Evidence map›Paper›PMID 30190540›Full record

ArticleScientific reports2018

Link Prediction based on Quantum-Inspired Ant Colony Optimization.

Zhiwei Cao, Yichao Zhang, Jihong Guan, Shuigeng Zhou

Abstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Zhiwei CaoDepartment of Computer Science and Technology, Tongji University, 4800 Cao'an Road, Shanghai, 201804, China.
Yichao ZhangDepartment of Computer Science and Technology, Tongji University, 4800 Cao'an Road, Shanghai, 201804, China.
Jihong GuanDepartment of Computer Science and Technology, Tongji University, 4800 Cao'an Road, Shanghai, 201804, China. jhguan@tongji.edu.cn.
Shuigeng ZhouShanghai Key Laboratory of Intelligent Information Processing, Shanghai, 200433, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Incomplete or partial observations of network structures pose a serious challenge to theoretical and engineering studies of real networks. To remedy the missing links in real datasets, topology-based link prediction is introduced into the studies of various networks. Due to the complexity of network structures, the accuracy and robustness of most link prediction algorithms are not satisfying enough. In this paper, we propose a quantum-inspired ant colony optimization algorithm that integrates ant colony optimization and quantum computing to predict links in networks. Extensive experiments on both synthetic and real networks show that the accuracy and robustness of the new algorithm is competitive in respect to most of the state of the art algorithms. This result suggests that the application of intelligent optimization to link prediction is promising for boosting its accuracy and robustness.

Identifiers

PMID30190540
PMCPMC6127200

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.