Complexity

Analysis and Applications of Location-Aware Big Complex Network Data


Publishing date
01 Jun 2019
Status
Published
Submission deadline
25 Jan 2019

Lead Editor
Guest Editors

1The University of Western Australia, Crawley, Australia

2RMIT University, Melbourne, Australia

3The Hong Kong Baptist University, Kowloon, Hong Kong

4Soochow University, Suzhou, China


Analysis and Applications of Location-Aware Big Complex Network Data

Description

In response to the ever-increasing challenges of location-aware network data like spatiosocial network and traffic network data, the network data processing technology is experiencing revolutionary changes in each stage including data collecting, cleaning, organizing, interpreting, analyzing, utilizing, and visualization. Those changes lead to a globally noticeable development trend of the convergence with big data frameworks, network analytical modeling, link or route prediction, and recommendation systems. This special issue aims at providing a forum to present recent advancements in the convergent research about big complex network data. Challenges include real-time event detection in a city, congestion discovery in a traffic network, location prediction of social users, social users’ behavior recognition in physical world, and unified systems of processing multidimensional complex network data. The robust solutions call for highly innovative techniques in the fields including, but not limited to, machine learning, genetic algorithms, chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory. The special issue will attract high-quality submissions of location-aware big complex network data from world-wide researchers in the areas of the machine learning, artificial intelligence, data mining, natural language processing, data and web mining, and big data management to utilize their expertise and match up to develop more efficient and practical algorithms or models to obtain smart knowledge from daily generated invaluable social network data and traffic network data.

Potential topics include but are not limited to the following:

  • Novel genetic algorithms to handle the problem complexity in location-aware social network
  • Sophisticated neural network structure predicting complex events in location-aware social network
  • Machine learning or deep learning in deriving social activities and behavioral metrics
  • Fuzzy modeling and control of chaotic systems to cope with data uncertainty
  • Spatial social influence learning modeling techniques
  • Parallel big data processing infrastructure to achieve real-time response to data analysis requests
  • Dynamic network data modeling using evolutionary game theory
  • Learning methods for social link prediction and revisit prediction in traffic network
  • Applications of any of the above methods and technologies

Articles

  • Special Issue
  • - Volume 2019
  • - Article ID 4027638
  • - Research Article

Edge Computing in an IoT Base Station System: Reprogramming and Real-Time Tasks

Huifeng Wu | Junjie Hu | ... | Danfeng Sun
  • Special Issue
  • - Volume 2019
  • - Article ID 4829164
  • - Research Article

A Novel Index Method for K Nearest Object Query over Time-Dependent Road Networks

Yajun Yang | Hanxiao Li | ... | Muxi Leng
  • Special Issue
  • - Volume 2019
  • - Article ID 8728245
  • - Research Article

Finding the Shortest Path with Vertex Constraint over Large Graphs

Yajun Yang | Zhongfei Li | ... | Qinghua Hu
  • Special Issue
  • - Volume 2019
  • - Article ID 5370961
  • - Research Article

Evaluation of Residential Housing Prices on the Internet: Data Pitfalls

Ming Li | Guojun Zhang | ... | Chunshan Zhou
  • Special Issue
  • - Volume 2019
  • - Article ID 4906903
  • - Research Article

Sign Prediction on Unlabeled Social Networks Using Branch and Bound Optimized Transfer Learning

Weiwei Yuan | Jiali Pang | ... | Mohammed Al-Dhelaan
  • Special Issue
  • - Volume 2019
  • - Article ID 8503962
  • - Research Article

Discovering Travel Community for POI Recommendation on Location-Based Social Networks

Lei Tang | Dandan Cai | ... | Hanbo Wang
  • Special Issue
  • - Volume 2019
  • - Article ID 4042624
  • - Research Article

A Block Object Detection Method Based on Feature Fusion Networks for Autonomous Vehicles

Qiao Meng | Huansheng Song | ... | Xiangqing Zhang
  • Special Issue
  • - Volume 2019
  • - Article ID 9301420
  • - Research Article

Promoting Geospatial Service from Information to Knowledge with Spatiotemporal Semantics

Jing Geng | Shuliang Wang | ... | Tianru Dai
  • Special Issue
  • - Volume 2019
  • - Article ID 7643905
  • - Research Article

A Destination Prediction Network Based on Spatiotemporal Data for Bike-Sharing

Jian Jiang | Fei Lin | ... | Jia Wu
  • Special Issue
  • - Volume 2018
  • - Article ID 6101409
  • - Research Article

Targeted Influential Nodes Selection in Location-Aware Social Networks

Susu Yang | Hui Li | Zhongyuan Jiang
Complexity
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 Journal metrics
Acceptance rate43%
Submission to final decision64 days
Acceptance to publication35 days
CiteScore3.200
Impact Factor2.462
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