Our Seminars in 2015

Who will Answer my Question on Stack Overflow?

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.

Towards Software Language Processing, Software Economics, and Software Ecosystem Design

Abstract: We are working on the project “Interdisciplinary global networks for accelerating theory and practice in software ecosystem,” which aims at exploring the intersection between Software Engineering and Natural Language Processing and the intersection between Software Engineering and Game Theory. We call them Software Language Processing and Software Economics, respectively. With these new approaches, we are interested in newly designing software ecosystems. I will present some of our studies and our future challenges.

Bio: Hideaki Hata is an Assistant Professor in the Department of Information Science at Nara Institute of Science and Technology (NAIST), Japan. He received his PhD in Information Science from Osaka University. His research interests includes software analytics, software language processing, and software economics. He is a member of IEEE and ACM.

Review of “Log delta analysis: Interpretable differencing of business process event logs”

Presenter(s): Ayu Saraswati – UOW
Time: 4pm onwards
Venue: 6.105 – Smart Building

Abstract: This paper addresses the problem of explaining behavioral differences between two business process event logs. The paper presents a method that, given two event logs, returns a set of statements in natural language capturing behavior that is present or frequent in one log, while absent or infrequent in the other. This log delta analysis method allows users to diagnose differences between normal and deviant executions of a process or between two versions or variants of a process. The method relies on a novel approach to losslessly encode an event log as an event structure, combined with a frequency-enhanced technique for differencing pairs of event structures. A validation of the proposed method shows that it accurately diagnoses typical change patterns and can explain differences between normal and deviant cases in a real-life log, more compactly and precisely than previously proposed methods.

Semantic annotation of agent programs

Innovations in data curation

Digital Knowledge Ecosystems: Architecture and Ecology

Professor Athula Ginige – School of Computing, Engineering & Mathematics, Western Sydney University
Date: October 15, 2015
Time: 4pm onwards
Venue: 6.105 – Smart Building

Abstract: We are now in a phase of human history characterised by having unprecedented level of connectivity to exchange information digitally. This has enabled us to rethink and modify various business as well as livelihood processes.
To better understand how this connectivity can be effectively used to enhance livelihood activities we embarked on a project to develop a mobile based information system for Sri Lankan farmers. To support livelihood activities people need information to make informed decisions. Some of this information could be derived from prior knowledge (quasi static), some can be generated from other information captured in real time (dynamic). Rapid growth of mobile usage especially Smartphones has provided a platform suitable to capture, process and disseminate such information. While developing a mobile based information system for farmers in Sri Lanka we discovered by aggregating and disaggregating information we can create an information flow model among major stakeholders in the agriculture domain mimicking energy flows in biological ecosystems to assist them in making informed decisions. To sustain the flow of information we designed the system to empower users to act based on provided information and capture the actions to derive new information. Based on the insights gained a four tier generic architecture was developed for Digital Knowledge Ecosystems consisting of information aggregation and disaggregation, information flow and storage, user empowerment processes and user interfaces. We are now starting to see emergence of digital ecology patterns similar to what can be observed in biological ecosystems.
The insights gained from the Sri Lankan farmer project is now being applied to develop large complex Digital Knowledge Ecosystems for agriculture in India and health and wellbeing management systems in some of the EU countries and Australia. Further this model has been used in a project to stimulate innovation and competiveness among Small Business and to reorganise a large engineering knowledgebase in Australia.
In this seminar I will describe the technologies and methodologies that evolved when developing the mobile based information system for farmers in Sri Lank, generalisation of the findings into a four tier Digital Knowledge Ecosystem architecture and the ecology pattern that has started to evolve.

Bio: Athula Ginige is a Professor of Information Technology at Western Sydney University. He graduated with B.Sc. first class honours from University of Moratuwa, Sri Lanka. He obtained his Ph.D. from the University of Cambridge. He is now a fellow of the Cambridge Commonwealth Society, a member of the editorial board of The International Journal of Web Engineering and Editor-in-Chief of The International Journal on Advances in ICT for Emerging Regions. He has over 170 Journal and Conference publications. He has given many Keynotes, invited talks, seminar presentations and tutorials at various local and international conferences on video coding, multimedia information systems, Web Engineering, and eBusiness. His current research interests are in Social Computing and Digital Knowledge Ecosystems. He has successfully supervised 16 PhD students.
In recent times he has adopted a Digital Knowledge Ecosystem (DKES) approach to developing effective solutions to real world problems. The DKES approach combines powerful backend data sourcing and aggregation with empowered design and user experience. The DKES approach connects technology and people is now being used for developing mobile based information systems for agriculture, healthcare and stimulating innovation in businesses etc.

