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Full-Text Articles in Entire DC Network
Video Hyperlinking: Libraries And Tools For Threading And Visualizing Large Video Collection, Lei Pang, Wei Zhang, Hung-Khoon Tan, Chong-Wah Ngo
Video Hyperlinking: Libraries And Tools For Threading And Visualizing Large Video Collection, Lei Pang, Wei Zhang, Hung-Khoon Tan, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
While HTML documents could be effortlessly hyperlinked by markup tags, creation of the hyperlinks for multimedia objects is by no means easy due to the involvement of various visual processing units and intensive computational overhead. This paper introduces an open source, named VIREO-VH, which provides end-to-end support for creating hyperlinks to thread and visualize collections of videos. The software components include video pre-processing, bag-ofwords based inverted file indexing for scalable near-duplicate keyframe search, localization of partial near-duplicate segments, and galaxy visualization of video collection. The open source has been internally used by VIREO research team since 2007, and was evolved …
Fashionask: Pushing Community Answers To Your Fingertips, Wei Zhang, Lei Pang, Chong-Wah Ngo
Fashionask: Pushing Community Answers To Your Fingertips, Wei Zhang, Lei Pang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
We demonstrate a multimedia-based question-answering system, named FashionAsk, by allowing users to ask questions referring to pictures snapped by mobile devices. Specifically, instead of asking verbose questions to depict visual instances, direct pictures are provided as part of questions. To answer these multi-modal questions, FashionAsk performs a large-scale instance search to infer the names of instances, and then matches with similar questions from communitycontributed QA websites as answers. The demonstration is conducted on a million-scale dataset of Web images and QA pairs in the domain of fashion products. Asking a multimedia question through FashionAsk can take as short as five …
Predicting Domain Adaptivity: Redo Or Recycle?, Ting Yao, Chong-Wah Ngo, Shiai Zhu
Predicting Domain Adaptivity: Redo Or Recycle?, Ting Yao, Chong-Wah Ngo, Shiai Zhu
Research Collection School Of Computing and Information Systems
Over the years, the academic researchers have contributed various visual concept classifiers. Nevertheless, given a new dataset, most researchers still prefer to develop large number of classifiers from scratch despite expensive labeling efforts and limited computing resources. A valid question is why not multimedia community “embrace the green” and recycle off-the-shelf classifiers for new dataset. The difficulty originates from the domain gap that there are many different factors that govern the development of a classifier and eventually drive its performance to emphasize certain aspects of dataset. Reapplying a classifier to an unseen dataset may end up GIGO (garbage in, garbage …
Community As A Connector: Associating Faces With Celebrity Names In Web Videos, Zhineng Chen, Chong-Wah Ngo, Juan Cao, Wei Zhang
Community As A Connector: Associating Faces With Celebrity Names In Web Videos, Zhineng Chen, Chong-Wah Ngo, Juan Cao, Wei Zhang
Research Collection School Of Computing and Information Systems
Associating celebrity faces appearing in videos with their names is of increasingly importance with the popularity of both celebrity videos and related queries. However, the problem is not yet seriously studied in Web video domain. This paper proposes a Community connected Celebrity Name-Face Association approach (CCNFA), where the community is regarded as an intermediate connector to facilitate the association. Specifically, with the names and faces extracted from Web videos, C-CNFA decomposes the association task into a three-step framework: community discovering, community matching and celebrity face tagging. To achieve the goal of efficient name-face association under this umbrella, algorithms such as …
Benchmarking Still-To-Video Face Recognition Via Partial And Local Linear Discriminant Analysis On Cox-S2v Dataset, Zhiwu Huang, S. Shan, H. Zhang, S. Lao, A. Kuerban, X. Chen
Benchmarking Still-To-Video Face Recognition Via Partial And Local Linear Discriminant Analysis On Cox-S2v Dataset, Zhiwu Huang, S. Shan, H. Zhang, S. Lao, A. Kuerban, X. Chen
Research Collection School Of Computing and Information Systems
In this paper, we explore the real-world Still-to-Video (S2V) face recognition scenario, where only very few (single, in many cases) still images per person are enrolled into the gallery while it is usually possible to capture one or multiple video clips as probe. Typical application of S2V is mug-shot based watch list screening. Generally, in this scenario, the still image(s) were collected under controlled environment, thus of high quality and resolution, in frontal view, with normal lighting and neutral expression. On the contrary, the testing video frames are of low resolution and low quality, possibly with blur, and captured under …
Vireo@Trecvid 2012: Searching With Topology, Recounting Will Small Concepts, Learning With Free Examples, Wei Zhang, Chun-Chet Tan, Shi-Ai Zhu, Ting Yao, Lei Pang, Chong-Wah Ngo
Vireo@Trecvid 2012: Searching With Topology, Recounting Will Small Concepts, Learning With Free Examples, Wei Zhang, Chun-Chet Tan, Shi-Ai Zhu, Ting Yao, Lei Pang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
The vireo group participated in four tasks: instance search, multimedia event recounting, multimedia event detection, and semantic indexing. In this paper, we will present our approaches and discuss the evaluation results.
