Excellence in Research and Innovation for Humanity

ICSMEAM 2017 : 19th International Conference on Social Media Engineering, Analysis and Mining

London, United Kingdom
September 21 - 22, 2017

Conference Code: 17UK09ICSMEAM

Conference Proceedings

All submitted conference papers will be blind peer reviewed by three competent reviewers. The peer-reviewed conference proceedings are indexed in the International Science Index (ISI), Google Scholar, Semantic Scholar, Zenedo, OpenAIRE, BASE, WorldCAT, Sherpa/RoMEO, and other index databases. Impact Factor Indicators.

Special Journal Issues

ICSMEAM 2017 has teamed up with the Special Journal Issue on Social Media Engineering, Analysis and Mining. A number of selected high-impact full text papers will also be considered for the special journal issues. All submitted papers will have the opportunity to be considered for this Special Journal Issue. The paper selection will be carried out during the peer review process as well as at the conference presentation stage. Submitted papers must not be under consideration by any other journal or publication. The final decision for paper selection will be made based on peer review reports by the Guest Editors and the Editor-in-Chief jointly. Selected full-text papers will be published online free of charge.

Conference Sponsor and Exhibitor Opportunities

The Conference offers the opportunity to become a conference sponsor or exhibitor. To participate as a sponsor or exhibitor, please download and complete the Conference Sponsorship Request Form.

Important Dates

Abstracts/Full-Text Paper Submission Deadline   July 31, 2017
Notification of Acceptance/Rejection   August 14, 2017
Final Paper (Camera Ready) Submission & Early Bird Registration Deadline   August 21, 2017
Conference Dates   September 21 - 22, 2017

Important Notes

Please ensure your submission meets the conference's strict guidelines for accepting scholarly papers. Downloadable versions of the check list for Full-Text Papers and Abstract Papers.

Please refer to the Paper Submission GUIDE before submitting your paper.

Selected Conference Papers

1) Noise Reduction in Web Data: A Learning Approach Based on Dynamic User Interests
Julius Onyancha, Valentina Plekhanova
2) Evaluating Machine Learning Techniques for Activity Classification in Smart Home Environments
Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard
3) Cognition of Driving Context for Driving Assistance
Manolo Dulva Hina, Clement Thierry, Assia Soukane, Amar Ramdane-Cherif
4) Hybrid Reliability-Similarity-Based Approach for Supervised Machine Learning
Walid Cherif
5) Hybrid Approach for Software Defect Prediction Using Machine Learning with Optimization Technique
C. Manjula, Lilly Florence
6) Optimized Preprocessing for Accurate and Efficient Bioassay Prediction with Machine Learning Algorithms
Jeff Clarine, Chang-Shyh Peng, Daisy Sang
7) Comparative Evaluation of Accuracy of Selected Machine Learning Classification Techniques for Diagnosis of Cancer: A Data Mining Approach
Rajvir Kaur, Jeewani Anupama Ginige
8) Optimization of Slider Crank Mechanism Using Design of Experiments and Multi-Linear Regression
Galal Elkobrosy, Amr M. Abdelrazek, Bassuny M. Elsouhily, Mohamed E. Khidr
9) Socio-Technical Systems: Transforming Theory into Practice
L. Ngowi, N. H. Mvungi
10) Missing Link Data Estimation with Recurrent Neural Network: An Application Using Speed Data of Daegu Metropolitan Area
JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim
11) Adaption Model for Building Agile Pronunciation Dictionaries Using Phonemic Distance Measurements
Akella Amarendra Babu, Rama Devi Yellasiri, Natukula Sainath
12) Hand Gesture Detection via EmguCV Canny Pruning
N. N. Mosola, S. J. Molete, L. S. Masoebe, M. Letsae
13) A Comprehensive Evaluation of Supervised Machine Learning for the Phase Identification Problem
Brandon Foggo, Nanpeng Yu
14) Automated User Story Driven Approach for Web-Based Functional Testing
Mahawish Masud, Muhammad Iqbal, M. U. Khan, Farooque Azam
15) Building a Scalable Telemetry Based Multiclass Predictive Maintenance Model in R
Jaya Mathew

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