Using i * Model towards Ontology Integration and Completeness Checking in Enterprise Systems Requirement Hierarchy

 Novarun Deb – Dept. of Computer Science, University of Calcutta, India.
Date: September 17, 2015
Time: 4pm onwards
Venue: 6.105 – Smart Building

Abstract:  i * is a goal oriented requirements engineering tool that can model varied requirements for solutions being developed by an enterprise. Different stakeholders within an enterprise may use partial or even completely non-intersecting vocabulary sets. This would lead to developing multiple i * models having independent ontologies. Collectively, these i * models define a requirements refinement hierarchy where different tiers of the hierarchy capture different levels of detail. In order to integrate such a distributed ontology, we require an appropriate mapping or correlate definitions between different ontologies at multiple levels. This paper tries to identify different types of bridging correlations that allow an integration of multi-ontological i* refinement hierarchies. We use these correlations to demonstrate how relative completeness can be established between adjacent tiers of the hierarchy. Varying  degrees of relative completeness have also been identified and their fulfillment criteria have been summarized as theorems. A University Admissions System has been used as a case study to illustrate heuristics for achieving greater relative completeness.

Trends in business process management: A report on the BPM-2015 Conference (Innsbruck, Austria, Sept. 2015)

Goal-aligned categorization of instance variants in knowledge-intensive processes

Relevance in Belief Revision

Prof. Pavlos Peppas, University of Patras, Greece
Date: August 20, 2015
Time: 4pm onwards
Venue: 6.105 – Smart Building

Abstract: A quarter of a century ago, a new research area, now known as Belief Revision, emerged at the cross-section of Formal Philosophy and Artificial Intelligence. In Belief Revision the problem at focus is the process by which a rational agent changes her beliefs in the light of new information. What makes the problem non-trivial is that, in principle, it is not enough to simply add the new information to one’s stock of beliefs; some of the old beliefs need to be withdrawn, on pain of inconsistency. Furthermore, there is typically more than one choice on which beliefs to give up. In making this choice the agent, arguably, need to consider the relevance of the new information to the old beliefs. In this talk we shall review the most important ideas and results in Belief Revision, and we shall examine the recent attempts that have been made to formalize the role of relevance in the area.

Bio: Pavlos Peppas received his Diploma in Computer Engineering and Infomatics from the University of Patras in 1988, and his PhD in Computer Science from the University of Sydney in 1994. He was appointed at Macquarie University as a lecturer in 1993, and was promoted to senior lecturer in 1998. In 2000 and for about two years he worked in industry (Intrasoft, Athens), and later joined AIT (Athens Information Technology) as a Senior Scientist. From 2001 to 2004, Pavlos was Adjunct Associate Professor at the School of Computer Science and Engineering at the University of New South Wales. In November 2003 he joined the Dept of Business Administration at the University of Patras as an Associate Professor and was promoted to Professor in 2013. Since July 2013, Pavlos is also a Principal Research Fellow at the University of Technology, Sydney. His research interests lie primarily in the area of Knowledge Representation and Reasoning, with a focus on Belief Revision and on Reasoning about Action.

Characterization and Prediction of Issue-related Risks in Software Projects

Morakot Choetkiertikul, University of Wollongong
Date: May 28, 2015
Time: 4pm onwards
Venue: 6.105 – Smart Building

Abstract: Identifying risks relevant to a software project and planning measures to deal with them are critical to the success of the project. Current practices in risk assessment mostly rely on high-level, generic guidance or the subjective judgements of experts. In this paper, we propose a novel approach to risk assessment using historical data associated with a software project. Specifically, our approach identifies patterns of past events that caused project delays, and uses this knowledge to identify risks in the current state of the project. A set of risk factors characterizing “risky” software tasks (in the form of issues) were extracted from five open source projects: Apache, Duraspace, JBoss, Moodle, and Spring. In addition, we performed feature selection using a sparse logistic regression model to select risk factors with good discriminative power. Based on these risk factors, we built predictive models to predict if an issue will cause a project delay. Our predictive models are able to predict both the risk impact (i.e. the extend of the delay) and the likelihood of a risk occurring. The evaluation results demonstrate the effectiveness of our predictive models, achieving on average 48%–81% precision, 23% 90% recall, 29%–71% F-measure, and 70%–92% Area Under the ROC Curve. Our predictive models also have low error rates: 0.39–0.75 for Macro-averaged Mean Cost-Error and 0.7–1.2 for Macro averaged Mean Absolute Error.

