Special Sessions
Special Session 1:
2nd Special Session on Intelligent Data MiningPaper List
Special Session 2:
GrC 2016: Data Science and ComputingSpecial Session 1:
2nd Special Session on Intelligent Data Mining
Dec.5-8, 2016 Washington D.C., USARecent developments in processing, storing, and sharing huge amount of data become problem due to the lack of new approaches, techniques, methods, algorithms and technologies. Researchers try to find proper solutions based on their experiences and make contributions to current data mining and classification knowledge. This approach actually causes new set of problems due to the missing theoretical notions, lack of necessary disciplines and insufficient awareness on data security, information retrieval, social networking within behavioral and social and ethical issues. This special session seeks solutions on interdisciplinary gaps between data and intelligent approaches.
The AI & ML fields are interdisciplinary, including computer science, mathematics, psychology, linguistics, philosophy and neuroscience. There is no software or hardware available to solve problems like human's do. Researchers only make assumptions to replicate biological architectures. So, the brain is capable of change and recognizes experiences. Every day, there are more than 7 billion people works for processing limitless number of data like a single computer through sophisticated cloud networks. Each brain has own big data warehouse and biological CPU.
Nowadays, researchers use interdisciplinary way to understand knowledge among all types of resource including data, document, tool, device, experience, process and people. This approach may help to understand biological evolution to propose robust and powerful approaches between human nature and big data processing.
Intelligent Data Mining term is not only related to Computer Science. This special session opens to every researcher as well as industrial partners to make contribution.
The aims of this Special Session on Intelligent Data Mining are to:
- Bring researchers and experts together to discuss and share their experiences
- Share the current and new research topics and ideas,
- Improve and enhance personal, enterprise, national and international awareness,
- Provide a platform to present and discuss recent advancements,
- Increase international collaborations among university–industry-institutions,
in the fields of theory and applications of data mining, artificial intelligence, computer science, mathematics, psychology, linguistics, philosophy, neuroscience and other disciplines to discuss better understanding of big data and intelligence.
The papers submitted to this special session might be in a large range of topics that include theory, application and implementation of artificial intelligence, machine learning and data mining including the topics given below,
Use of Artificial Intelligence | Machine Learning in Big Data as
- Data Mining, Data Science and Big Data,
- Data Warehouse, Clustering, Visualization
- Security, Privacy,
- Big DaaS
- Scalable Computing, Cloud Computing,
- Knowledge Discovery, Integration, Transformation
- Information Retrieval,
- Data Classification, Regression, Cleaning,
- Smart Cities & Energy
- Social Media, Social Networking, Social Data,
- Semantics,
- IoT
- Multimedia
- Mobile Computing
- Sensors, Networks, Devices
- Mathematics,
- Psychology,
- Linguistics,
- Philosophy,
- Neuroscience,
- Biometric,
- Sustainability
- Human Biology,
- Bioinformatics,
- Cognitive Science,
- Surveillance,
- Business Intelligence,
- Recent Theory, Trends, Technologies and Applications,
- Future Directions and Challenges in Intelligent Data Mining ,
- Industrial Challenges in Intelligent Data Mining ,
- Demo Applications,
Papers should be submitted for this special session by Sept 23, 2016, at the conference special session submission system (http://cci.drexel.edu/bigdata/bigdata2016/PaperSubmission.html). Papers should be submitted as a pdf in 2-column IEEE format. Detailed instructions for the authors can be found at the conference website. Accepted papers will be published in the conference proceedings. All accepted papers must be presented by one of the author/s in the conference to include the article in the proceedings.
