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Timeline Prediction Framework For Iterative Software Engineering Projects With Changes, Kay Berkling, Georgios Kiragiannis, Armin Zundel, Subhajit Datta
Timeline Prediction Framework For Iterative Software Engineering Projects With Changes, Kay Berkling, Georgios Kiragiannis, Armin Zundel, Subhajit Datta
Research Collection School Of Computing and Information Systems
Even today, software projects still suffer from delays and budget overspending. The causes for this problem are compounded when the project team is distributed across different locations and generally attributed to the decreasing ability to communicate well (due to cultural, linguistic, and physical distance). Many projects, especially those with off-shoring component, consist of small iterations with changes, deletions and additions, yet there is no formal model of the flow of iterations available. A number of commercially available project prediction tools for projects as a whole exist, but the model adaptation process by iteration, if it exists, is unclear. Furthermore, no …
Revenue Management In Business Services, Brenda Dietrich, Giuseppe A. Paleologo, Laura Wynter
Revenue Management In Business Services, Brenda Dietrich, Giuseppe A. Paleologo, Laura Wynter
Research Collection School Of Computing and Information Systems
A significant portion of the services industry is focused on providing services (medical, legal, financial, personal, and travel) to individuals. However, studies have shown that a less visible but rapidly growing segment of the service sector comprises firms that provide business functions to other businesses. The sector covers tasks such as payroll processing, procurement, and information systems management, as well as business consulting, technical support, call center operations, and software development. Firms may choose to purchase, rather than perform, these business functions to reduce costs, to mitigate risk, or simply to focus on their processes that provide marketplace differentiation. Transferring …
Ranked Reverse Nearest Neighbor Search, Ken C. K. Lee, Baihua Zheng, Wang-Chien Lee
Ranked Reverse Nearest Neighbor Search, Ken C. K. Lee, Baihua Zheng, Wang-Chien Lee
Research Collection School Of Computing and Information Systems
Given a set of data points P and a query point q in a multidimensional space, Reverse Nearest Neighbor (RNN) query finds data points in P whose nearest neighbors are q. Reverse k-Nearest Neighbor (RkNN) query (where k ≥ 1) generalizes RNN query to find data points whose kNNs include q. For RkNN query semantics, q is said to have influence to all those answer data points. The degree of q's influence on a data point p (∈ P) is denoted by κp where q is the κp-th NN of p. We introduce a new variant of RNN query, namely, …
Linear Relaxation Techniques For Task Management In Uncertain Settings, Pradeep Varakantham, Stephen F. Smith
Linear Relaxation Techniques For Task Management In Uncertain Settings, Pradeep Varakantham, Stephen F. Smith
Research Collection School Of Computing and Information Systems
In this paper, we consider the problem of assisting a busy user in managing her workload of pending tasks. We assume that our user is typically oversubscribed, and is invariably juggling multiple concurrent streams of tasks (or work flows) of varying importance and urgency. There is uncertainty with respect to the duration of a pending task as well as the amount of follow-on work that may be generated as a result of executing the task. The user’s goal is to be as productive as possible; i.e., to execute tasks that realize the maximum cumulative payoff. This is achieved by enabling …
Predicting Trusts Among Users Of Online Communities - An Epinions Case Study, Haifeng Liu, Ee-Peng Lim, Hady Wirawan Lauw, Minh-Tam Le, Aixin Sun, Jaideep Srivastava, Young Ae Kim
Predicting Trusts Among Users Of Online Communities - An Epinions Case Study, Haifeng Liu, Ee-Peng Lim, Hady Wirawan Lauw, Minh-Tam Le, Aixin Sun, Jaideep Srivastava, Young Ae Kim
Research Collection School Of Computing and Information Systems
Embedding deals with reducing the high-dimensional representation of data into a low-dimensional representation. Previous work mostly focuses on preserving similarities among objects. Here, not only do we explicitly recognize multiple types of objects, but we also focus on the ordinal relationships across types. Collaborative Ordinal Embedding or COE is based on generative modelling of ordinal triples. Experiments show that COE outperforms the baselines on objective metrics, revealing its capacity for information preservation for ordinal data.
