It would be highly appreciated to participate with your research papers in our special track at IFKAD2016.
IFKAD 2016 - International Forum on Knowledge Asset Dynamics
11th edition on the theme of:
Towards a New Architecture of Knowledge:
Big Data, Culture and Creativity
Dresden, Germany 15-17 June 2016
Submitted papers will be subjected to a double-blind peer review and all accepted and registered papers will be included in the Forum proceedings with ISBN and ISSN number.
The proceedings will be submitted for inclusion in the Thomson Reuters Conference Proceedings Citation Index database (previous proceedings already included) and Scopus database.
Following the Conference, authors of the selected high quality papers will be invited to submit their papers for inclusion in Special Issues and regular issues of high-impact international academic journals.
INNOVATIVE BUSINESS ANALYTICS IN THE ERA OF BIG DATA: BEHAVIORAL TREND DISCOVERY USING COMPUTER INTELLIGENCE
The era of big data and dynamic business environment calls for innovative approaches to analyze huge amounts of scattered data. Analyzing such amounts of data facilitates behavioral trend discovery. The knowledge is an emergent asset for building and sustaining modern and prospected business ecosystem. Such knowledge encompasses various aspects of culture, organization, social, behaviors, and other success factors. Therefore, integrating dispersed and underlying nuggets is way beyond legacy mining techniques. Aligning and utilizing the advancements in computer intelligence to the advancements in business refers to Business Analytics (BA). BA has been used in different fields and by many researchers to support business creativity. For example: (1) behavioral analysis of mobile network subscribers to enhance customer relationship management, (2) market segmentation for appropriate service delivery, and (3) superior customer satisfaction for higher return on investment. Furthermore, the excessive activities conducted over social networks create a substantial resource of big data. Data mining techniques over such data promote behavioral trend discovery.
This track solicits novel work boosting knowledge discovery from different angles with respect to the aforementioned aspects of behavioral trend prediction. Moreover, empirical interdisciplinary research with added value accomplished by behavioural-based analysis is applicable to the theme.
Topics of interest include, but not limited to:
- Behavioral trend discovery using computer intelligence
- Leveraging Social network analysis for better behavioral trend discovery
- Sentiment analysis in the era of big data
- Challenges for behavioral data analysis
- Innovative big data analysis techniques for behavioral modeling
- Cross-Cloud behavioral data mining and modeling
- Mobile-based behavioral trend discovery
- Business intelligence supporting blue ocean strategies
- Innovative design of frameworks/approaches based on behavioral trends
- Real-world applications for behavioral trend discovery
Behavioral Modeling; Big Data; Business Analytics; Computer Intelligence; Knowledge Discovery
Nazeeh Ghatasheh | The University of Jordan, Jordan
Ismail AL-Taharwa | The University of Jordan, Jordan
For further details: http://www.knowledgeasset.org/Tracks/?track=25