Personalized expert-based recommender system: Training C-SVM for personalized expert identification

Yeounoh Chung; Hye Wuk Jung; Jaekwang Kim; Jee Hyong Lee

doi:10.1007/978-3-642-39712-7_33

Personalized expert-based recommender system: Training C-SVM for personalized expert identification

Yeounoh Chung
, Hye Wuk Jung
, Jaekwang Kim
, Jee Hyong Lee

Sungkyunkwan University

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

6 Scopus citations

Abstract

In order to improve the performance of the existing recommendation algorithms, previous researches on expert-based recommender systems have exploited the knowledge of experts. However, the previous expert-based recommender systems are limited in that the same experts are suggested for all users. In this paper, we study personalized expert identification problem, assuming each user needs different kinds and levels of expert help. We demonstrate the feasibility of personalized expert-based recommendation; we present and analyze an SVM framework for finding personalized experts.

Original language	English
Title of host publication	Machine Learning and Data Mining in Pattern Recognition - 9th International Conference, MLDM 2013, Proceedings
Pages	434-441
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-642-39712-7_33
State	Published - 2013
Event	9th International Conference on International Conference on Machine Learning and Data Mining, MLDM 2013 - New York, NY, United States Duration: 19 Jul 2013 → 25 Jul 2013

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7988 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	9th International Conference on International Conference on Machine Learning and Data Mining, MLDM 2013
Country/Territory	United States
City	New York, NY
Period	19/07/13 → 25/07/13

Keywords

Collaborative Filtering (CF)
Expert-based Recommender System
Personalized Expert
Support Vector Machine (SVM)

Access to Document

10.1007/978-3-642-39712-7_33

Cite this

Chung, Y., Jung, H. W., Kim, J., & Lee, J. H. (2013). Personalized expert-based recommender system: Training C-SVM for personalized expert identification. In Machine Learning and Data Mining in Pattern Recognition - 9th International Conference, MLDM 2013, Proceedings (pp. 434-441). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7988 LNAI). https://doi.org/10.1007/978-3-642-39712-7_33

Chung, Yeounoh ; Jung, Hye Wuk ; Kim, Jaekwang et al. / Personalized expert-based recommender system : Training C-SVM for personalized expert identification. Machine Learning and Data Mining in Pattern Recognition - 9th International Conference, MLDM 2013, Proceedings. 2013. pp. 434-441 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{ea61089b2fda4510a2c8eda7fd31ff79,

title = "Personalized expert-based recommender system: Training C-SVM for personalized expert identification",

abstract = "In order to improve the performance of the existing recommendation algorithms, previous researches on expert-based recommender systems have exploited the knowledge of experts. However, the previous expert-based recommender systems are limited in that the same experts are suggested for all users. In this paper, we study personalized expert identification problem, assuming each user needs different kinds and levels of expert help. We demonstrate the feasibility of personalized expert-based recommendation; we present and analyze an SVM framework for finding personalized experts.",

keywords = "Collaborative Filtering (CF), Expert-based Recommender System, Personalized Expert, Support Vector Machine (SVM)",

author = "Yeounoh Chung and Jung, \{Hye Wuk\} and Jaekwang Kim and Lee, \{Jee Hyong\}",

year = "2013",

doi = "10.1007/978-3-642-39712-7\_33",

language = "English",

isbn = "9783642397110",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "434--441",

booktitle = "Machine Learning and Data Mining in Pattern Recognition - 9th International Conference, MLDM 2013, Proceedings",

note = "9th International Conference on International Conference on Machine Learning and Data Mining, MLDM 2013 ; Conference date: 19-07-2013 Through 25-07-2013",

}

Chung, Y, Jung, HW, Kim, J & Lee, JH 2013, Personalized expert-based recommender system: Training C-SVM for personalized expert identification. in Machine Learning and Data Mining in Pattern Recognition - 9th International Conference, MLDM 2013, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7988 LNAI, pp. 434-441, 9th International Conference on International Conference on Machine Learning and Data Mining, MLDM 2013, New York, NY, United States, 19/07/13. https://doi.org/10.1007/978-3-642-39712-7_33

Personalized expert-based recommender system: Training C-SVM for personalized expert identification. / Chung, Yeounoh; Jung, Hye Wuk; Kim, Jaekwang et al.
Machine Learning and Data Mining in Pattern Recognition - 9th International Conference, MLDM 2013, Proceedings. 2013. p. 434-441 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7988 LNAI).

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

TY - GEN

T1 - Personalized expert-based recommender system

T2 - 9th International Conference on International Conference on Machine Learning and Data Mining, MLDM 2013

AU - Chung, Yeounoh

AU - Jung, Hye Wuk

AU - Kim, Jaekwang

AU - Lee, Jee Hyong

PY - 2013

Y1 - 2013

N2 - In order to improve the performance of the existing recommendation algorithms, previous researches on expert-based recommender systems have exploited the knowledge of experts. However, the previous expert-based recommender systems are limited in that the same experts are suggested for all users. In this paper, we study personalized expert identification problem, assuming each user needs different kinds and levels of expert help. We demonstrate the feasibility of personalized expert-based recommendation; we present and analyze an SVM framework for finding personalized experts.

AB - In order to improve the performance of the existing recommendation algorithms, previous researches on expert-based recommender systems have exploited the knowledge of experts. However, the previous expert-based recommender systems are limited in that the same experts are suggested for all users. In this paper, we study personalized expert identification problem, assuming each user needs different kinds and levels of expert help. We demonstrate the feasibility of personalized expert-based recommendation; we present and analyze an SVM framework for finding personalized experts.

KW - Collaborative Filtering (CF)

KW - Expert-based Recommender System

KW - Personalized Expert

KW - Support Vector Machine (SVM)

UR - https://www.scopus.com/pages/publications/84881230826

U2 - 10.1007/978-3-642-39712-7_33

DO - 10.1007/978-3-642-39712-7_33

M3 - Conference contribution

AN - SCOPUS:84881230826

SN - 9783642397110

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 434

EP - 441

BT - Machine Learning and Data Mining in Pattern Recognition - 9th International Conference, MLDM 2013, Proceedings

Y2 - 19 July 2013 through 25 July 2013

ER -

Chung Y, Jung HW, Kim J , Lee JH. Personalized expert-based recommender system: Training C-SVM for personalized expert identification. In Machine Learning and Data Mining in Pattern Recognition - 9th International Conference, MLDM 2013, Proceedings. 2013. p. 434-441. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-39712-7_33

Personalized expert-based recommender system: Training C-SVM for personalized expert identification

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