Mining Temporal Rules For Software Maintenance, David Lo, Siau-Cheng Khoo, Chao Liu
Mining Temporal Rules For Software Maintenance, David Lo, Siau-Cheng Khoo, Chao Liu
Research Collection School Of Computing and Information Systems
Software evolution incurs difficulties in program comprehension and software verification, and hence it increases the cost of software maintenance. In this study, we propose a novel technique to mine from program execution traces a sound and complete set of statistically significant temporal rules of arbitrary lengths. The extracted temporal rules reveal invariants that the program observes, and will consequently guide developers to understand the program behaviors, and facilitate all downstream applications such as verification and debugging. Different from previous studies that were restricted to mining two-event rules (e.g., (lock) →(unlock)), our algorithm discovers rules of arbitrary lengths. In order to …
Spreadsheet Modeling Of Equipment Acquisition Plan, Thin Yin Leong, Michelle L. F. Cheong
Spreadsheet Modeling Of Equipment Acquisition Plan, Thin Yin Leong, Michelle L. F. Cheong
Research Collection School Of Computing and Information Systems
Excel spreadsheets have been used in many classrooms to teach modeling and analysis of real business problems. This can be done with relative ease but often the modeling approach may be inappropriate and the analysis results not easily implemented. In this article, we illustrate these difficulties with the modeling of the number of equipment required in future years, given demand (historical and projected) and the amount of equipment held. We show how the desired output can be, and needs to be related to the given input. For this purpose, we apply the TREND function to predict data into future years. …
User Guidance Of Resource-Adaptive Systems, João Pedro Sousa, Rajesh Krishna Balan, Vahe Poladian, David Garlan, Mahadev Satyanarayanan
User Guidance Of Resource-Adaptive Systems, João Pedro Sousa, Rajesh Krishna Balan, Vahe Poladian, David Garlan, Mahadev Satyanarayanan
Research Collection School Of Computing and Information Systems
This paper presents a framework for engineering resource-adaptive software systems targeted at small mobile devices. The proposed framework empowers users to control tradeoffs among a rich set of ervicespecific aspects of quality of service. After motivating the problem, the paper proposes a model for capturing user preferences with respect to quality of service, and illustrates prototype user interfaces to elicit such models. The paper then describes the extensions and integration work made to accommodate the proposed framework on top of an existing software infrastructure for ubiquitous computing. The research question addressed here is the feasibility of coordinating resource allocation and …
Searching Blogs And News: A Study On Popular Queries, Aixin Sun, Meishan Hu, Ee Peng Lim
Searching Blogs And News: A Study On Popular Queries, Aixin Sun, Meishan Hu, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Blog/news search engines are very important channels to reach information about the real-time happenings. In this paper, we study the popular queries collected over one year period and compare their search results returned by a blog search engine (i.e., Technorati) and a news search engine (i.e., Google News). We observed that the numbers of hits returned by the two search engines for the same set of queries were highly correlated, suggesting that blogs often provide commentary to current events reported in news. As many popular queries are related to some events, we further observed a high cohesiveness among the returned …
Mobile Interaction Design: Integrating Individual And Organizational Perspectives, Peter Tarasewich, Jun Gong, Fiona Fui-Hoon Nah, David Dewester
Mobile Interaction Design: Integrating Individual And Organizational Perspectives, Peter Tarasewich, Jun Gong, Fiona Fui-Hoon Nah, David Dewester
Research Collection School Of Computing and Information Systems
While mobile computing provides organizations with many information systems implementation alternatives, it is often difficult to predict the potential benefits, limitations, and problems with mobile applications. Given the inherent portability of mobile devices, many design and use issues can arise which do not exist with desktop systems. While many existing rules of thumb for design of stationary systems apply to mobile systems, many new ones emerge. Issues such as the security and privacy of information take on new dimensions, and potential conflicts can develop when a single mobile device serves both personal and business needs. This paper identifies potential issues …
Estimating Local Optimums In Em Algorithm Over Gaussian Mixture Model, Zhenjie Zhang, Bing Tian Dai, Anthony K.H. Tung
Estimating Local Optimums In Em Algorithm Over Gaussian Mixture Model, Zhenjie Zhang, Bing Tian Dai, Anthony K.H. Tung
Research Collection School Of Computing and Information Systems
EM algorithm is a very popular iteration-based method to estimate the parameters of Gaussian Mixture Model from a large observation set. However, in most cases, EM algorithm is not guaranteed to converge to the global optimum. Instead, it stops at some local optimums, which can be much worse than the global optimum.
