Cognitive Computing - ICCC 2020
4th International Conference, Held as Part of the Services Conference Federation, SCF 2020, Honolulu, HI, USA, September 18-20, 2020, Proceedings
Published on 13. September 2020
XIV, 125 pages
978-3-030-59585-2 (ISBN)
Description
This book constitutes the proceedings of the International Conference on Cognitive Computing, ICCC 2020, held as part of SCF 2020 in Honolulu, HI, USA, in September 2020.
The conference was held virtually due to the COVID-19 pandemic. The 8 full and 2 short papers presented in this volume were carefully reviewed and selected from 20 submissions. The papers cover all aspects of Sensing Intelligence (SIJ as a Service (SlaaS). Cognitive Computing is a sensing-driven computing (SDC) scheme that explores and integrates intelligence from all types of senses in various scenarios and solution contexts.
The conference was held virtually due to the COVID-19 pandemic. The 8 full and 2 short papers presented in this volume were carefully reviewed and selected from 20 submissions. The papers cover all aspects of Sensing Intelligence (SIJ as a Service (SlaaS). Cognitive Computing is a sensing-driven computing (SDC) scheme that explores and integrates intelligence from all types of senses in various scenarios and solution contexts.
More details
Series
Edition
1st ed. 2020
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Product notice
Reflowable
Illustrations
XIV, 125 p. 30 illus., 18 illus. in color.
ISBN-13
978-3-030-59585-2 (9783030595852)
DOI
10.1007/978-3-030-59585-2
Schweitzer Classification
Other editions
Additional editions
Yujiu Yang | Lei Yu | Liang-Jie Zhang
Cognitive Computing - ICCC 2020
4th International Conference, Held as Part of the Services Conference Federation, SCF 2020, Honolulu, HI, USA, September 18-20, 2020, Proceedings
Book
09/2020
Springer
€53.49
Shipment within 7-9 days
Content
- Intro
- Preface
- Organization
- Conference Sponsor - Services Society
- About the Services Conference Federation (SCF)
- Contents
- Research Track
- HFF: Hybrid Feature Fusion Model for Click-Through Rate Prediction
- 1 Introduction
- 2 Related Work
- 3 Our Model
- 3.1 Embedding Layer
- 3.2 Feature Interaction Layer
- 3.3 Feature Fusion Layer
- 3.4 Prediction Layer
- 4 Experiments
- 4.1 Datasets
- 4.2 Data Preparation
- 4.3 Experimental Results
- 4.4 Analysis
- 5 Conclusion
- References
- PRTransE: Emphasize More Important Facts Based on Pagerank for Knowledge Graph Completion
- 1 Introduction
- 2 Related Work
- 2.1 Translation-Based Models
- 2.2 Other Models
- 3 Model
- 3.1 PRTransE
- 3.2 Entity Importance
- 3.3 Relation Importance
- 3.4 Triplet Importance
- 4 Experiments and Analysis
- 4.1 Datasets and Evaluation Protocol
- 4.2 Experiment Setup
- 4.3 Link Prediction
- 5 Conclusion
- References
- Context Based Quantum Language Model with Application to Question Answering
- 1 Introduction
- 2 Related Work
- 3 Basic Concepts
- 4 Context Based Quantum Language Model
- 4.1 Word Encoder
- 4.2 Sentence Density Matrix with Hidden Projector
- 4.3 Sentence Feature Selection and Matching
- 5 Experiment
- 5.1 Datasets and Evaluation Metrics
- 5.2 Baselines
- 5.3 Implementation Details
- 5.4 Experimental Results
- 6 Discussion
- 7 Conclusion
- References
- Improving Fake Product Detection with Aspect-Based Sentiment Analysis
- 1 Introduction
- 2 Related Work
- 3 Method
- 3.1 CNN-LSTM
- 3.2 Attention-Based ABSA
- 3.3 Fake Product Detection
- 4 Experiments
- 4.1 Dataset
- 4.2 Experiment Settings
- 4.3 Results and Analysis
- 5 Conclusion
- References
- A Dual Layer Regression Model for Cross-border E-commerce Industry Sale and Hot Product Prediction
- 1 Introduction
- 2 Related Work
- 3 Dataset Construction
- 4 Methodology
- 4.1 Problem Description
- 4.2 Dual Layer Regression Model
- 4.3 Model Training
- 5 Experimentation
- 5.1 Experimental Settings
- 5.2 Results and Analysis
- 5.3 Ablation Study
- 5.4 Limitations and Further Discussion
- 6 Conclusion
- References
- End-to-End Nested Multi-Attention Network for 3D Brain Tumor Segmentation
- 1 Introduction
- 2 Related Work
- 3 Nested Multi-Attention Network
- 3.1 Nested Organs Segmentation Problem
- 3.2 Nested Multi-Attention Network Framework
- 3.3 Training
- 3.4 Evaluation Metrics
- 4 Experiments and Results
- 4.1 Dataset and Pre-processing
- 4.2 Implementation Details
- 4.3 Results Analysis
- 4.4 Extensive Discussions
- 5 Conclusion
- References
- Application Track
- ALBERT-Based Chinese Named Entity Recognition
- 1 Introduction
- 2 Related Work
- 3 ALBERT Model
- 4 Approaches
- 4.1 Motivation
- 4.2 Architecture of the Proposed Method
- 5 Experiments
- 5.1 Experimental Setup
- 5.2 Experimental Results
- 6 Conclusion
- References
- Cognitive and Predictive Analytics on Big Open Data
- 1 Introduction
- 2 Related Works
- 3 Our Big Data Analytic Approach
- 3.1 An Overview of Our Approach
- 3.2 Detailed Description of Our Approach
- 4 Evaluation
- 4.1 Results from Frequent Pattern Mining
- 4.2 Results from Association Rule Mining and Associative Classification
- 5 Conclusions
- References
- Short Paper Track
- Semantic Enhancement Based Dynamic Construction of Domain Knowledge Graph
- 1 Introduction
- 2 Methodology
- 2.1 Entity Recognition by Combining LSTM and CRF
- 2.2 Topic Model Based Semantic Enhancement
- 2.3 Heuristic Querying Rules
- 2.4 Dynamic Update of KG
- 3 Evaluation
- 3.1 Setting
- 3.2 Results
- 4 Related Work
- 5 Conclusion
- References
- Traffic Incident Detection from Massive Multivariate Time-Series Data
- 1 Introduction
- 2 Related Work
- 3 Data
- 3.1 Sensor Data
- 3.2 CHP Data
- 3.3 Relating Sensor Data to CHP Data
- 4 Method
- 4.1 Models
- 4.2 Engineered Features
- 4.3 Sparse/Unbalanced Data
- 5 Results
- 6 Conclusions and Future Work
- References
- Author Index