If you have any question about this special session, please do not hesitate to direct your question to the special session organizer Dr. Uraz Yavanoglu (urazyavanoglu@gmail.com, uraz.yavanoglu@asu.edu)
Special Session Organizer:
Dr. Uraz Yavanoglu
Department of Computer Engineering
Gazi University, Turkey
www.druraz.com
Postdoctoral Scholar
School of Computing, Informatics, and Decision Systems Engineering
Arizona State University, USA
The important dates for this special session are:
Full Paper Submission Deadline : Sept 23, 2016 11:59pm PST
Notification of Acceptance : Oct 24, 2016
Camera-ready papers & Pre-registration : Nov 5, 2016, 11:59pm PST
Conference Dates : Dec 5-8, 2016
For Paper Submission, please click here
Special Session 1 Accepted Papers
| Paper List |
|---|
| Francisco Padillo, José María Luna, and Sebastián Ventura Subgroup Discovery on Big Data: pruning the search space on exhaustive search algorithms |
| Abdulkadir KAYIKLI, Zehra Aysun ALTIKARDES, Hayriye KORKMAZ, Ali Serdar FAK, Hasan ERDAL, and Ahmet Fevzi BABA A Novel Method for Prediction Dipper/Non-dipper Pattern In Hypertension Patients |
| Hsiao-Wei Hu, Hao-Chen Chang, and Wen-Shiu Lin From Big Data to Big Challenge: An optimized frequent pattern mining algorithm with multiple minimum supports |
| Thamarai Selvi Somasundaram, Kannan Govindarajan, and Vivekanandan Suresh Kumar Swarm Intelligence (SI) based Profiling and Scheduling of Big Data Applications |
| Chenyu Zhai and jing peng Mining Latent Features from Reviews and Ratings for Item Recommendation |
| Sachin Kumar, Saibal K Pal, and Rampal Singh Smart Home: Accurate Prediction of Energy Consumption with Extreme Learning Machine Variants |
| Busra Mutlu, Merve Mutlu, Kasim Oztoprak, and Erdogan Dogdu Identifying Trolls and Determining Terror Awareness Level in Social Networks Using a Scalable Framework |
| Quanzhi Li Classifying Tables in Financial Documents |
| Kai Zhao, Sasu Tarkoma, Siyuan Liu, and Huy Vo Urban Human Mobility Data Mining: An Overview |
| Murat Ozbayoglu, Gokhan Kucukayan, and Erdogan Dogdu A Real-Time Autonomous Highway Accident Detection Model Based on Big Data Processing and Computational Intelligence |
| Jenq-Haur Wang and Jia-Zhi Lin Improving Clustering Efficiency by SimHash-based K-Means Algorithm for Big Data Analytics |
| Sercan Kulcu and Erdogan Dogdu A Survey on Semantic Web and Big Data Technologies for Social Network Analysis |
| Paul Raff and Ze Jin The Difference-of-Datasets Framework: A Statistical Method to Discover Insight |
| Ammar Jakabji and Hasan Dağ Improving item-based recommendation accuracy with user's preferences on Apache Mahout |
| Omer Berat Sezer, Erdogan Dogdu, Murat Ozbayoglu, and Aras Can Onal An Extended IoT Framework with Semantics, Big Data, and Analytics |
| Madhu Shashanka, Min-Yi Shen, and Jisheng Wang User and Entity Behavior Analytics for Enterprise Security |
| Nora Alkhamees and Maria Fasli Event Detection from Social Network Streams Using Frequent Pattern Mining with Dynamic Support Values |
| Ozlem Yavanoglu Intelligent Authorship Identification with using Turkish Newspapers Metadata |
| Brahim Hnich, Ata Sasmaz, O¨ zkan Sayın, Faisal R. Al-Osaimid, and Amine Lamine Smart Online Vehicle Tracking System for Security Applications |
| Sampath Jayarathna and Faryaneh Poursardar Change Detection and Classification of Digital Collections |
| Feyza Yıldırım Okay and Suat Özdemir A Secure Data Aggregation Protocol for Fog Computing Based Smart Grids |
| Yerzhan Kerimbekov and Hasan Şakir Bilge A feature selection method based on Lorentzian metric |
| ismail duru, Gülüstan Doğan, and Banu Diri An Overview Of Studies About Students' Performance Analysis and Learning Analytics in MOOCs |
| Aparna Oruganti, Fangzhou Sun, Hiba Baroud, and Abhishek Dubey DelayRadar: A Multivariate Predictive Model for Transit Systems |
| Giuseppe Bruno Text Mining and Sentiment Extraction in Central Bank Documents |
