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Articles 31 - 60 of 157
Full-Text Articles in Physical Sciences and Mathematics
Sketchwizard: Wizard Of Oz Prototyping Of Pen-Based User Interfaces, Richard C. Davis, T. Scott Saponas, Michael Shilman, James A. Landay
Sketchwizard: Wizard Of Oz Prototyping Of Pen-Based User Interfaces, Richard C. Davis, T. Scott Saponas, Michael Shilman, James A. Landay
Research Collection School Of Computing and Information Systems
SketchWizard allows designers to create Wizard of Oz prototypes of pen-based user interfaces in the early stages of design. In the past, designers have been inhibited from participating in the design of pen-based interfaces because of the inadequacy of paper prototypes and the difficulty of developing functional prototypes. In SketchWizard, designers and end users share a drawing canvas between two computers, allowing the designer to simulate the behavior of recognition or other technologies. Special editing features are provided to help designers respond quickly to end-user input. This paper describes the SketchWizard system and presents two evaluations of our approach. The …
Flexible Access Control To Jpeg 2000 Image Code-Streams, Yongdong Wu, Di Ma, Robert H. Deng
Flexible Access Control To Jpeg 2000 Image Code-Streams, Yongdong Wu, Di Ma, Robert H. Deng
Research Collection School Of Computing and Information Systems
JPEG 2000 is an international standard for still image compression in the 21st century. Part 8 of the standard, named JPSEC, is concerned with all the security aspects, in particular to access control and authentication. This paper presents a novel access control scheme for JPEG 2000 image code-streams. The proposed scheme is secure against collusion attacks and highly efficient. The scheme is also very flexible, allowing access control to JPEG 2000 image code-streams according to any combination of resolution, quality layer and region of interest. The "encrypt once, decrypt many ways" property of our scheme is designed to work seamlessly …
Efficient Discovery Of Frequent Approximate Sequential Patterns, Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu
Efficient Discovery Of Frequent Approximate Sequential Patterns, Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu
Research Collection School Of Computing and Information Systems
We propose an efficient algorithm for mining frequent approximate sequential patterns under the Hamming distance model. Our algorithm gains its efficiency by adopting a "break-down-and-build-up" methodology. The "breakdown" is based on the observation that all occurrences of a frequent pattern can be classified into groups, which we call strands. We developed efficient algorithms to quickly mine out all strands by iterative growth. In the "build-up" stage, these strands are grouped up to form the support sets from which all approximate patterns would be identified. A salient feature of our algorithm is its ability to grow the frequent patterns by iteratively …
Preserving Privacy In Supply Chain Management: A Challenge For Next Generation Data Mining, Madhu Ahluwalia, Zhiyuan Chen, Arrya Gangopadhyay, Zhiling Guo
Preserving Privacy In Supply Chain Management: A Challenge For Next Generation Data Mining, Madhu Ahluwalia, Zhiyuan Chen, Arrya Gangopadhyay, Zhiling Guo
Research Collection School Of Computing and Information Systems
In this paper we identify a major area of research as a topic for next generation data mining. The research effort in the last decade on privacy preserving data mining has resulted in the development of numerous algorithms. However, most of the existing research has not been applied in any particular application context. Hence it is unclear whether the current algorithms are directly applicable in any particular problem context. In this paper we identify a significant application context that not only requires protection of privacy but also sophisticated data analysis. The area in question is supply chain management, arguably one …
Om-Based Video Shot Retrieval By One-To-One Matching, Yuxin Peng, Chong-Wah Ngo, Jianguo Xiao
Om-Based Video Shot Retrieval By One-To-One Matching, Yuxin Peng, Chong-Wah Ngo, Jianguo Xiao
Research Collection School Of Computing and Information Systems
