Search result diversification via data fusion

Shengli Wu, Chunlan Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

In recent years, researchers have investigated search result diversification through a variety of approaches.In such situations, information retrieval systems need to consider both aspects of relevance and diversity for those retrieved documents.On the other hand, previous research has demonstrated that data fusionis useful for improving performance when we are only concerned with relevance.However, it is not clear if it helps when both relevance and diversity are both taken into consideration. In this short paper, we propose a few data fusion methods to tryto improve performance when both relevance and diversity are concerned.Experiments are carried out with 3 groups of top-ranked results submitted to theTREC web diversity task. We find that data fusion is still a useful approach to performance improvement for diversity as for relevance previously.

Conference

ConferenceThe 37th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR '14, Gold Coast , QLD, Australia - July 06 - 11, 2014
Period1/01/14 → …

Fingerprint

Data fusion
Information retrieval systems
Experiments

Keywords

  • Search result diversification
  • data fusion
  • linear combination
  • weight assignment

Cite this

Wu, S., & Huang, C. (2014). Search result diversification via data fusion. In Unknown Host Publication (pp. 827-830) https://doi.org/10.1145/2600428.2609451
Wu, Shengli ; Huang, Chunlan. / Search result diversification via data fusion. Unknown Host Publication. 2014. pp. 827-830
@inproceedings{f971012fe0fa4960ae0884281f50ba46,
title = "Search result diversification via data fusion",
abstract = "In recent years, researchers have investigated search result diversification through a variety of approaches.In such situations, information retrieval systems need to consider both aspects of relevance and diversity for those retrieved documents.On the other hand, previous research has demonstrated that data fusionis useful for improving performance when we are only concerned with relevance.However, it is not clear if it helps when both relevance and diversity are both taken into consideration. In this short paper, we propose a few data fusion methods to tryto improve performance when both relevance and diversity are concerned.Experiments are carried out with 3 groups of top-ranked results submitted to theTREC web diversity task. We find that data fusion is still a useful approach to performance improvement for diversity as for relevance previously.",
keywords = "Search result diversification, data fusion, linear combination, weight assignment",
author = "Shengli Wu and Chunlan Huang",
year = "2014",
doi = "10.1145/2600428.2609451",
language = "English",
pages = "827--830",
booktitle = "Unknown Host Publication",

}

Wu, S & Huang, C 2014, Search result diversification via data fusion. in Unknown Host Publication. pp. 827-830, The 37th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR '14, Gold Coast , QLD, Australia - July 06 - 11, 2014, 1/01/14. https://doi.org/10.1145/2600428.2609451

Search result diversification via data fusion. / Wu, Shengli; Huang, Chunlan.

Unknown Host Publication. 2014. p. 827-830.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Search result diversification via data fusion

AU - Wu, Shengli

AU - Huang, Chunlan

PY - 2014

Y1 - 2014

N2 - In recent years, researchers have investigated search result diversification through a variety of approaches.In such situations, information retrieval systems need to consider both aspects of relevance and diversity for those retrieved documents.On the other hand, previous research has demonstrated that data fusionis useful for improving performance when we are only concerned with relevance.However, it is not clear if it helps when both relevance and diversity are both taken into consideration. In this short paper, we propose a few data fusion methods to tryto improve performance when both relevance and diversity are concerned.Experiments are carried out with 3 groups of top-ranked results submitted to theTREC web diversity task. We find that data fusion is still a useful approach to performance improvement for diversity as for relevance previously.

AB - In recent years, researchers have investigated search result diversification through a variety of approaches.In such situations, information retrieval systems need to consider both aspects of relevance and diversity for those retrieved documents.On the other hand, previous research has demonstrated that data fusionis useful for improving performance when we are only concerned with relevance.However, it is not clear if it helps when both relevance and diversity are both taken into consideration. In this short paper, we propose a few data fusion methods to tryto improve performance when both relevance and diversity are concerned.Experiments are carried out with 3 groups of top-ranked results submitted to theTREC web diversity task. We find that data fusion is still a useful approach to performance improvement for diversity as for relevance previously.

KW - Search result diversification

KW - data fusion

KW - linear combination

KW - weight assignment

U2 - 10.1145/2600428.2609451

DO - 10.1145/2600428.2609451

M3 - Conference contribution

SP - 827

EP - 830

BT - Unknown Host Publication

ER -

Wu S, Huang C. Search result diversification via data fusion. In Unknown Host Publication. 2014. p. 827-830 https://doi.org/10.1145/2600428.2609451