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Full-Text Articles in Entire DC Network
Selection Of Concept Detectors For Video Search By Ontology-Enriched Semantic Spaces, Xiao-Yong Wei, Chong-Wah Ngo, Yu-Gang Jiang
Selection Of Concept Detectors For Video Search By Ontology-Enriched Semantic Spaces, Xiao-Yong Wei, Chong-Wah Ngo, Yu-Gang Jiang
Research Collection School Of Computing and Information Systems
This paper describes the construction and utilization of two novel semantic spaces, namely Ontology-enriched Semantic Space (OSS) and Ontology-enriched Orthogonal Semantic Space (OS2), to facilitate the selection of concept detectors for video search. These two semantic spaces are enriched with ontology knowledge, while emphasizing consistent and uniform comparison of ontological relatedness among concepts for query-to-concept mapping. OS2, in addition to being a linear space like OSS, also guarantees orthogonality of the semantic space. Compared with other ontology reasoning measures, both spaces are capable of providing platforms that offer a global view of concept inter-relatedness, by allowing evaluation of concept similarity …
Link Layer Multicast Using Smart Antennas: No Client Left Behind, Souvik Sen, Jie Xiong, Rahul Ghosh, Romit Roy Choudhury
Link Layer Multicast Using Smart Antennas: No Client Left Behind, Souvik Sen, Jie Xiong, Rahul Ghosh, Romit Roy Choudhury
Research Collection School Of Computing and Information Systems
Wireless link layer multicast is an important service primitive for emerging applications, such as live video, streaming audio, and other content telecasts. The broadcast nature of the wireless channel is amenable to multicast because a single packet transmission may be received by all clients in the multicast group. However, in view of diverse channel conditions at different clients, the rate of such a transmission is bottlenecked by the rate of the weakest client. Multicast throughput degrades severely. Attempts to increase the data rate result in lower reliability and higher unfairness. This paper utilizes smart beamforming antennas to improve multicast performance …
Video Event Detection Using Motion Relativity And Visual Relatedness, Feng Wang, Yu-Gang Jiang, Chong-Wah Ngo
Video Event Detection Using Motion Relativity And Visual Relatedness, Feng Wang, Yu-Gang Jiang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Event detection plays an essential role in video content analysis. However, the existing features are still weak in event detection because: i) most features just capture what is involved in an event or how the event evolves separately, and thus cannot completely describe the event; ii) to capture event evolution information, only motion distribution over the whole frame is used which proves to be noisy in unconstrained videos; iii) the estimated object motion is usually distorted by camera movement. To cope with these problems, in this paper, we propose a new motion feature, namely Expanded Relative Motion Histogram of Bag-ofVisual-Words …
Specifying And Verifying Event-Based Fairness Enhanced Systems, Jun Sun, Yang Liu, Jin Song Dong, Hai H. Wang
Specifying And Verifying Event-Based Fairness Enhanced Systems, Jun Sun, Yang Liu, Jin Song Dong, Hai H. Wang
Research Collection School Of Computing and Information Systems
Liveness/Fairness plays an important role in software specification, verification and development. Existing event-based compositional models are safety-centric. In this paper, we describe a framework for systematically specifying and verifying event-based systems under fairness assumptions. We introduce different event annotations to associate fairness constraints with individual events. Fairness annotated events can be used to embed liveness/fairness assumptions in event-based models flexibly and naturally. We show that state-of-the-art verification algorithms can be extended to verify models under fairness assumptions, with little computational overhead. We further improve the algorithm by other model checking techniques like partial order reduction. A toolset named Pat has …
Near-Duplicate Keyframe Retrieval By Nonrigid Image Matching, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, Shuicheng Yan
Near-Duplicate Keyframe Retrieval By Nonrigid Image Matching, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, Shuicheng Yan
Research Collection School Of Computing and Information Systems
Near-duplicate image retrieval plays an important role in many real-world multimedia applications. Most previous approaches have some limitations. For example, conventional appearance-based methods may suffer from the illumination variations and occlusion issue, and local feature correspondence-based methods often do not consider local deformations and the spatial coherence between two point sets. In this paper, we propose a novel and effective Nonrigid Image Matching (NIM) approach to tackle the task of near-duplicate keyframe retrieval from real-world video corpora. In contrast to previous approaches, the NIM technique can recover an explicit mapping between two near-duplicate images with a few deformation parameters and …
Resource-Aware Video Multicasting Via Access Gateways In Wireless Mesh Networks, Wanqing Tu, Cormac J. Sreenan, Chun Tung Chou, Archan Misra
Resource-Aware Video Multicasting Via Access Gateways In Wireless Mesh Networks, Wanqing Tu, Cormac J. Sreenan, Chun Tung Chou, Archan Misra