Comments-Oriented Document Summarization: Understanding Documents With Readers' Feedback, Meishan Hu, Aixin Sun, Ee Peng Lim
Comments-Oriented Document Summarization: Understanding Documents With Readers' Feedback, Meishan Hu, Aixin Sun, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Comments left by readers on Web documents contain valuable information that can be utilized in different information retrieval tasks including document search, visualization, and summarization. In this paper, we study the problem of comments-oriented document summarization and aim to summarize a Web document (e.g., a blog post) by considering not only its content, but also the comments left by its readers. We identify three relations (namely, topic, quotation, and mention) by which comments can be linked to one another, and model the relations in three graphs. The importance of each comment is then scored by: (i) graph-based method, where the …
Searching Correlated Objects In A Long Sequence, Ken C. K. Lee, Wang-Chien Lee, Donna Peuquet, Baihua Zheng
Searching Correlated Objects In A Long Sequence, Ken C. K. Lee, Wang-Chien Lee, Donna Peuquet, Baihua Zheng
Research Collection School Of Computing and Information Systems
Sequence, widely appearing in various applications (e.g. event logs, text documents, etc) is an ordered list of objects. Exploring correlated objects in a sequence can provide useful knowledge among the objects, e.g., event causality in event log and word phrases in documents. In this paper, we introduce correlation query that finds correlated pairs of objects often appearing closely to each other in a given sequence. A correlation query is specified by two control parameters, distance bound, the requirement of object closeness, and correlation threshold, the minimum requirement of correlation strength of result pairs. Instead of processing the query by scanning …
Mining Past-Time Temporal Rules From Execution Traces, David Lo, Siau-Cheng Khoo, Chao Liu
Mining Past-Time Temporal Rules From Execution Traces, David Lo, Siau-Cheng Khoo, Chao Liu
Research Collection School Of Computing and Information Systems
Specification mining is a process of extracting specifications, often from program execution traces. These specifications can in turn be used to aid program understanding, monitoring and verification. There are a number of dynamic-analysis-based specification mining tools in the literature, however none so far extract past time temporal expressions in the form of rules stating: whenever a series of events occurs, previously another series of events has happened. Rules of this format are commonly found in practice and useful for various purposes. Most rule-based specification mining tools only mine future-time temporal expression. Many past-time temporal rules like whenever a resource is …
Bounded Model Checking Of Compositional Processes, Jun Sun, Yang Liu, Jin Song Dong, Jing Sun
Bounded Model Checking Of Compositional Processes, Jun Sun, Yang Liu, Jin Song Dong, Jing Sun
Research Collection School Of Computing and Information Systems
Verification techniques like SAT-based bounded model checking have been successfully applied to a variety of system models. Applying bounded model checking to compositional process algebras is, however, not a trivial task. One challenge is that the number of system states for process algebra models is not statically known, whereas exploring the full state space is computationally expensive. This paper presents a compositional encoding of hierarchical processes as SAT problems and then applies state-of-the-art SAT solvers for bounded model checking. The encoding avoids exploring the full state space for complex systems so as to deal with state space explosion. We developed …
Mapping The Multi-Tiered Impacts Of The Growth Of It Industries In India: A Combined Scale-And-Scope Externalities Perspective, Robert J. Kauffman, Ajay Kumar
Mapping The Multi-Tiered Impacts Of The Growth Of It Industries In India: A Combined Scale-And-Scope Externalities Perspective, Robert J. Kauffman, Ajay Kumar
Research Collection School Of Computing and Information Systems
Externalities occur among agglomerated firms. Scale externalities occur between firms in the same industry. Scope externalities occur when heterogeneous industries are collocated. Combined scale-and-scope externalities exist when the scale of one industry is beneficial to the growth of another collocated industry. In the Sein and Haridranath (2004) framework of information technology (IT) impacts on development, scale externalities correspond to second-order impacts, while combined scale and scope eternalities correspond to third-order impacts. We use an agglomeration perspective to explain the growth of IT industries in India. We study growth patterns of four specific IT industries: computer and peripheral equipment manufacturing, semiconductor …