This paper proposes a new approach for shot-based retrieval by optimal matching (OM), which provides an effective mechanism for the similarity measure and ranking of shots by one-to-one matching. In the proposed approach, a weighted bipartite graph is constructed to model the color similarity between two shots. Then OM based on Kuhn-Munkres algorithm is employed to compute the maximum weight of a constructed bipartite graph as the shot similarity value by one-to-one matching among frames. To improve the speed efficiency of OM, two improved algorithms are also proposed: bipartite graph construction based on subshots and bipartite graph construction based on …
I Tube, You Tube, Everybody Tubes: Analyzing The World’S Largest User Generated Content Video System, Meeyoung Cha, Haewoon Kwak, Pablo Rodriguez, Yong-Yeol Ahn, Sue. Moon
I Tube, You Tube, Everybody Tubes: Analyzing The World’S Largest User Generated Content Video System, Meeyoung Cha, Haewoon Kwak, Pablo Rodriguez, Yong-Yeol Ahn, Sue. Moon
Research Collection School Of Computing and Information Systems
User Generated Content (UGC) is re-shaping the way people watch video and TV, with millions of video producers and consumers. In particular, UGC sites are creating new viewing patterns and social interactions, empowering users to be more creative, and developing new business opportunities. To better understand the impact of UGC systems, we have analyzed YouTube, the world's largest UGC VoD system. Based on a large amount of data collected, we provide an in-depth study of YouTube and other similar UGC systems. In particular, we study the popularity life-cycle of videos, the intrinsic statistical properties of requests and their relationship with …
Gapprox: Mining Frequent Approximate Patterns From A Massive Network, Chen Chen, Xifeng Yan, Feida Zhu, Jiawei Han
Gapprox: Mining Frequent Approximate Patterns From A Massive Network, Chen Chen, Xifeng Yan, Feida Zhu, Jiawei Han
Research Collection School Of Computing and Information Systems
Recently, there arise a large number of graphs with massive sizes and complex structures in many new applications, such as biological networks, social networks, and the Web, demanding powerful data mining methods. Due to inherent noise or data diversity, it is crucial to address the issue of approximation, if one wants to mine patterns that are potentially interesting with tolerable variations. In this paper, we investigate the problem of mining frequent approximate patterns from a massive network and propose a method called gApprox. gApprox not only finds approximate network patterns, which is the key for many knowledge discovery applications on …
Mining Modal Scenarios From Execution Traces, David Lo, Shahar Maoz, Siau-Cheng Khoo
Mining Modal Scenarios From Execution Traces, David Lo, Shahar Maoz, Siau-Cheng Khoo
Research Collection School Of Computing and Information Systems
Specification mining is a dynamic analysis process aimed at automatically inferring suggested specifications of a program from its execution traces. We describe a method, a framework, and a tool, for mining inter-object scenario-based specifications in the form of a UML2-compliant variant of Damm and Harel's Live Sequence Charts (LSC), which extends the classical partial order semantics of sequence diagrams with temporal liveness and symbolic class level lifelines, in order to generate compact and expressive specifications. Moreover, we use previous research work and tools developed for LSC to visualize, analyze, manipulate, test, and thus evaluate the scenario-based specifications we mine. Our …
Performance Of Network-Coding In Multi-Rate Wireless Environments For Multicast Applications, Luiz F. M. Viera, Archan Misra, Mario Gerla
Performance Of Network-Coding In Multi-Rate Wireless Environments For Multicast Applications, Luiz F. M. Viera, Archan Misra, Mario Gerla
Research Collection School Of Computing and Information Systems
This paper investigates the interaction between net-work coding and link-layer transmission rate diversity in multi-hop wireless networks. By appropriately mixing data packets at intermediate nodes, network coding allows a single multicast flow to achieve higher throughput to a set of receivers. Broadcast applications can also exploit link-layer rate diversity, whereby individual nodes can transmit at faster rates at the expense of corresponding smaller coverage area. We first demonstrate how combining rate-diversity with network coding can provide a larger capacity for data dissemination of a single multicast flow, and how consideration of rate diversity is critical for maximizing system throughput. We …
Npake+: A Hierarchical Group Password-Authenticated Key Exchange Protocol Using Different Passwords, Zhiguo Wan, Robert H. Deng, Feng Bao, Bart Preneel