Research Collection School Of Computing and Information Systems
This paper studies video multicasting in large scale areas using wireless mesh networks. The focus is on the use of Internet access gateways that allow a choice of alternative routes to avoid potentially lengthy multi-hop wireless paths with low capacity. A set of heuristic-based algorithms are described that together aim to maximize network capacity: the two-tier integrated architecture algorithm, the weighted gateway uploading algorithm, the link-controlled routing tree algorithm, and the alternative channel assignment algorithm. These algorithms use different approaches to arrange multicast group members into a clustered and two-tier integrated architecture in which network protocols can make use of …
Recursive Pattern Based Hybrid Supervised Training, Kiruthika Ramanathan, Sheng Uei Guan
Recursive Pattern Based Hybrid Supervised Training, Kiruthika Ramanathan, Sheng Uei Guan
Research Collection School Of Computing and Information Systems
We propose, theorize and implement the Recursive Pattern-based Hybrid Supervised (RPHS) learning algorithm. The algorithm makes use of the concept of pseudo global optimal solutions to evolve a set of neural networks, each of which can solve correctly a subset of patterns. The pattern-based algorithm uses the topology of training and validation data patterns to find a set of pseudo-optima, each learning a subset of patterns. It is therefore well adapted to the pattern set provided. We begin by showing that finding a set of local optimal solutions is theoretically equivalent, and more efficient, to finding a single global optimum …
Comparison Of Online Social Relations In Volume Vs Interaction: A Case Study Of Cyworld, Hyunwoo Chun, Haewoon Kwak, Young-Ho Eom, Yong-Yeol Ahn, Sue Moon, Hawoong. Jeong
Comparison Of Online Social Relations In Volume Vs Interaction: A Case Study Of Cyworld, Hyunwoo Chun, Haewoon Kwak, Young-Ho Eom, Yong-Yeol Ahn, Sue Moon, Hawoong. Jeong
Research Collection School Of Computing and Information Systems
Online social networking services are among the most popular Internet services according to Alexa.com and have become a key feature in many Internet services. Users interact through various features of online social networking services: making friend relationships, sharing their photos, and writing comments. These friend relationships are expected to become a key to many other features in web services, such as recommendation engines, security measures, online search, and personalization issues. However, we have very limited knowledge on how much interaction actually takes place over friend relationships declared online. A friend relationship only marks the beginning of online interaction.Does the interaction …
Ontology Enhanced Web Image Retrieval: Aided By Wikipedia And Spreading Activation Theory, Huan Wang, Xing Jiang, Liang-Tien Chia, Ah-Hwee Tan
Ontology Enhanced Web Image Retrieval: Aided By Wikipedia And Spreading Activation Theory, Huan Wang, Xing Jiang, Liang-Tien Chia, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Ontology, as an efective approach to bridge the semantic gap in various domains, has attracted a lot of interests from multimedia researchers. Among the numerous possibilities enabled by ontology, we are particularly interested in exploiting ontology for a better understanding of media task (particularly, images) on the World Wide Web. To achieve our goal, two open issues are inevitably involved: 1) How to avoid the tedious manual work for ontology construction? 2) What are the effective inference models when using an ontology? Recent works about ontology learned from Wikipedia has been reported in conferences targeting the areas of knowledge management …
Structuring Low-Quality Videotaped Lectures For Cross-Reference Browsing By Video Text Analysis, Feng Wang, Chong-Wah Ngo, Ting-Chuen Pong
Structuring Low-Quality Videotaped Lectures For Cross-Reference Browsing By Video Text Analysis, Feng Wang, Chong-Wah Ngo, Ting-Chuen Pong
Research Collection School Of Computing and Information Systems
This paper presents an unified approach in analyzing and Structuring the content of videotaped lectures for distance learning applications. By Structuring lecture videos, we can Support topic indexing and semantic querying of multimedia documents captured in the traditional classrooms. Our goal in this paper is to automatically construct the cross references of lecture videos and textual documents so as to facilitate the synchronized browsing and presentation of multimedia information. The major issues involved in our approach are topical event detection, video text analysis and the matching of slide shots and external documents. In topical event detection, a novel transition detector …
Accelerating Near-Duplicate Video Matching By Combining Visual Similarity And Alignment Distortion, Hung-Khoon Tan, Xiao Wu, Chong-Wah Ngo, Wan-Lei Zhao
Accelerating Near-Duplicate Video Matching By Combining Visual Similarity And Alignment Distortion, Hung-Khoon Tan, Xiao Wu, Chong-Wah Ngo, Wan-Lei Zhao
Research Collection School Of Computing and Information Systems
