Representative-based diversity retrieval

Chein Shung Hwang; Nai Wen Kuo; Ping Yu

doi:10.1109/ICICIC.2008.444

Representative-based diversity retrieval

Chein Shung Hwang, Nai Wen Kuo, Ping Yu

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

2 Citations (Scopus)

Abstract

Recently, case-based reasoning has been widely used in electronic commerce by providing product recommendations that are most similar to user's needs. However in some cases, the most similar recommendations are not necessary the ones most acceptable or useful. There is a growing awareness of the need for providing alternatives to similarity-based retrieval, alternatives that attempt to improve the recommendation diversity. In this paper, we present a new retrieval algorithm which is able to optimize the trade-off between similarity and diversity. Experimental results show that the proposed algorithm can achieve a better overall quality than other approaches.

Original language	English
Title of host publication	3rd International Conference on Innovative Computing Information and Control, ICICIC'08
DOIs	https://doi.org/10.1109/ICICIC.2008.444
Publication status	Published - Sept 30 2008
Externally published	Yes
Event	3rd International Conference on Innovative Computing Information and Control, ICICIC'08 - Dalian, Liaoning, China Duration: Jun 18 2008 → Jun 20 2008

Conference

Conference	3rd International Conference on Innovative Computing Information and Control, ICICIC'08
Country/Territory	China
City	Dalian, Liaoning
Period	6/18/08 → 6/20/08

ASJC Scopus subject areas

Computer Science Applications
Software
Control and Systems Engineering

Access to Document

10.1109/ICICIC.2008.444

Cite this

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title = "Representative-based diversity retrieval",

abstract = "Recently, case-based reasoning has been widely used in electronic commerce by providing product recommendations that are most similar to user's needs. However in some cases, the most similar recommendations are not necessary the ones most acceptable or useful. There is a growing awareness of the need for providing alternatives to similarity-based retrieval, alternatives that attempt to improve the recommendation diversity. In this paper, we present a new retrieval algorithm which is able to optimize the trade-off between similarity and diversity. Experimental results show that the proposed algorithm can achieve a better overall quality than other approaches.",

author = "Hwang, {Chein Shung} and Kuo, {Nai Wen} and Ping Yu",

year = "2008",

month = sep,

day = "30",

doi = "10.1109/ICICIC.2008.444",

language = "English",

isbn = "9780769531618",

booktitle = "3rd International Conference on Innovative Computing Information and Control, ICICIC'08",

note = "3rd International Conference on Innovative Computing Information and Control, ICICIC'08 ; Conference date: 18-06-2008 Through 20-06-2008",

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TY - GEN

T1 - Representative-based diversity retrieval

AU - Hwang, Chein Shung

AU - Kuo, Nai Wen

AU - Yu, Ping

PY - 2008/9/30

Y1 - 2008/9/30

N2 - Recently, case-based reasoning has been widely used in electronic commerce by providing product recommendations that are most similar to user's needs. However in some cases, the most similar recommendations are not necessary the ones most acceptable or useful. There is a growing awareness of the need for providing alternatives to similarity-based retrieval, alternatives that attempt to improve the recommendation diversity. In this paper, we present a new retrieval algorithm which is able to optimize the trade-off between similarity and diversity. Experimental results show that the proposed algorithm can achieve a better overall quality than other approaches.

AB - Recently, case-based reasoning has been widely used in electronic commerce by providing product recommendations that are most similar to user's needs. However in some cases, the most similar recommendations are not necessary the ones most acceptable or useful. There is a growing awareness of the need for providing alternatives to similarity-based retrieval, alternatives that attempt to improve the recommendation diversity. In this paper, we present a new retrieval algorithm which is able to optimize the trade-off between similarity and diversity. Experimental results show that the proposed algorithm can achieve a better overall quality than other approaches.

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U2 - 10.1109/ICICIC.2008.444

DO - 10.1109/ICICIC.2008.444

M3 - Conference contribution

AN - SCOPUS:52449124222

SN - 9780769531618

BT - 3rd International Conference on Innovative Computing Information and Control, ICICIC'08

T2 - 3rd International Conference on Innovative Computing Information and Control, ICICIC'08

Y2 - 18 June 2008 through 20 June 2008

ER -

Representative-based diversity retrieval

Abstract

Conference

ASJC Scopus subject areas

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