Data Mining for Business Intelligence

Ben Gurion University of the Negev

BGU Main Campus, Abraham Ben David Ohayon Behavioral Sciences Complex, Auditorium 01
May 10th, 2018

The Conference

May 10th, 2018
09:00 am
Sixth Annual Conference

Knowledge Discovery in Databases (KDD) was defined in 1996 by Fayyad, Piatetsky-Shapiro, and Smyth as “the nontrivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns in data".

 Since then, hundreds of data mining algorithms have been developed to assist data scientists in finding hidden knowledge in data. Business Intelligence (BI) is an increasingly popular term representing the tools and systems that play a key role in the strategic planning process of the corporation by turning knowledge into profit. Though some data mining algorithms are already being applied for BI, their knowledge discovery potential is still far from being fully utilized. 

The sixth DM for BI conference, organized by the Department of Software and Information Systems Engineering at Ben-Gurion University of the Negev, aims at bringing together researchers and practitioners in data mining, data science, machine learning, predictive analytics and related fields to discuss emerging trends and key issues in utilization of data mining methods for business intelligence.  

 The conference speakers include the most respected and knowledgeable data mining and business intelligence experts from Academia and Industry that will discuss the state-of-the-art and state-of-the-practice in data mining for BI, lessons learned, innovative ideas, and prospects for the future.

This year, the DMBI annual conference will be preceded by a Data Hackathon.

 
The conference is co-chaired by Prof. Bracha Shapira, Prof. Mark Last and Prof. Lior Rokach

Prof. Bracha Shapira
Prof. Mark Last
Prof. Lior Rokach
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Confirmed Speakers

Dr. Omri Allouche
Gong.io
Eran Avidan
Intel
Dr. Linas Baltrunas
Netflix
Lee Blum
Verint
Dr. Gil Chamiel‏
Taboola
Dr. Yaara Goldschmidt
IBM
Dr. Yossi Kuttner
Amdocs
Dr. Michaël Mariën
KBC
Yam Peleg
Deep Trading ltd
Ishai Rosenberg
DeepInstinct
Omer Sagi
DELLEMC
Dr. Asaf Shabtai
Ben-Gurion University of the Negev
Dr. Dafna Shahaf
Hebrew University of Jerusalem
Dr. Oren Tsur
Ben-Gurion University of the Negev
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Confirmed Talks

Keynote Talk: Context Aware Recommendations at Netflix, Dr. Linas Baltrunas (Abstract) (Bio) (Presentation)

How Data Mining is Turning the Art of Sales into a Learnable Science, Dr. Omri Allouche‏ 

(Abstract) (Bio) (Presentation)

Real-Time Deep Learning on Video Streams, Mr. Eran Avidan (Abstract) (Bio

A Data Scientist’s Swiss Army Knife: A Cyber Defense System to Detect Low Footprint Campaigns in Multi-petabyte Network Data, Mr. Lee Blum (Abstract) (Bio) (Presentation)

Don't Believe Everything Your Network Tells You: Uncertainty in Deep Learning for Recommendation Systems, Dr. Gil Chamiel‏ (Abstract) (Bio) (Presentation)

Machine Learning and Causal Inference for Healthcare Recommendation Applications, Dr. Yaara Goldschmidt‏ (Abstract) (Bio

Ensemble Learning Method for K-Means Clustering In Big Data Environment, Dr. Yossi Kuttner (Abstract) (Bio) (Presentation)

Introducing and Using Chatbots in the Financial Industry, Dr. Michaël Mariën (Abstract) (Bio

Deep Meta Learning - Learning to Learn, Yam Peleg (Abstract) (Bio

End-to-End Deep Neural Networks and Transfer Learning for Automatic Analysis of Nation-State Malware, Mr. Ishai Rosenberg (Abstract) (Bio) (Presentation)

Improving DevOps and QA Efficiency Using Machine Learning, Mr. Omer Sagi (Abstract) (Bio) (Presentation)

Accelerating Innovation through Analogy Mining, Dr. Dafna Shahaf (Abstract) (Bio

Generic Black-Box End-to-End Attack against State of the Art API Call Based Malware Classifiers, Dr Asaf Shabtai (Abstract) (Bio) (Presentation)

ConStance: Modeling Annotation Contexts to Improve StanceClassification, Dr. Oren Tsur (Abstract) (Bio

 

Accepted Posters

Anna Khalemsky - Dynamic Segmentation Rules for Online Classifier of Big Data via Small Data Buffers

Michael Khavkin - Preserving Differential Privacy and Utility of Non-Stationary Data Streams

Amit Livne - Deep Recommendation System Utilizing Sequential Latent Context

Avigail Perl, Sapir Natan - Health DSS for Vascular Disease

Adir Solomon - Predict Demographic Information Using Word2vec on Spatial Trajectories