H-Dpop: Using Hard Constraints For Search Space Pruning In Dcop, Akshat Kumar, Adrian Petcu, Boi Faltings
H-Dpop: Using Hard Constraints For Search Space Pruning In Dcop, Akshat Kumar, Adrian Petcu, Boi Faltings
Research Collection School Of Computing and Information Systems
In distributed constraint optimization problems, dynamic programming methods have been recently proposed (e.g. DPOP). In dynamic programming many valuations are grouped together in fewer messages, which produce much less networking overhead than search. Nevertheless, these messages are exponential in size. The basic DPOP always communicates all possible assignments, even when some of them may be inconsistent due to hard constraints. Many real problems contain hard constraints that significantly reduce the space of feasible assignments. This paper introduces H-DPOP, a hybrid algorithm that is based on DPOP, which uses Constraint Decision Diagrams (CDD) to rule out infeasible assignments, and thus compactly …
Active Kernel Learning, Steven C. H. Hoi, Rong Jin
Active Kernel Learning, Steven C. H. Hoi, Rong Jin
Research Collection School Of Computing and Information Systems
Identifying the appropriate kernel function/matrix for a given dataset is essential to all kernel-based learning techniques. A number of kernel learning algorithms have been proposed to learn kernel functions or matrices from side information (e.g., either labeled examples or pairwise constraints). However, most previous studies are limited to “passive” kernel learning in which side information is provided beforehand. In this paper we present a framework of Active Kernel Learning (AKL) that actively identifies the most informative pairwise constraints for kernel learning. The key challenge of active kernel learning is how to measure the informativeness of an example pair given its …
Semi-Supervised Ensemble Ranking, Steven C. H. Hoi, Rong Jin
Semi-Supervised Ensemble Ranking, Steven C. H. Hoi, Rong Jin
Research Collection School Of Computing and Information Systems
Ranking plays a central role in many Web search and information retrieval applications. Ensemble ranking, sometimes called meta-search, aims to improve the retrieval performance by combining the outputs from multiple ranking algorithms. Many ensemble ranking approaches employ supervised learning techniques to learn appropriate weights for combining multiple rankers. The main shortcoming with these approaches is that the learned weights for ranking algorithms are query independent. This is suboptimal since a ranking algorithm could perform well for certain queries but poorly for others. In this paper, we propose a novel semi-supervised ensemble ranking (SSER) algorithm that learns query-dependent weights when combining …
On Profiling Blogs With Representative Entries, Jinfeng Zhuang, Steven C. H. Hoi, Aixin Sun
On Profiling Blogs With Representative Entries, Jinfeng Zhuang, Steven C. H. Hoi, Aixin Sun
Research Collection School Of Computing and Information Systems
With an explosive growth of blogs, information seeking in blogosphere becomes more and more challenging. One example task is to find the most relevant topical blogs against a given query or an existing blog. Such a task requires concise representation of blogs for effective and efficient searching and matching. In this paper, we investigate a new problem of profiling a blog by choosing a set of m most representative entries from the blog, where m is a predefined number that is application-dependent. With the set of selected representative entries, applications on blogs avoid handling hundreds or even thousands of entries …
Timed Automata Patterns, Jin Song Dong, Ping Hao, Shengchao Qin, Jun Sun, Wang Yi
Timed Automata Patterns, Jin Song Dong, Ping Hao, Shengchao Qin, Jun Sun, Wang Yi
Research Collection School Of Computing and Information Systems