Npake+: A Hierarchical Group Password-Authenticated Key Exchange Protocol Using Different Passwords, Zhiguo Wan, Robert H. Deng, Feng Bao, Bart Preneel
Research Collection School Of Computing and Information Systems
Although two-party password-authenticated key exchange (PAKE) protocols have been intensively studied in recent years, group PAKE protocols have received little attention. In this paper, we propose a hierarchical group PAKE protocol nPAKE+ protocol under the setting where each party shares an independent password with a trusted server. The nPAKE+ protocol is a novel combination of the hierarchical key tree structure and the password-based Diffie-Hellman exchange, and hence it achieves substantial gain in computation efficiency. In particular, the computation cost for each client in our protocol is only O(logn). Additionally, the hierarchical feature of nPAKE+ enables every subgroup obtains their own …
Analyzing Service Usage Patterns: Methodology And Simulation, Qianhui (Althea) Liang, Jen-Yao Chung
Analyzing Service Usage Patterns: Methodology And Simulation, Qianhui (Althea) Liang, Jen-Yao Chung
Research Collection School Of Computing and Information Systems
This paper proposes that service mining technology will power the construction of new business services via both intra- and inter-enterprise service assembly within the Service Oriented Architecture (SOA) framework. We investigate the methodologies of service mining at the component level of service usage. We also demonstrate how mining of service usage patterns is intended to be used to improve different aspects of service composition. Simulation experiments conducted for mining at the component level are analyzed. The processing details within a general service mining deployment are demonstrated.
A Multitude Of Opinions: Mining Online Rating Data, Hady Wirawan Lauw, Ee Peng Lim
A Multitude Of Opinions: Mining Online Rating Data, Hady Wirawan Lauw, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Online rating system is a popular feature of Web 2.0 applications. It typically involves a set of reviewers assigning rating scores (based on various evaluation criteria) to a set of objects. We identify two objectives for research on online rating data, namely achieving effective evaluation of objects and learning behaviors of reviewers/objects. These two objectives have conventionally been pursued separately. We argue that the future research direction should focus on the integration of these two objectives, as well as the integration between rating data and other types of data.
Evaluating Bag-Of-Visual-Words Representations In Scene Classification, Jun Yang, Yu-Gang Jiang, Alexander G. Hauptmann, Chong-Wah Ngo
Evaluating Bag-Of-Visual-Words Representations In Scene Classification, Jun Yang, Yu-Gang Jiang, Alexander G. Hauptmann, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Based on keypoints extracted as salient image patches, an image can be described as a “bag of visual words” and this representation has been used in scene classification. The choice of dimension, selection, and weighting of visual words in this representation is crucial to the classification performance but has not been thoroughly studied in previous work. Given the analogy between this representation and the bag-of-words representation of text documents, we apply techniques used in text categorization, including term weighting, stop word removal, feature selection, to generate image representations that differ in the dimension, selection, and weighting of visual words. The …
Taking Stock Of The Creative Commons Experiment: Monitoring The Use Of Creative Commons Licenses And Evaluating Its Implications For The Future Of Creative Commons And For Copyright Law, Giorgos Cheliotis, Kam Wai, Warren Bartholomew Chik, Ankit Guglani, Giri Kumar Tayi
Taking Stock Of The Creative Commons Experiment: Monitoring The Use Of Creative Commons Licenses And Evaluating Its Implications For The Future Of Creative Commons And For Copyright Law, Giorgos Cheliotis, Kam Wai, Warren Bartholomew Chik, Ankit Guglani, Giri Kumar Tayi
Research Collection School Of Computing and Information Systems
We provide an analysis of the use of Creative Commons (CC) licenses, an approach to licensing creative works which has become very popular among authors who wish to promote more liberal sharing and use of their work. We provide data demonstrating the popularity of CC, examine which specific license types within the CC framework are most popular, and then identify contributing factors for the relative popularity of some of the license types.
