and information/knowledge to be recommended. The proposed group recommendation method is evaluated with real-world data and the evaluation results demonstrate the effectiveness of the proposed method. © PACIS 2018.

KW - Group recommendation

KW - knowledge graph

KW - profile construction

KW - recommendation service design

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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85067573381&origin=recordpage

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9784902590838

T3 - Proceedings of the Pacific Asia Conference on Information Systems

BT - PACIS 2018 Proceedings

A2 - Tanabu, Motonari

A2 - Senoo, Dai

PB - Association for Information Systems

T2 - 22nd Pacific Asia Conference on Information Systems (PACIS 2018)

Y2 - 26 June 2018 through 30 June 2018

ER -

Enhancing Group Recommendation by Knowledge Graph

Abstract

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Research Keywords

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