(Strong) Multidesignated Verifiers Signatures Secure Against Rogue Key Attack, Yunmei Zhang, Man Ho Au, Guomin Yang, Willy Susilo
(Strong) Multidesignated Verifiers Signatures Secure Against Rogue Key Attack, Yunmei Zhang, Man Ho Au, Guomin Yang, Willy Susilo
Research Collection School Of Computing and Information Systems
Designated verifier signatures (DVS) allow a signer to create a signature whose validity can only be verified by a specific entity chosen by the signer. In addition, the chosen entity, known as the designated verifier, cannot convince any body that the signature is created by the signer. Multi-designated verifiers signatures (MDVS) are a natural extension of DVS in which the signer can choose multiple designated verifiers. DVS and MDVS are useful primitives in electronic voting and contract signing. In this paper, we investigate various aspects of MDVS and make two contributions. Firstly, we revisit the notion of unforgeability under rogue …
Cognitive Architectures And Autonomy: Commentary And Response, Włodzisław Duch, Ah-Hwee Tan, Stan Franklin
Cognitive Architectures And Autonomy: Commentary And Response, Włodzisław Duch, Ah-Hwee Tan, Stan Franklin
Research Collection School Of Computing and Information Systems
This paper provides a very useful and promising analysis and comparison of current architectures of autonomous intelligent systems acting in real time and specific contexts, with all their constraints. The chosen issue of Cognitive Architectures and Autonomy is really a challenge for AI current projects and future research. I appreciate and endorse not only that challenge but many specific choices and claims; in particular: (i) that “autonomy” is a key concept for general intelligent systems; (ii) that “a core issue in cognitive architecture is the integration of cognitive processes ....”; (iii) the analysis of features and capabilities missing in current …
Divad: A Dynamic And Interactive Visual Analytical Dashboard For Exploring And Analyzing Transport Data, Tin Seong Kam, Ketan Barshikar, Shaun Jun Hua Tan
Divad: A Dynamic And Interactive Visual Analytical Dashboard For Exploring And Analyzing Transport Data, Tin Seong Kam, Ketan Barshikar, Shaun Jun Hua Tan
Research Collection School Of Computing and Information Systems
The advances in location-based data collection technologies such as GPS, RFID etc. and the rapid reduction of their costs provide us with a huge and continuously increasing amount of data about movement of vehicles, people and goods in an urban area. This explosive growth of geospatially-referenced data has far outpaced the planner’s ability to utilize and transform the data into insightful information thus creating an adverse impact on the return on the investment made to collect and manage this data. Addressing this pressing need, we designed and developed DIVAD, a dynamic and interactive visual analytics dashboard to allow city planners …
Multiview Semi-Supervised Learning With Consensus, Guangxia Li, Kuiyu Chang, Steven C. H. Hoi
Multiview Semi-Supervised Learning With Consensus, Guangxia Li, Kuiyu Chang, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Obtaining high-quality and up-to-date labeled data can be difficult in many real-world machine learning applications. Semi-supervised learning aims to improve the performance of a classifier trained with limited number of labeled data by utilizing the unlabeled ones. This paper demonstrates a way to improve the transductive SVM, which is an existing semi-supervised learning algorithm, by employing a multiview learning paradigm. Multiview learning is based on the fact that for some problems, there may exist multiple perspectives, so called views, of each data sample. For example, in text classification, the typical view contains a large number of raw content features such …
A Unified Learning Framework For Auto Face Annotation By Mining Web Facial Images, Dayong Wang, Steven C. H. Hoi, Ying He
A Unified Learning Framework For Auto Face Annotation By Mining Web Facial Images, Dayong Wang, Steven C. H. Hoi, Ying He
Research Collection School Of Computing and Information Systems
Auto face annotation plays an important role in many real-world multimedia information and knowledge management systems. Recently there is a surge of research interests in mining weakly-labeled facial images on the internet to tackle this long-standing research challenge in computer vision and image understanding. In this paper, we present a novel unified learning framework for face annotation by mining weakly labeled web facial images through interdisciplinary efforts of combining sparse feature representation, content-based image retrieval, transductive learning and inductive learning techniques. In particular, we first introduce a new search-based face annotation paradigm using transductive learning, and then propose an effective …