Robust Local Search And Its Application To Generating Robust Schedules, Hoong Chuin Lau, Fei Xiao, Thomas Ou
Robust Local Search And Its Application To Generating Robust Schedules, Hoong Chuin Lau, Fei Xiao, Thomas Ou
Research Collection School Of Computing and Information Systems
In this paper, we propose an extended local search framework to solve combinatorial optimization problems with data uncertainty. Our approach represents a major departure from scenario-based or stochastic programming approaches often used to tackle uncertainty. Given a value 0 < ? 1, we are interested to know what the robust objective value is, i.e. the optimal value if we allow an chance of not meeting it, assuming that certain data values are defined on bounded random variables. We show how a standard local search or metaheuristic routine can be extended to efficiently construct a decision rule with such guarantee, albeit heuristically. We demonstrate its practical applicability on the Resource Constrained Project Scheduling Problem with minimal and maximal time lags (RCPSP/max) taking into consideration activity duration uncertainty. Experiments show that, partial order schedules can be constructed that are robust in our sense without the need for a large planned horizon (due date), which improves upon the work proposed by Policella et al. 2004.
Column Heterogeneity As A Measure Of Data Quality, Bing Tian Dai, Nick Koudas, Beng Chin Ooi, Divesh Srivastava, Suresh Venkatasubramanian
Column Heterogeneity As A Measure Of Data Quality, Bing Tian Dai, Nick Koudas, Beng Chin Ooi, Divesh Srivastava, Suresh Venkatasubramanian
Research Collection School Of Computing and Information Systems
Data quality is a serious concern in every data management application, and a variety of quality measures have been proposed, including accuracy, freshness and completeness, to capture the common sources of data quality degradation. We identify and focus attention on a novel measure, column heterogeneity, that seeks to quantify the data quality problems that can arise when merging data from different sources. We identify desiderata that a column heterogeneity measure should intuitively satisfy, and discuss a promising direction of research to quantify database column heterogeneity based on using a novel combination of cluster entropy and soft clustering. Finally, we present …
Novelty Detection For Cross-Lingual News Stories With Visual Duplicates And Speech Transcripts, Xiao Wu, Alexander G. Hauptmann, Chong-Wah Ngo
Novelty Detection For Cross-Lingual News Stories With Visual Duplicates And Speech Transcripts, Xiao Wu, Alexander G. Hauptmann, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
An overwhelming volume of news videos from different channels and languages is available today, which demands automatic management of this abundant information. To effectively search, retrieve, browse and track cross-lingual news stories, a news story similarity measure plays a critical role in assessing the novelty and redundancy among them. In this paper, we explore the novelty and redundancy detection with visual duplicates and speech transcripts for cross-lingual news stories. News stories are represented by a sequence of keyframes in the visual track and a set of words extracted from speech transcript in the audio track. A major difference to pure …
Anonymous And Authenticated Key Exchange For Roaming Networks, Guomin Yang, Duncan S. Wong, Xiaotie Deng
Anonymous And Authenticated Key Exchange For Roaming Networks, Guomin Yang, Duncan S. Wong, Xiaotie Deng
Research Collection School Of Computing and Information Systems
User privacy is a notable security issue in wireless communications. It concerns about user identities from being exposed and user movements and whereabouts from being tracked. The concern of user privacy is particularly signified in systems which support roaming when users are able to hop across networks administered by different operators. In this paper, we propose a novel construction approach of anonymous and authenticated key exchange protocols for a roaming user and a visiting server to establish a random session key in such a way that the visiting server authenticates the user's home server without knowing exactly who the user …
Context-Based Detection Of Clone-Related Bugs, Lingxiao Jiang, Zhendong Su, Edwin Chiu
Context-Based Detection Of Clone-Related Bugs, Lingxiao Jiang, Zhendong Su, Edwin Chiu
Research Collection School Of Computing and Information Systems