Timed Automata have proven to be useful for specification and verification of real-time systems. System design using Timed Automata relies on explicit manipulation of clock variables. A number of automated analyzers for Timed Automata have been developed. However, Timed Automata lack composable patterns for high-level system design. Specification languages like Timed Communicating Sequential Process (CSP) and Timed Communicating Object-Z (TCOZ) are well suited for presenting compositional models of complex real-time systems. In this work, we define a set of composable Timed Automata patterns based on hierarchical constructs in time-enriched process algebras. The patterns facilitate the hierarchical design of complex systems …
Probabilistically Reliable On-Demand Multicast In Wireless Mesh Networks, Xin Zhao, Chun Tung Chou, Jun Guo, Sanjay Jha, Archan Misra
Probabilistically Reliable On-Demand Multicast In Wireless Mesh Networks, Xin Zhao, Chun Tung Chou, Jun Guo, Sanjay Jha, Archan Misra
Research Collection School Of Computing and Information Systems
This paper studies probabilistically reliable multicast in wireless mesh networks (WMNs), utilizing MAC layer re-transmission and wireless broadcast advantage to improve both the multicast throughput and the delivery rate. We first present a new multicast routing metric which we call the expected multicast transmissions (EMT). EMT captures the effect of link packet delivery ratio, MAC layer retransmission and wireless broadcast advantage at the same time. The EMT of a MAC layer multicast transmission is the expected number of data transmissions (including retransmissions) required for a packet to reach all the recipients. The EMT of a multicast tree is the sum …
Work Dispersion, Process-Based Learning And Offshore Software Development Performance, Narayanasamy Ramasubbu, Sunil Mithas, M. S. Krishnan, Chris Kemerer
Work Dispersion, Process-Based Learning And Offshore Software Development Performance, Narayanasamy Ramasubbu, Sunil Mithas, M. S. Krishnan, Chris Kemerer
Research Collection School Of Computing and Information Systems
In this paper we develop a learning-mediated model of offshore software project productivity and quality to examine whether widely adopted structured software processes are effective in mitigating the negative effects of work dispersion in offshore software development. We explicate how the key process areas of the capability maturity model (CMM) can be utilized as a platform to launch learning routines in offshore software development and thereby explain why some offshore software development process improvement initiatives are more effective than others. We validate our learning-mediated model of offshore software project performance by utilizing data collected from 42 offshore software projects of …
An Office Survival Guide, M. Thulasidas
An Office Survival Guide, M. Thulasidas
Research Collection School Of Computing and Information Systems
In the unforgiving, dog-eat-dog corporate jungle, when you find yourself in a new corporate setting, you need to be sure of the welcome. More importantly, you need to prove yourself worthy of it.
Seemon: Scalable And Energy-Efficient Context Monitoring Framework For Sensor-Rich Mobile Environments, Seungwoo Kang, Jinwon Lee, Hyukjae Jang, Hyonik Lee, Youngki Lee, Souneil Park, Taiwoo Park, Junehwa Song
Seemon: Scalable And Energy-Efficient Context Monitoring Framework For Sensor-Rich Mobile Environments, Seungwoo Kang, Jinwon Lee, Hyukjae Jang, Hyonik Lee, Youngki Lee, Souneil Park, Taiwoo Park, Junehwa Song
Research Collection School Of Computing and Information Systems
Proactively providing services to mobile individuals is essential for emerging ubiquitous applications. The major challenge in providing users with proactive services lies in continuously monitoring their contexts based on numerous sensors. The context monitoring with rich sensors imposes heavy workloads on mobile devices with limited computing and battery power. We present SeeMon, a scalable and energy-efficient context monitoring framework for sensor-rich, resource-limited mobile environments. Running on a personal mobile device, SeeMon effectively performs context monitoring involving numerous sensors and applications. On top of SeeMon, multiple applications on the device can proactively understand users' contexts and react appropriately. This paper proposes …
A Multimodal And Multilevel Ranking Scheme For Large-Scale Video Retrieval, Steven C. H. Hoi, Michael R. Lyu
A Multimodal And Multilevel Ranking Scheme For Large-Scale Video Retrieval, Steven C. H. Hoi, Michael R. Lyu
Research Collection School Of Computing and Information Systems