In this paper, we investigate a novel approach to accelerate the matching of two video clips by exploiting the temporal coherence property inherent in the keyframe sequence of a video. Motivated by the fact that keyframe correspondences between near-duplicate videos typically follow certain spatial arrangements, such property could be employed to guide the alignment of two keyframe sequences. We set the alignment problem as an integer quadratic programming problem, where the cost function takes into account both the visual similarity of the corresponding keyframes as well as the alignment distortion among the set of correspondences. The set of keyframe-pairs found …
Fusing Semantics, Observability, Reliability And Diversity Of Concept Detectors For Video Search, Xiao-Yong Wei, Chong-Wah Ngo
Fusing Semantics, Observability, Reliability And Diversity Of Concept Detectors For Video Search, Xiao-Yong Wei, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Effective utilization of semantic concept detectors for large-scale video search has recently become a topic of intensive studies. One of main challenges is the selection and fusion of appropriate detectors, which considers not only semantics but also the reliability of detectors, observability and diversity of detectors in target video domains. In this paper, we present a novel fusion technique which considers different aspects of detectors for query answering. In addition to utilizing detectors for bridging the semantic gap of user queries and multimedia data, we also address the issue of "observability gap" among detectors which could not be directly inferred …
Ontology-Based Visual Word Matching For Near-Duplicate Retrieval, Yu-Gang Jiang, Chong-Wah Ngo
Ontology-Based Visual Word Matching For Near-Duplicate Retrieval, Yu-Gang Jiang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper proposes a novel approach to exploit the ontological relationship of visual words by linguistic reasoning. A visual word ontology is constructed to facilitate the rigorous evaluation of linguistic similarity across visual words. The linguistic similarity measurement enables cross-bin matching of visual words, compromising the effectiveness and speed of conventional keypoint matching and bag-of-word approaches. A constraint EMD is proposed and experimented to efficiently match visual words. Empirical findings indicate that the proposed approach offers satisfactory performance to near-duplicate retrieval, while still enjoying the merit of speed efficiency compared with other techniques.
Modeling Video Hyperlinks With Hypergraph For Web Video Reranking, Hung-Khoon Tan, Chong-Wah Ngo, Xiao Wu
Modeling Video Hyperlinks With Hypergraph For Web Video Reranking, Hung-Khoon Tan, Chong-Wah Ngo, Xiao Wu
Research Collection School Of Computing and Information Systems
In this paper, we investigate a novel approach of exploiting visual-duplicates for web video reranking using hypergraph. Current graph-based reranking approaches consider mainly the pair-wise linking of keyframes and ignore reliability issues that are inherent in such representation. We exploit higher order relation to overcome the issues of missing links in visual-duplicate keyframes and in addition identify the latent relationships among keyframes. Based on hypergraph, we consider two groups of video threads: visual near-duplicate threads and story threads, to hyperlink web videos and describe the higher order information existing in video content. To facilitate reranking using random walk algorithm, the …
Spatio-Temporal Efficiency In A Taxi Dispatch System, Darshan Santani, Rajesh Krishna Balan, C. Jason Woodard
Spatio-Temporal Efficiency In A Taxi Dispatch System, Darshan Santani, Rajesh Krishna Balan, C. Jason Woodard
Research Collection School Of Computing and Information Systems
In this paper, we present an empirical analysis of the GPS-enabled taxi dispatch system used by the world’s second largest land transportation company. We first summarize the collective dynamics of the more than 6,000 taxicabs in this fleet. Next, we propose a simple method for evaluating the efficiency of the system over a given period of time and geographic zone. Our method yields valuable insights into system performance—in particular, revealing significant inefficiencies that should command the attention of the fleet operator. For example, despite the state of the art dispatching system employed by the company, we find imbalances in supply …
Using Trusted Computing Technology To Facilitate Security Enforcement In Wireless Sensor Networks, Yanjiang Yang, Robert H. Deng, Feng Bao, Jianying Zhou
Using Trusted Computing Technology To Facilitate Security Enforcement In Wireless Sensor Networks, Yanjiang Yang, Robert H. Deng, Feng Bao, Jianying Zhou
Research Collection School Of Computing and Information Systems
Security enforcement in wireless sensor networks is by no means an easy task, due to the inherent resource-constrained nature of sensor nodes. To facilitate security enforcement, we propose to incorporate more powerful high-end Security Enforcement Facilitators (SEFs) into wireless sensor networks. In particular, the SEFs are equipped with TCG-compliant Trusted Platform Modules (TPMs) to protect cryptographic secrets, perform authenticated booting and attest their platform state to a remote base station.As such, the SEFs act as online trusted third parties toeffectively monitor the states of sensor nodes, help in keymanagement, simplify secure routing, and facilitate accesscontrol.