Process engineering – at the crossroads of Engineering collaboration and Collaborative engineering

Prof. Selmin Nurcan, University of Paris 1, Pantheon-Sorbonne
Date: Apr 23, 2015
Time: 4pm onwards
Venue: 6.105 – Smart Building

Abstract: The paradigm of Business Process Management (BPM) comes along with artefacts suited for the engineering and the management of cooperative/collaborative business processes and of the information systems that should support them. The purpose is to build flexible socio-technical systems that can be adapted to their environments’ changes. The traditional process modelling approaches do not fully satisfy the requirements of process engineering in constantly evolving environments. We need formalisms which allow not only to represent business processes and their links with the software components of the information (and collaboration) systems, but which also have the capacity to represent the variable and evolutionary (thus decision-oriented) nature of those business processes. In process engineering, the requirement to integrate into the models (representations) the capacity to handle the flexibility of business processes is more and more strong. This capacity can be acquired by using variability, evolution, migration techniques according to the degree of agility wished for those processes and their support systems. Besides, the various process models may belong to a shared process repository. It is thus essential to maintain the coherence of all the models during evolutions. The capacity of the process models for supporting the flexibility also requires that the modelling and execution platforms integrates the context awareness to guide the decisions regarding the collaboration and the coordination in the business processes. The standard BPM life cycle consists of a number of phases (design, deployment, operation, evaluation). The literature provides various tracks of research that aim to enhance this life cycle to make it less rigid. The steps and procedures, the flow of information and the role of the participants are often rigidly defined and allow few modifications. Also, the capability to cope with external events is restricted to those that are ‘foreseen’ in the BPM life cycle. Stakeholders may also not be able to provide necessary information, because they are not requested or allowed to do it. To cope with these issues, we argue that BPM shall also provide an effective knowledge sharing among stakeholders and that this can be achieved using social software and promoting collaborative engineering.

Bio: Selmin Nurcan is an Associate Professor at the University Paris 1 Panthéon-Sorbonne and a senior researcher at the ‘Centre de Recherche en Informatique’ (CRI). She has a Ph.D, a habilitation, and an engineering degree in Computer Science. Her research interests include enterprise computing, business process engineering/management, change modeling, information systems engineering, business/IS alignment, IS governance, CSCW, and more recently service orientation in enterprise engineering. She has actively participated in research projects in collaboration with the industry. She is author or co-author of 150 research productions. Selmin is co-organizer of the BPMDS series at CAISE since 2007, co-founder and co-organizer of the BPMS2 workshop series at BPM since 2008, co-founder and co-organizer of the SoEA4EE workshop series at EDOC since 2009, and a member of IFIP WG 8.1. She is acting as a program committee member of a number of international conferences and workshops. She chaired the CAISE Forum in 2011 and 2014, co-chaired the RCIS’2013 Program Committee and is currently co-chairing the CAISE’2015 Doctoral Consortium. She is serving on the editorial board of several international journals such us International Journal of Information System Modeling and Design, International Journal of Information Systems in the Service Sector, Requirements Engineering Journal, Journal of Innovation and Learning, e-journal on Advances in Enterprise Systems.