Evgenia Wasserman Pritsker - Cold Start Recommendation by Social Media Information and Graph-based Approach

Abraham Itzhak Weinberg - Selecting a Representative Decision Tree from Multiple Decision-Tree Models

Yuval Zak - Dynamically Generating Visualizations for Unmanned Aerial Vehicle (UAV) Operators: Use of Machine Learning to Improve Mission Performance

The Schedule

09:00 - 09:30 – Registration and Refreshments

09:30 - 09:45 – Conference Opening - Greetings

                         Prof. Bracha Shapira, Department of Software and Information Systems Engineering

Session 1 - Machine Learning Applications – Session Chair – Prof. Lior Rokach

09:45 - 10:05 – Mr. Omer Sagi – Dell EMC and BGU - Improving DevOps and QA Efficiency Using Machine Learning

 

10:05 - 10:25 – Dr. Yaara Goldschmidt– IBM Research Haifa – Machine Learning and Causal Inference for Healthcare Recommendation Applications

Keynote: 10:25-11:05 –Dr.  Linas Baltrunas – Netfilx - Context Aware Recommendations at Netflix

 

11:05-11:20 Coffee Break

Session 2 - ML for Cyber Security – Session Chair – Dr. Robert Moskovitch

11:20 - 11:40 –  Mr. Ishai Rosenberg – DeepInstinct - End-to-End Deep Neural Networks and Transfer Learning for Automatic Analysis of Nation-State Malware 

11:40 - 12:00 – Dr. Asaf Shabtai – BGU - Generic Black-Box End-to-End Attack against State of the Art API Call Based Malware Classifiers

12:00 - 12:20 – Mr. Lee Blum – Verint -   A Data Scientist’s Swiss Army Knife: A Cyber Defense System to Detect Low Footprint Campaigns in Multi-petabyte Network Data

 

Session 3 - Machine Learning for NLP – Session Chair – Prof. Mark Last

12:20 - 12:40 – Dr. Oren Tsur –BGU -  ConStance: Modeling Annotation Contexts to Improve Stance Classification

12:40 - 13:00 – Dr. Michaël Mariën  - KBC -  Introducing and Using Chatbots in the Financial Industry

Poster Teasers – 13:00 - 13:15

13:15 - 14:00 – Lunch and Poster Session

14:00 - 14:15- Hackathon Presentations – Prizes

Session 4 - Deep Learning - Session Chair –  Dr. Gilad Katz

14:15 - 14:35 – Dr. Gil Chamiel – Taboola - Don't Believe Everything Your Network Tells You: Uncertainty in Deep Learning for Recommendation Systems

14:35 - 14:55 – Mr.  Eran Avidan – Intel - Real-Time Deep Learning on Video Streams

14:55 - 15:15 – Mr. Yam Peleg - Deep Meta Learning - Learning to Learn

Session 5  - Machine Learning Algorithms – Session Chair-  Dr. Rami Puzis

15:15 - 15:35 – Dr. Dafna Shahaf – Hebrew University - Accelerating Innovation through Analogy Mining

15:35 - 15:55 – Dr. Yossi Kuttner – Amdocs - Ensemble Learning Method for K-Means Clustering In Big Data Environment

15:55 - 16:15 – Dr. Omri Allouche – Gong.io - How Data Mining is Turning the Art of Sales into a Learnable Science

16:15-16:20- Conference Closing

 

Sponsors

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Past Events

Call for Student Posters

DMBI 2018 will provide an interaction opportunity for MSc and PhD students to present and demonstrate their new and innovative work, and to obtain feedback from their peers in an informal setting.  A poster submission is an extended abstract of two pages and it should be submitted to dmbi@post.bgu.ac.il. 


Submissions will be reviewed and evaluated by the Conference Chairs (Prof. Mark Last, Prof. Lior Rokach, and Prof. Bracha Shapira) based on relevance, significance, quality, and clarity. If accepted, the abstract will be published on the conference website, and one of the authors will be required to prepare a 70 x 100 cm poster and deliver a brief (2-min.) presentation in the poster session.  
We encourage submission of posters derived from work-in-progress as well as from recently published papers and completed theses. 
 Topics of interest include, but are not limited to:

•         Big Data

•         Data Mining

•         Machine Learning

•         Predictive Analytics

•         Business Intelligence

•         Text Analytics

 

Important Dates

Poster submission deadline:    April 8, 2018

Poster notification deadline:    April 17, 2018

Conference:                               May 10, 2018

 

DMBI2018

P.O.B. 653, Beer-Sheva 8410501 Israel

dmbi@post.bgu.ac.il

Tel: 08-6479347 

Fax: 08-6479346

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