Output Regularized Metric Learning With Side Information, Wei Liu, Steven C. H. Hoi, Jianzhuang Liu
Output Regularized Metric Learning With Side Information, Wei Liu, Steven C. H. Hoi, Jianzhuang Liu
Research Collection School Of Computing and Information Systems
Distance metric learning has been widely investigated in machine learning and information retrieval. In this paper, we study a particular content-based image retrieval application of learning distance metrics from historical relevance feedback log data, which leads to a novel scenario called collaborative image retrieval. The log data provide the side information expressed as relevance judgements between image pairs. Exploiting the side information as well as inherent neighborhood structures among examples, we design a convex regularizer upon which a novel distance metric learning approach, named output regularized metric learning, is presented to tackle collaborative image retrieval. Different from previous distance metric …
Tuning Into The Digital Channel: Evaluating Business Model Fit For Internet Firm Survival, Robert J. Kauffman, Bin Wang
Tuning Into The Digital Channel: Evaluating Business Model Fit For Internet Firm Survival, Robert J. Kauffman, Bin Wang
Research Collection School Of Computing and Information Systems
More than 5,000 Internet firms have failed since the beginning of 2000. One common perception is that the downturn in the economy drove many firms out of business. But then, why have some firms survived? In this research, we provide an empirical analysis by examining how the business model characteristics of an Internet firm affect its survival. We analyze a panel data set of 130 public Internet firms using two different techniques: non-parametric survival analysis, and the semiparametric Cox proportional hazards model. We characterize the survival rates throughout the lifetimes of the public Internet firms in our sample. Our results …
Cascade Rsvm In Peer-To-Peer Network, Hock Hee Ang, Vivekanand Gopalkrishnan, Steven C. H. Hoi, Wee Keong Ng
Cascade Rsvm In Peer-To-Peer Network, Hock Hee Ang, Vivekanand Gopalkrishnan, Steven C. H. Hoi, Wee Keong Ng
Research Collection School Of Computing and Information Systems
The goal of distributed learning in P2P networks is to achieve results as close as possible to those from centralized approaches. Learning models of classification in a P2P network faces several challenges like scalability, peer dynamism, asynchronism and data privacy preservation. In this paper, we study the feasibility of building SVM classifiers in a P2P network. We show how cascading SVM can be mapped to a P2P network of data propagation. Our proposed P2P SVM provides a method for constructing classifiers in P2P networks with classification accuracy comparable to centralized classifiers and better than other distributed classifiers. The proposed algorithm …
Special Issue Introduction: Hci Studies In Mis, Fiona Fui-Hoon Nah, Xiaowen Fang, Traci Hess, Weiyin Hong
Special Issue Introduction: Hci Studies In Mis, Fiona Fui-Hoon Nah, Xiaowen Fang, Traci Hess, Weiyin Hong
Research Collection School Of Computing and Information Systems
We are grateful to the editors-in-chief for this opportunity and their strong support of the second AIS SIGHCI-sponsored special issue on HCI studies in MIS. We also thank the following reviewers who have played an important role in the development of the manuscripts included in this special issue: Steven Bellman, Damon Campbell, Jinwei Cao, Jane Carey, Andrea Everard, Mark Fuller, Matt Germonprez, Maggie Guo, Susanna Ho, De Liu, Hong Sheng, Chuan Hoo Tan, Horst Treiblmaier, June Wei, and Yunjie Calvin Xu.
