PMID- 26963089
OWN - NLM
STAT- MEDLINE
DCOM- 20160801
LR  - 20160324
IS  - 1932-6203 (Electronic)
IS  - 1932-6203 (Linking)
VI  - 11
IP  - 3
DP  - 2016
TI  - IRLT: Integrating Reputation and Local Trust for Trustworthy Service 
      Recommendation in Service-Oriented Social Networks.
PG  - e0151438
LID - 10.1371/journal.pone.0151438 [doi]
LID - e0151438
AB  - With the prevalence of Social Networks (SNs) and services, plenty of trust models 
      for Trustworthy Service Recommendation (TSR) in Service-oriented SNs (S-SNs) have 
      been proposed. The reputation-based schemes usually do not contain user 
      preferences and are vulnerable to unfair rating attacks. Meanwhile, the local 
      trust-based schemes generally have low reliability or even fail to work when the 
      trust path is too long or does not exist. Thus it is beneficial to integrate them 
      for TSR in S-SNs. This work improves the state-of-the-art Combining Global and 
      Local Trust (CGLT) scheme and proposes a novel Integrating Reputation and Local 
      Trust (IRLT) model which mainly includes four modules, namely Service 
      Recommendation Interface (SRI) module, Local Trust-based Trust Evaluation (LTTE) 
      module, Reputation-based Trust Evaluation (RTE) module and Aggregation Trust 
      Evaluation (ATE) module. Besides, a synthetic S-SN based on the famous Advogato 
      dataset is deployed and the well-known Discount Cumulative Gain (DCG) metric is 
      employed to measure the service recommendation performance of our IRLT model with 
      comparing to that of the excellent CGLT model. The results illustrate that our 
      IRLT model is slightly superior to the CGLT model in honest environment and 
      significantly outperforms the CGLT model in terms of the robustness against 
      unfair rating attacks.
FAU - Liu, Zhiquan
AU  - Liu Z
AD  - School of Computer Science and Technology, Xidian University, Xi'an, Shaanxi, 
      China.
FAU - Ma, Jianfeng
AU  - Ma J
AD  - School of Computer Science and Technology, Xidian University, Xi'an, Shaanxi, 
      China.
AD  - School of Cyber Engineering, Xidian University, Xi'an, Shaanxi, China.
FAU - Jiang, Zhongyuan
AU  - Jiang Z
AD  - School of Cyber Engineering, Xidian University, Xi'an, Shaanxi, China.
FAU - Miao, Yinbin
AU  - Miao Y
AD  - School of Telecommunication Engineering, Xidian University, Xi'an, Shaanxi, 
      China.
FAU - Gao, Cong
AU  - Gao C
AD  - School of Computer Science and Technology, Xidian University, Xi'an, Shaanxi, 
      China.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20160310
PL  - United States
TA  - PLoS One
JT  - PloS one
JID - 101285081
SB  - IM
MH  - Humans
MH  - *Models, Theoretical
MH  - *Social Support
MH  - *Trust
PMC - PMC4786195
COIS- Competing Interests: The authors have declared that no competing interests exist.
EDAT- 2016/03/11 06:00
MHDA- 2016/08/02 06:00
PMCR- 2016/03/10
CRDT- 2016/03/11 06:00
PHST- 2016/01/29 00:00 [received]
PHST- 2016/02/29 00:00 [accepted]
PHST- 2016/03/11 06:00 [entrez]
PHST- 2016/03/11 06:00 [pubmed]
PHST- 2016/08/02 06:00 [medline]
PHST- 2016/03/10 00:00 [pmc-release]
AID - PONE-D-16-04167 [pii]
AID - 10.1371/journal.pone.0151438 [doi]
PST - epublish
SO  - PLoS One. 2016 Mar 10;11(3):e0151438. doi: 10.1371/journal.pone.0151438. 
      eCollection 2016.