Group Norms in Normative Multi-Agent Systems

Prof. Brian Logan, University of Nottingham, UK
Date: Apr 2, 2015
Time: 4pm onwards
Venue: 6.105 – Smart Building

Abstract: Norms have been widely proposed as a way of coordinating and controlling the behaviour of multi-agent systems (MAS). Perhaps surprisingly, much of the work on normative MAS has focussed on norms directed at individual agents, and ignored one of the key features of multi-agent systems, namely that a group of agents may act together to achieve an objective that none of the agents can achieve on their own. As a result, there has been little discussion of how norms could (or should) be interpreted in the context of group action. In this talk I will present some preliminary ideas about how normative multi-agent systems can be generalised to incorporate the notions of group obligations and prohibitions, and what it means for agents to be individually and collectively responsible for discharging a group norm. I will briefly outline the extensions to the normHACing framework for programming norm-aware multi-agent systems necessary to support group norms at the system and agent level. This is still very much work in progress, and I will conclude with some directions for future work.

Bio: Brian Logan is an Associate Professor in the School of Computer Science at the University of Nottingham, UK, where he leads the Agents Lab. Prior to moving to Nottingham, he worked at the Universities of Edinburgh, Cambridge and Birmingham. His research interests lie in the area of agent systems, and span the specification, design and implementation of multi-agent systems, including software architectures for multi-agent systems, logics for reasoning about agent-based systems, and software tools for building multi-agent systems.

Scalability and Distributed Agent Based Model for Service Delivery Optimisation

An Equitable Approach to Solving Distributed Constraint Optimization Problems

Graham Billiau
Date: Mar 19, 2015
Time: 4pm onwards
Venue: 6.105 – Smart Building

Abstract: In this talk I will give a brief overview of the work that I have done for my PhD thesis. This is only supposed to be a one hour talk, so I won’t be able to go into much detail. Instead I’ll focus on what I’ve done, why I’ve taken this approach and why it’s important.

Alternative conceptions of complex event processing: An informal discussion

Automatic Extraction of Enterprise Architecture

Ayu Saraswati
Date: Mar 5, 2015
Time: 4pm onwards
Venue: 6.105 – Smart Building

Abstract: Enterprise architecture provides a bird’s eye view of an organization. It is a visualisation tool for organization stakeholder to manage and improve the organization. However, building an enterprise architecture is a time-consuming and often highly complex task. It involves data collection and analysis in several di erent granularity. Previous automated work is concentrated on separate granularity to generate independent artefacts. In this paper, we proposed a method to correlate these artefacts to build a complete enterprise architecture model.

Towards a Science of Security Games: Key Algorithmic Principles, Deployed Applications and Research Challenges

Prof. Milind Tambe, University of Southern California
Date: Wed, Feb. 25th, 2015
Time: 4pm onwards
Venue: 6.105 – Smart Building

Abstract: Security is a critical concern around the world, whether it is the challenge of protecting ports, airports and other critical infrastructure, interdicting the illegal flow of drugs, weapons and money, protecting endangered species, forests and fisheries, suppressing urban crime or security in cyberspace. Unfortunately, limited security resources prevent full security coverage at all times. Instead, these limited security resources must be deployed efficiently, simultaneously taking into account adversary responses to the security coverage (e.g., an adversary can exploit predictability in security allocation), adversary preferences and past available data. To help in efficient and randomized security resource allocation, we have been using the “security games” framework to build decision-aids for security agencies around the world. Security games is a novel area of research that is founded on computational and behavioral game theory, while also incorporating elements of AI planning under uncertainty and machine learning. We have deployed security-games based decision aids for security of ports and ferry traffic with the US coast guard (in the ports of New York, Boston, Los Angeles/Long Beach, Houston and others), for security of airports and air traffic with the US Federal Air Marshals and the Los Angeles World Airport (LAX) police, and tested this framework for security of metro trains with the Los Angeles Sheriff’s Department. Moreover, recent work on green security games has led to testing our decision aids for protection of fisheries with the US Coast Guard and protection of wildlife at sites in multiple countries. I will discuss our use-inspired research in security games, including algorithms for scaling up security games as well as for handling significant adversarial uncertainty and learning models of human adversary behaviors. (*) This is joint work with a number of former and current PHD students, postdocs, and other collaborators, all listed at: http://teamcore.usc.edu/security