Do Online Reviews Affect Product Sales? The Role Of Reviewer Characteristics And Temporal Effects, Nan Hu, Ling Liu, Jennifer Zhang
Do Online Reviews Affect Product Sales? The Role Of Reviewer Characteristics And Temporal Effects, Nan Hu, Ling Liu, Jennifer Zhang
Research Collection School Of Computing and Information Systems
Online product reviews provided by consumers who previously purchased products have become a major information source for consumers and marketers regarding product quality. This study extends previous research by conducting a more compelling test of the effect of online reviews on sales. In particular, we consider both quantitative and qualitative aspects of online reviews, such as reviewer quality, reviewer exposure, product coverage, and temporal effects. Using transaction cost economics and uncertainty reduction theories, this study adopts a portfolio approach to assess the effectiveness of the online review market. We show that consumers understand the value difference between favorable news and …
Generating Robust Schedules Subject To Resource And Duration Uncertainties, Na Fu, Hoong Chuin Lau, Fei Xiao
Generating Robust Schedules Subject To Resource And Duration Uncertainties, Na Fu, Hoong Chuin Lau, Fei Xiao
Research Collection School Of Computing and Information Systems
We consider the Resource-Constrained Project Scheduling Problem with minimal and maximal time lags under resource and duration uncertainties. To manage resource uncertainties, we build upon the work of Lambrechts et al 2007 and develop a method to analyze the effect of resource breakdowns on activity durations. We then extend the robust local search framework of Lau et al 2007 with additional considerations on the impact of unexpected resource breakdowns to the project makespan, so that partial order schedules (POS) can absorb both resource and duration uncertainties. Experiments show that our proposed model is capable of addressing the uncertainty of resources, …
Tagnsearch: Searching And Navigating Geo-Referenced Collections Of Photographs, Quang Minh Nguyen, Thi Nhu Quynh Kim, Dion Hoe-Lian Goh, Yin-Leng Theng, Ee Peng Lim, Aixin Sun, Chew-Hung Chang, Kalyani Chatterjea
Tagnsearch: Searching And Navigating Geo-Referenced Collections Of Photographs, Quang Minh Nguyen, Thi Nhu Quynh Kim, Dion Hoe-Lian Goh, Yin-Leng Theng, Ee Peng Lim, Aixin Sun, Chew-Hung Chang, Kalyani Chatterjea
Research Collection School Of Computing and Information Systems
TagNSearch is a map-based tool for searching and browsing geo-tagged photographs based on their associated tags. Using Flickr as the dataset, TagNSearch returns, for a given query, photographs clustered by locations, and summarizes each cluster of photographs by cluster-specific tags. A map-based interface is also provided to help users better search, navigate and browse photographs and their clusters. A qualitative evaluation comparing TagNSearch and an existing tag search support in Flickr was also conducted. The task involved finding locations associated with a set of photographs. Participants were found to perform this task better using TagNSearch than Flickr.