| Xiao Li, Reza Sharifi Sedeh, Liao Wang, and Yang Yang PATIENT-RECORD LEVEL INTEGRATION OF DE-IDENTIFIED HEALTHCARE BIG DATABASES |
| Jianbo Yuan, Walid Shalaby, Mohammed Korayem, David Lin, and Khalifeh AlJadda Solving Cold Start Problem in Large-scale Recommendation Engines: A Deep Learning Approach |
| Yehezkel Resheff Online Trajectory Segmentation and Summary With Applications to Visualization and Retrieval |
| Yiheng Zhou, Numair Sani, and Jiebo Luo Fine-grained Mining of Illicit Drug Use Patterns Using Social Multimedia Data from Instagram |
| Chengcheng Wan, Yanmin Zhu, Jiadi Yu, and Yanyan Shen SMOPAT: Mining Semantic Mobility Patterns from Trajectories of Private Vehicles |
| Bingchuan Liu, Yudong Tan, and Huimin Zhou A Bayesian Predictor of Airline Class Seats Based on Multinomial Event Model |
| Ali Sekmen, Akram Aldroubi, Ahmet Bugra Koku, and Ahmet Faruk Cakmak Skeleton Decomposition Analysis for Subspace Clustering |
| Yuchen Wu, Jianbo Yuan, Quanzeng You, and Jiebo Luo The Effect of Pets on Happiness: A Data-Driven Approach via Large-Scale Social Media |
| Omair Shafiq Event Segmentation using Parallel MRK-Means Clustering based on MapReduce |
| Victor Perazzolo Barros and Pollyana Notargiacomo Big Data Analytics in Cloud Gaming: Players' Patterns Recognition using Artificial Neural Networks |
| Nada Basit, Yutong Zhang, Hao Wu, Haoran Liu, Jieming Bin, Yijun He, and Abdeltawab Hendawi MapReduce-based Deep Learning With Handwritten Digit Recognition Case Study |
| Soukaina Filali Boubrahimi, Berkay Aydin, Dustin Kempton, and Rafal Angryk Visualizing Solar Event Data Using Heterogenous Data Sources |
| Jaroslav Cechak, Philip Thruesen, Blandine Seznec, Roel Castano, and Nattiya Kanhabua To Link or Not to Link: Ranking Hyperlinks in Wikipedia using Collective Attention |
Special Session 2:
GrC 2016: Data Science and Computing
Dec.5-8, 2016 Washington D.C., USAGranular Computing (GrC) is a general computation theory for effectively using granules such as classes, clusters, subsets, groups and intervals to build an efficient computational model for complex applications with huge amounts of data, information and knowledge. Though the label is relatively recent, the basic notions and principles of granular computing, though under different names, have appeared in many related fields, such as information hiding in programming, granularity in artificial intelligence, divide and conquer in theoretical computer science, interval computing, cluster analysis, fuzzy and rough set theories, neutrosophic computing, quotient space theory, belief functions, machine learning, databases, and many others.
GrC 2016 Special Symposium: Data Science and Computing will continue to address the issues related to Granular Computing and its applications. it will provide researchers from universities, laboratories and industry to present state-of-the-art research results and methodologies in theory and applications of granular computing, including rough sets as special form for granulation. The conference will also make it possible for researchers and developers to highlight their new research directions and new interactions with novel computing models. To broaden more impact on granular computing and its applications, It will focus on currently important major research tracks such as social network computing, cloud computing, computer security, data mining, soft computing ( neural networks, fuzzy systems, evolutionary computation, rough sets), e-Intelligence (Web intelligence, semantic Web, Web informatics), bioinformatics, medical informatics
Highlights:
- The conference will take place in Hyatt Regency Washington on Capitol Hill.
- The meeting is intended to be a forum for discussions of concepts, issues, and methods by leading researchers in the fundamental problems of granular computing in an atmosphere intended to promote the exchange of ideas and viewpoints.
For Paper Submission, please click here