Neural Modeling Of Episodic Memory: Encoding, Retrieval, And Forgetting, Wenwen Wang, Budhitama Subagdja, Ah-Hwee Tan, Janusz A. Starzyk
Neural Modeling Of Episodic Memory: Encoding, Retrieval, And Forgetting, Wenwen Wang, Budhitama Subagdja, Ah-Hwee Tan, Janusz A. Starzyk
Research Collection School Of Computing and Information Systems
This paper presents a neural model that learns episodic traces in response to a continuous stream of sensory input and feedback received from the environment. The proposed model, based on fusion Adaptive Resonance Theory (fusion ART) network, extracts key events and encodes spatio-temporal relations between events by creating cognitive nodes dynamically. The model further incorporates a novel memory search procedure, which performs parallel search of stored episodic traces continuously. Combined with a mechanism of gradual forgetting, the model is able to achieve a high level of memory performance and robustness, while controlling memory consumption over time. We present experimental studies, …
A Probabilistic Graphical Model For Topic And Preference Discovery On Social Media, Lu Liu, Feida Zhu, Lei Zhang, Shiqiang Yang
A Probabilistic Graphical Model For Topic And Preference Discovery On Social Media, Lu Liu, Feida Zhu, Lei Zhang, Shiqiang Yang
Research Collection School Of Computing and Information Systems
Many web applications today thrive on offering services for large-scale multimedia data, e.g., Flickr for photos and YouTube for videos. However, these data, while rich in content, are usually sparse in textual descriptive information. For example, a video clip is often associated with only a few tags. Moreover, the textual descriptions are often overly specific to the video content. Such characteristics make it very challenging to discover topics at a satisfactory granularity on this kind of data. In this paper, we propose a generative probabilistic model named Preference-Topic Model (PTM) to introduce the dimension of user preferences to enhance the …
Influentials, Novelty, And Social Contagion: The Viral Power Of Average Friends, Close Communities, And Old News, Nicholas Harrigan, Palakorn Achananuparp, Ee Peng Lim
Influentials, Novelty, And Social Contagion: The Viral Power Of Average Friends, Close Communities, And Old News, Nicholas Harrigan, Palakorn Achananuparp, Ee Peng Lim
Research Collection School Of Computing and Information Systems
What is the effect of (1) popular individuals, and (2) community structures on the retransmission of socially contagious behavior? We examine a community of Twitter users over a five month period, operationalizing social contagion as ‘retweeting’, and social structure as the count of subgraphs (small patterns of ties and nodes) between users in the follower/following network. We find that popular individuals act as ‘inefficient hubs’ for social contagion: they have limited attention, are overloaded with inputs, and therefore display limited responsiveness to viral messages. We argue this contradicts the ‘law of the few’ and ‘influentials hypothesis’. We find that community …
Entity Synonyms For Structured Web Search, Tao Cheng, Hady W. Lauw, Stelios Paparizos
Entity Synonyms For Structured Web Search, Tao Cheng, Hady W. Lauw, Stelios Paparizos
Research Collection School Of Computing and Information Systems
Nowadays, there are many queries issued to search engines targeting at finding values from structured data (e.g., movie showtime of a specific location). In such scenarios, there is often a mismatch between the values of structured data (how content creators describe entities) and the web queries (how different users try to retrieve them). Therefore, recognizing the alternative ways people use to reference an entity, is crucial for structured web search. In this paper, we study the problem of automatic generation of entity synonyms over structured data toward closing the gap between users and structured data. We propose an offline, data-driven …
Information Retrieval Based Nearest Neighbor Classification For Fine-Grained Bug Severity Prediction, Yuan Tian, David Lo, Chengnian Sun
Information Retrieval Based Nearest Neighbor Classification For Fine-Grained Bug Severity Prediction, Yuan Tian, David Lo, Chengnian Sun
Research Collection School Of Computing and Information Systems