A Heuristic Method For Job-Shop Scheduling With An Infinite Wait Buffer: From One-Machine To Multi-Machine Problems, Z. J. Zhao, J. Kim, M. Luo, Hoong Chuin Lau, S. S. Ge
A Heuristic Method For Job-Shop Scheduling With An Infinite Wait Buffer: From One-Machine To Multi-Machine Problems, Z. J. Zhao, J. Kim, M. Luo, Hoong Chuin Lau, S. S. Ge
Research Collection School Of Computing and Information Systems
Through empirical comparison of classical job shop problems (JSP) with multi-machine consideration, we find that the objective to minimize the sum of weighted tardiness has a better wait property compared with the objective to minimize the makespan. Further, we test the proposed Iterative Minimization Micro-model (IMM) heuristic method with the mixed integer programming (MIP) solution by CPLEX. For multi-machine problems, the IMM heuristic method is faster and achieves a better solution. Finally, for a large problem instance with 409 jobs and 30 types of machines, IMM-heuristic method is compared with ProModel and we find that the heuristic method is slightly …
Relative Importance, Specific Investment And Ownership In Interorganizational Systems., Kunsoo Han, Robert J. Kauffman, Barrie R. Nault
Relative Importance, Specific Investment And Ownership In Interorganizational Systems., Kunsoo Han, Robert J. Kauffman, Barrie R. Nault
Research Collection School Of Computing and Information Systems
Implementation and maintenance of interorganizational systems (IOS) require investments by all the participating firms. Compared with intraorganizational systems, however, there are additional uncertainties and risks. This is because the benefits of IOS investment depend not only on a firm's own decisions, but also on those of its business partners. Without appropriate levels of investment by all the firms participating in an IOS, they cannot reap the full benefits. Drawing upon the literature in institutional economics, we examine IOS ownership as a means to induce value-maximizing noncontractible investments. We model the impact of two factors derived from the theory of incomplete …
Distinguishing Between Fe And Ddos Using Randomness Check, Hyundo Park, Peng Li, Debin Gao, Heejo Lee, Robert H. Deng
Distinguishing Between Fe And Ddos Using Randomness Check, Hyundo Park, Peng Li, Debin Gao, Heejo Lee, Robert H. Deng
Research Collection School Of Computing and Information Systems
Threads posed by Distributed Denial of Service (DDoS) attacks are becoming more serious day by day. Accurately detecting DDoS becomes an important and necessary step in securing a computer network. However, Flash Event (FE), which is created by legitimate requests, shares very similar characteristics with DDoS in many aspects and makes it hard to be distinguished from DDoS attacks. In this paper, we propose a simple yet effective mechanism called FDD (FE and DDoS Distinguisher) to distinguish FE and DDoS. To the best of our knowledge, this is the first effective and practical mechanism that distinguishes FE and DDoS attacks. …
An Efficient Pir Construction Using Trusted Hardware, Yanjiang Yang, Xuhua Ding, Robert H. Deng, Feng Bao
An Efficient Pir Construction Using Trusted Hardware, Yanjiang Yang, Xuhua Ding, Robert H. Deng, Feng Bao
Research Collection School Of Computing and Information Systems
For a private information retrieval (PIR) scheme to be deployed in practice, low communication complexity and low computation complexity are two fundamental requirements it must meet. Most existing PIR schemes only focus on the communication complexity. The reduction on the computational complexity did not receive the due treatment mainly because of its O(n) lower bound. By using the trusted hardware based model, we design a novel scheme which breaks this barrier. With constant storage, the computation complexity of our scheme, including offline computation, is linear to the number of queries and is bounded by after optimization.
Software Nightmares, Manoj Thulasidas
Software Nightmares, Manoj Thulasidas
Research Collection School Of Computing and Information Systems
To err is human, but to really foul things up, you need a computer. So states the remarkably insightful Murphy’s Law. And nowhere else does this ring truer than in our financial workplace. After all, it is the financial sector that drove the rapid progress in the computing industry – which is why the first computing giant had the word “business” in its name. The financial industry keeps up with the developments in the computer industry for one simple reason. Stronger computers and smarter programs mean more money — a concept we readily grasp. As we use the latest and …
Hierarchical Inter-Object Traces For Specification Mining, David Lo, Shahar Maoz
Hierarchical Inter-Object Traces For Specification Mining, David Lo, Shahar Maoz
Research Collection School Of Computing and Information Systems
Major challenges of dynamic analysis approaches to specification mining include scalability over long traces as well as comprehensibility and expressivity of results. We present a novel use of object hierarchies over inter-object traces as an abstraction/refinement mechanism enabling scalable, incremental, top-down mining of scenario-based specifications.
Integrating Lightweight Systems Analysis Into The Unified Process By Using Service Responsibility Tables, X. Tan, S. Alter, Keng Siau
Integrating Lightweight Systems Analysis Into The Unified Process By Using Service Responsibility Tables, X. Tan, S. Alter, Keng Siau
Research Collection School Of Computing and Information Systems
This paper is a step toward establishing direct, but non-automatic links between lightweight (semi-formal) analysis methods for business professionals and heavyweight analysis methods for IT professionals. After noting the importance of user involvement in obtaining accurate and meaningful user requirements, the paper summarizes the Unified Process, a software development methodology that employs Unified Modeling Language (UML). Another section in the paper summarizes previous extensions of the work system method that produced a lightweight analysis tool called Service Responsibility Tables (SRTs). This paper uses a straightforward example to demonstrate a set of heuristics for translating between service responsibility tables produced by …