Bio: Milind Tambe is Helen N. and Emmett H. Jones Professor in Engineering at the University of Southern California(USC). He is a fellow of AAAI and ACM, as well as recipient of the ACM/SIGART Autonomous Agents Research Award, Christopher Columbus Fellowship Foundation Homeland security award, the INFORMS Wagner prize for excellence in Operations Research practice, the Rist Prize of the Military Operations Research Society, IBM Faculty Award, Okawa foundation faculty research award, RoboCup scientific challenge award, USC Associates award for creativity in research and USC Viterbi School of Engineering use-inspired research award. Prof. Tambe has contributed several foundational papers in agents and multiagent systems; this includes areas of multiagent teamwork, distributed constraint optimization (DCOP) and security games. For this research, he has received the “influential paper award” from the International Foundation for Agents and Multiagent Systems(IFAAMAS), as well as with his research group, best paper awards at a number of premier Artificial Intelligence Conferences and workshops; these have included multiple best paper awards at the International Conference on Autonomous Agents and Multiagent Systems and International Conference on Intelligent Virtual Agents. In addition, the ”security games” framework and algorithms pioneered by Prof. Tambe and his research group are now deployed for real-world use by several agencies including the US Coast Guard, the Transportation Security Administration, LAX Police and other agencies for security scheduling at a variety of US ports, airports and transportation infrastructure. This research has led to him and his students receiving the US Coast Guard Meritorious Team Commendation from the Commandant, US Coast Guard First District’s Operational Excellence Award, Certificate of Appreciation from the US Federal Air Marshals Service and special commendation given from the city of Los Angeles. For his teaching and service, Prof. Tambe has received the USC Steven B. Sample Teaching and Mentoring award and the ACM recognition of service award. Recently, he co-founded ARMORWAY, a company focused on risk mitigation and security resource optimization, where he serves on the board of directors. Prof. Tambe received his Ph.D. from the School of Computer Science at Carnegie Mellon University.

Business Process Effect Mining: From Process Instances to Process Design

Metta Santiputri
Date: Feb 19, 2015
Time: 4pm onwards
Venue: 6.105 – Smart Building

Abstract: The ability to define the semantics of business processes has been a key challenge in business process management, where much of the problem analysis relies on the semantics of the business process. However, the current industry-standard process modeling notation, Business Process Modeling Notation (BPMN), as well as several other similar notations, do not provide any means for describing the semantics of processes in terms of their effects. The proposed approach by Hinge et al. required explicit semantic annotation of process models. However, this solution is time-consuming and prone to error. The approach we propose involves leveraging the historical data of business process model execution. We rely on the available data to derive the effects using data mining algorithm and verify the results using the effect accumulation mechanism for semantic effects.

Agents as a Model for Expressing Complex Event Processing

Daniel Avery
Date: Feb 5, 2015
Time: 4pm onwards
Venue: 6.105 – Smart Building

Abstract: Complex Event Processing allows a machine to analyse multiple streams of data , rationalising​ the occurs of several atomic actions as a more significant and abstract event in real time. These abstract events can be used to construct even more complex and abstract events. However, problems exist in the storage of atoms that could potentially trigger a complex event; how long is an atomic event retained? how do we determined if the event is still relevant and appropriate? How can such a large volume of data be efficiently maintained in a system that demands real time access. In this talk, we present preliminary ideas of utilizing BDI agents as a model for representing complex event processing, in doing so, many of the current short comings of CEP can be address and improved on.

Towards creating socially aware software systems

Dr. Tony Savarimuthu, University of Otago
Date: Feb 5, 2015
Time: 4pm onwards
Venue: 6.105 – Smart Building

Abstract: In social computing there has been some interest in building socially aware systems that assist humans and software agents (e.g. bots) in making decisions about actions they can perform in their situated environment. These include actions that are permitted (permissions), forbidden (prohibitions) and obligated (obligations). The first part of this talk focuses on the creation of a particular type of socially aware system called a norm aware system that detects social norms from available social interaction data and recommends them to its users. The second part focuses on developing a system that can extract expectations of app users that can be used to gain insights into what features users really want (i.e. new features) and what expectations have been violated (i.e. problematic features).

Bio: Dr. Bastin Tony Roy Savarimuthu is a Senior Lecturer in Information Science at the University of Otago, Dunedin, New Zealand. His PhD work focused on investigating how norms emerge in artificial agent societies and how agents can identify norms in open agent societies. His current interests are in the areas of multi-agent systems, social computing and mining software repositories. He is particularly interested in studying social concepts such as norms, trust and reputation from social interaction data (e.g. computer-mediated interactions in social networks and multi-player games).

The calculus of optimal choice