Studies show that programs contain much similar code, commonly known as clones. One of the main reasons for introducing clones is programmers' tendency to copy and paste code to quickly duplicate functionality. We commonly believe that clones can make programs difficult to maintain and introduce subtle bugs. Although much research has proposed techniques for detecting and removing clones to improve software maintainability, little has considered how to detect latent bugs introduced by clones. In this paper, we introduce a general notion of context-based inconsistencies among clones and develop an efficient algorithm to detect such inconsistencies for locating bugs. We have …
Cross-Language And Cross-Media Image Retrieval: An Empirical Study At Imageclef2007, Steven C. H. Hoi
Cross-Language And Cross-Media Image Retrieval: An Empirical Study At Imageclef2007, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
This paper summarizes our empirical study of cross-language and cross-media image retrieval at the CLEF image retrieval track (ImageCLEF2007). In this year, we participated in the ImageCLEF photo retrieval task, in which the goal of the retrieval task is to search natural photos by some query with both textual and visual information. In this paper, we study the empirical evaluations of our solutions for the image retrieval tasks in three aspects. First of all, we study the application of language models and smoothing strategies for text-based image retrieval, particularly addressing the short text query issue. Secondly, we study the cross-media …
Overview Of The Imageclef 2007 Object Retrieval Task, Thomas Deselaers, Steven C. H. Hoi
Overview Of The Imageclef 2007 Object Retrieval Task, Thomas Deselaers, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
We describe the object retrieval task of ImageCLEF 2007, give an overview of the methods of the participating groups, and present and discuss the results. The task was based on the widely used PASCAL object recognition data to train object recognition methods and on the IAPR TC-12 benchmark dataset from which images of objects of the ten different classes bicycles, buses, cars, motorbikes, cats, cows, dogs, horses, sheep, and persons had to be retrieved. Seven international groups participated using a wide variety of methods. The results of the evaluation show that the task was very challenging and that different methods …
Ntu: Solution For The Object Retrieval Task Of The Imageclef2007, Steven C. H. Hoi
Ntu: Solution For The Object Retrieval Task Of The Imageclef2007, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Object retrieval is an interdisciplinary research problem between object recognition and content-based image retrieval (CBIR). It is commonly expected that object retrieval can be solved more effectively with the joint maximization of CBIR and object recognition techniques. We study a typical CBIR solution with application to the object retrieval tasks [26,27]. We expect that the empirical study in this work will serve as a baseline for future research when using CBIR techniques for object recognition.
Globally Distributed Software Development Project Performance: An Empirical Analysis, Narayanasamy Ramasubbu, Rajesh Krishna Balan
Globally Distributed Software Development Project Performance: An Empirical Analysis, Narayanasamy Ramasubbu, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
Software firms are increasingly distributing their software development effort across multiple locations. In this paper we present the results of a two year field study that investigated the effects of dispersion on the productivity and quality of distributed software development. We first develop a model of distributed software development. We then use the model, along with our empirically observed data, to understand the consequences of dispersion on software project performance. Our analysis reveals that, even in high process maturity environments, a) dispersion significantly reduces development productivity and has effects on conformance quality, and b) these negative effects of dispersion can …
Who’S Creating?, M. Thulasidas
Who’S Creating?, M. Thulasidas
Research Collection School Of Computing and Information Systems
We don’t read to retain information or knowledge any more. We search, scan, locate keywords, browse and bookmark. The Internet is doing to our reading habits what the calculator did to our arithmetic abilities. Knowledge is not cheap, although our easy access to it through the Internet may indicate otherwise. When we all become users of information, our knowledge will stop at its current level because nobody will be creating it any more.
