DSL NEWS UPDATE:
Prof. Aditya Ghose will present a keynote at a plenary session of Int'l Conf. on Service-Oriented Computing Workshops on Nov. 16th in Goa, India.
Prof. Aditya Ghose has been invited to deliver a keynote at a joint plenary session of the Service-Oriented Enterprise Architecture and Evolutionary Business Process Workshops at the EDOC-2015 conference (Adelaide, September, 2015). His keynote title: "The post-theoretic enterprise: Data-driven evolution of enterprise functionality".
Outcomes of a project on merging software models led by Dr Hoa Dam with researchers at Johannes Kepler University (Austria) and University of Otago (New Zealand) has recently been published in the highly-regarded Journal of Systems and Software. Earlier results of this research have won a Best Paper Award at the 11th Working IEEE/IFIP Conference on Software Architecture.
DSL fast growing research on Big Data analytics for software engineering (by PhD student Morakot Choetkiertikul, Dr Hoa Dam, and Prof. Aditya Ghose) scored another major success with a paper at the 30th IEEE/ACM International Conference on Automated Software Engineering (ASE), one of the top conferences in software engineering with an acceptance rate of 20.8%.
DSL authors Karthikeyan Ponnalagu, Prof. Aditya Ghose and Dr. Hoa Dam celebrate a major paper success at the BPM-2015 conference (the premier - and highly selective with a 17% acceptance rate - venue for business process management) with a paper that offers ways to use semantic annotation and goal-oriented analysis to manage variability in business process instances.
DSL authors Morakot Choetkiertikul, Dr. Hoa Dam and Prof. Aditya Ghose have won the ACM SIGSOFT Distinguished Paper Award for their work on mining risk indicators for software projects.
TITLE: Who will Answer my Question on Stack Overflow?
SPEAKER: Daniel Avery UOW
DATE: December 3, 2015
TIME: 4pm onwards
ABSTRACT: Stack Overflow is a highly successful Community Question Answering (CQA) service for software developers with more than three millions users and more than ten thousand posts per day. The large volume of questions makes it difficult for users to find questions that they are interested in answering. In this paper, we propose a number of approaches to predict who will answer a new question using the characteristics of the question (i.e. topic) and users (i.e. reputation), and the social network of Stack Overflow users (i.e. interested in the same topic). Specifically, our approach aims to identify a group of users (candidates) who have the potential to answer a new question by using feature-based prediction approach and social network based prediction approach. We develop predictive models to predict whether an identified candidate answers a new question. This prediction helps motivate the knowledge exchanging in the community by routing relevant questions to potential answerers.