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Generating Highly Accurate Predictions for Missing QoS Data via Aggregating Nonnegative Latent Factor Models
Xin Luo
,
Meng Chu Zhou
, Yunni Xia
, Qingsheng Zhu
, Ahmed Chiheb Ammari
, Ahmed Alabdulwahab
Electrical and Computer Engineering
Research output
:
Contribution to journal
›
Article
›
peer-review
248
Scopus citations
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Dive into the research topics of 'Generating Highly Accurate Predictions for Missing QoS Data via Aggregating Nonnegative Latent Factor Models'. Together they form a unique fingerprint.
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Keyphrases
Quality of Service
100%
Prediction Accuracy
100%
Highly Accurate
100%
Service Data
100%
Non-negative Latent Factor Model
100%
Quality of Service Prediction
40%
Motivation
20%
Reliability Prediction
20%
Service-oriented
20%
Learning Task
20%
Service-oriented Computing
20%
Web Service Selection
20%
Feature Samples
20%
Ensemble Model
20%
Non-negativity Constraint
20%
Service Invocation
20%
Computer Science
Quality of Service
100%
Prediction Accuracy
42%
And-States
14%
Comparison Result
14%
Research Topic
14%
Web Service
14%
Service Selection
14%
Service Invocation
14%
Real Data Sets
14%