A critical issue of large-scale multimedia retrieval is how to develop an effective framework for ranking the search results. This problem is particularly challenging for content-based video retrieval due to some issues such as short text queries, insufficient sample learning, fusion of multimodal contents, and large-scale learning with huge media data. In this paper, we propose a novel multimodal and multilevel (MMML) ranking framework to attack the challenging ranking problem of content-based video retrieval. We represent the video retrieval task by graphs and suggest a graph based semi-supervised ranking (SSR) scheme, which can learn with small samples effectively and integrate …
Advances And Challenges For Scalable Provenance In Stream Processing Systems, Archan Misra, Marion Blount, Anastasios Kementsietsidis, Daby Sow, Min Wang
Advances And Challenges For Scalable Provenance In Stream Processing Systems, Archan Misra, Marion Blount, Anastasios Kementsietsidis, Daby Sow, Min Wang
Research Collection School Of Computing and Information Systems
While data provenance is a well-studied topic in both database and workflow systems, its support within stream processing systems presents a new set of challenges. Part of the challenge is the high stream event rate and the low processing latency requirements imposed by many streaming applications. For example, emerging streaming applications in healthcare or finance call for data provenance, as illustrated in the Century stream processing infrastructure that we are building for supporting online healthcare analytics. At anytime, given an output data element (e.g., a medical alert) generated by Century, the system must be able to retrieve the input and …
Self-Organizing Neural Models Integrating Rules And Reinforcement Learning, Teck-Hou Teng, Zhong-Ming Tan, Ah-Hwee Tan
Self-Organizing Neural Models Integrating Rules And Reinforcement Learning, Teck-Hou Teng, Zhong-Ming Tan, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Traditional approaches to integrating knowledge into neural network are concerned mainly about supervised learning. This paper presents how a family of self-organizing neural models known as fusion architecture for learning, cognition and navigation (FALCON) can incorporate a priori knowledge and perform knowledge refinement and expansion through reinforcement learning. Symbolic rules are formulated based on pre-existing know-how and inserted into FALCON as a priori knowledge. The availability of knowledge enables FALCON to start performing earlier in the initial learning trials. Through a temporal-difference (TD) learning method, the inserted rules can be refined and expanded according to the evaluative feedback signals received …
Context Modeling With Evolutionary Fuzzy Cognitive Map In Interactive Storytelling, Yundong Cai, Chunyan Miao, Ah-Hwee Tan, Zhiqi Shen
Context Modeling With Evolutionary Fuzzy Cognitive Map In Interactive Storytelling, Yundong Cai, Chunyan Miao, Ah-Hwee Tan, Zhiqi Shen
Research Collection School Of Computing and Information Systems
To generate a believable and dynamic virtual world is a great challenge in interactive storytelling. In this paper, we propose a model, namely evolutionary fuzzy cognitive map (E-FCM), to model the dynamic causal relationships among different context variables. As an extension to conventional FCM, E-FCM models not only the fuzzy causal relationships among the variables, but also the probabilistic property of causal relationships, and asynchronous activity update of the concepts. With this model, the context variables evolve in a dynamic and uncertain manner with the according evolving time. As a result, the virtual world is presented more realistically and dynamically.
Traceable And Retrievable Identity-Based Encryption, Man Ho Au, Qiong Huang, Joseph K. Liu, Willy Susilo, Duncan S. Wong, Guomin Yang
Traceable And Retrievable Identity-Based Encryption, Man Ho Au, Qiong Huang, Joseph K. Liu, Willy Susilo, Duncan S. Wong, Guomin Yang
Research Collection School Of Computing and Information Systems
Very recently, the concept of Traceable Identity-based Encryption (IBE) scheme (or Accountable Authority Identity based Encryption scheme) was introduced in Crypto 2007. This concept enables some mechanisms to reduce the trust of a private key generator (PKG) in an IBE system. The aim of this paper is threefold. First, we discuss some subtleties in the first traceable IBE scheme in the Crypto 2007 paper. Second, we present an extension to this work by having the PKG’s master secret key retrieved automatically if more than one user secret key are released. This way, the user can produce a concrete proof of …