Practical Elimination Of Near-Duplicates From Web Video Search, Xiao Wu, Alexander G. Hauptmann, Chong-Wah Ngo
Practical Elimination Of Near-Duplicates From Web Video Search, Xiao Wu, Alexander G. Hauptmann, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Current web video search results rely exclusively on text keywords or user-supplied tags. A search on typical popular video often returns many duplicate and near-duplicate videos in the top results. This paper outlines ways to cluster and filter out the nearduplicate video using a hierarchical approach. Initial triage is performed using fast signatures derived from color histograms. Only when a video cannot be clearly classified as novel or nearduplicate using global signatures, we apply a more expensive local feature based near-duplicate detection which provides very accurate duplicate analysis through more costly computation. The results of 24 queries in a data …
Ontology-Enriched Semantic Space For Video Search, Xiao-Yong Wei, Chong-Wah Ngo
Ontology-Enriched Semantic Space For Video Search, Xiao-Yong Wei, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Multimedia-based ontology construction and reasoning have recently been recognized as two important issues in video search, particularly for bridging semantic gap. The lack of coincidence between low-level features and user expectation makes concept-based ontology reasoning an attractive midlevel framework for interpreting high-level semantics. In this paper, we propose a novel model, namely ontology-enriched semantic space (OSS), to provide a computable platform for modeling and reasoning concepts in a linear space. OSS enlightens the possibility of answering conceptual questions such as a high coverage of semantic space with minimal set of concepts, and the set of concepts to be developed for …
Rushes Video Summarization By Object And Event Understanding, Feng Wang, Chong-Wah Ngo
Rushes Video Summarization By Object And Event Understanding, Feng Wang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper explores a variety of visual and audio analysis techniques in selecting the most representative video clips for rushes summarization at TRECVID 2007. These techniques include object detection, camera motion estimation, keypoint matching and tracking, audio classification and speech recognition. Our system is composed of two major steps. First, based on video structuring, we filter undesirable shots and minimize the inter-shot redundancy by repetitive shot detection. Second, a representability measure is proposed to model the presence of objects and four audio-visual events: motion activity of objects, camera motion, scene changes, and speech content, in a video clip. The video …
Evolutionary Combinatorial Optimization For Recursive Supervised Learning With Clustering, Kiruthika Ramanathan, Sheng Uei Guan
Evolutionary Combinatorial Optimization For Recursive Supervised Learning With Clustering, Kiruthika Ramanathan, Sheng Uei Guan
Research Collection School Of Computing and Information Systems
The idea of using a team of weak learners to learn a dataset is a successful one in literature. In this paper, we explore a recursive incremental approach to ensemble learning. In this paper, patterns are clustered according to the output space of the problem, i.e., natural clusters are formed based on patterns belonging to each class. A combinatorial optimization problem is therefore formed, which is solved using evolutionary algorithms. The evolutionary algorithms identify the "easy" and the "difficult" clusters in the system. The removal of the easy patterns then gives way to the focused learning of the more complicated …
Realizing Live Sequence Charts In System Verilog, Hai H. Wang, Shengchao Qin, Jun Sun, Jin Song Dong
Realizing Live Sequence Charts In System Verilog, Hai H. Wang, Shengchao Qin, Jun Sun, Jin Song Dong
Research Collection School Of Computing and Information Systems
The design of an embedded control system starts with an investigation of properties and behaviors of the process evolving within its environment, and an analysis of the requirement for its safety performance. In early stages, system requirements are often specied as scenarios of behavior using sequence charts for different use cases. This specication must be precise, intuitive and expressive enough to capture different aspects of embedded control systems. As a rather rich and useful extension to the classical message sequence charts, Live Sequence Charts (LSC), which provide a rich collection of constructs for specifying both possible and mandatory behaviors, are …
Innovation Stack - Choosing Innovations For Commercialization, Arcot Desai Narasimhalu
Innovation Stack - Choosing Innovations For Commercialization, Arcot Desai Narasimhalu
Research Collection School Of Computing and Information Systems
This paper describes a method for enterprises to order the innovations of interest according to a number of parameters including their own business strategy and core competencies. The method takes into account aspects such as ability to create entry barriers and complementary assets. Enterprises can now use this method to both filter out innovations that may not be of interest to them and then order the short listed or selected innovations according to their attractiveness.