Bugs are prevalent in software systems. Some bugs are critical and need to be fixed right away, whereas others are minor and their fixes could be postponed until resources are available. In this work, we propose a new approach leveraging information retrieval, in particular BM25-based document similarity function, to automatically predict the severity of bug reports. Our approach automatically analyzes bug reports reported in the past along with their assigned severity labels, and recommends severity labels to newly reported bug reports. Duplicate bug reports are utilized to determine what bug report features, be it textual, ordinal, or categorical, are important. …
Handling Interpretation And Representation In Multilingual Research: A Meta-Study Of Pragmatic Issues Resulting From The Use Of Multiple Languages In A Qualitative Information Systems Research Work, Ilse Baumgartner
Research Collection School Of Computing and Information Systems
Although the number of multilingual qualitative research studies appears to be growing, investigations concerned with methodological issues arising from the use of several languages within a single research are still very scarce. Most of these seem to deal exclusively with issues related to the use of interpreters and translators in qualitative research (e.g., Temple & Edwards, 2002; Temple, Edwards & Alexander, 2006; Edwards, 1998; Temple & Young 2004). Methodological investigations going beyond pure translation dilemmas in qualitative research are, however, almost non-existent. The reason for this seems to be simple: the situation where the researcher possesses mother-tongue fluency in all …
Automatic Defect Categorization, Ferdian Thung, David Lo, Lingxiao Jiang
Automatic Defect Categorization, Ferdian Thung, David Lo, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
Defects are prevalent in software systems. In order to understand defects better, industry practitioners often categorize bugs into various types. One common kind of categorization is the IBM’s Orthogonal Defect Classification (ODC). ODC proposes various orthogonal classification of defects based on much information about the defects, such as the symptoms and semantics of the defects, the root cause analysis of the defects, and many more. With these category labels, developers can better perform post-mortem analysis to find out what the common characteristics of the defects that plague a particular software project are. Albeit the benefits of having these categories, for …
Credit Card Program Value Maximization With Promotion Density For Product Discounts In Shopping Malls, Rae M. Chang, Robert John Kauffman, Kwansoo Kim
Credit Card Program Value Maximization With Promotion Density For Product Discounts In Shopping Malls, Rae M. Chang, Robert John Kauffman, Kwansoo Kim
Research Collection School Of Computing and Information Systems
We model value maximization of credit card programs for shopping malls, when card customerscan obtain product discounts of different percentages in the presence of promotion density andcompetition. Our results suggest strategies for quantitatively evaluating the trade-offs in valueoutcomes when consumer sensitivity to product discounting varies.
Sensor Openflow: Enabling Software-Defined Wireless Sensor Networks, Tie Luo, Hwee-Pink Tan, Tony Q. S. Quek
Sensor Openflow: Enabling Software-Defined Wireless Sensor Networks, Tie Luo, Hwee-Pink Tan, Tony Q. S. Quek
Research Collection School Of Computing and Information Systems
While it has been a belief for over a decade that wireless sensor networks (WSN) are application-specific, we argue that it can lead to resource underutilization and counter-productivity. We also identify two other main problems with WSN: rigidity to policy changes and difficulty to manage. In this paper, we take a radical, yet backward and peer compatible, approach to tackle these problems inherent to WSN. We propose a Software-Defined WSN architecture and address key technical challenges for its core component, Sensor OpenFlow. This work represents the first effort that synergizes software-defined networking and WSN.
A Feasibility Study Of Crowdsourcing And Google Street View To Determine Sidewalk Accessibility, Kotaro Hara, Victoria Le, Jon Froehlich
A Feasibility Study Of Crowdsourcing And Google Street View To Determine Sidewalk Accessibility, Kotaro Hara, Victoria Le, Jon Froehlich
Research Collection School Of Computing and Information Systems
We explore the feasibility of using crowd workers from Amazon Mechanical Turk to identify and rank sidewalk accessibility issues from a manually curated database of 100 Google Street View images. We examine the effect of three different interactive labeling interfaces (Point, Rectangle, and Outline) on task accuracy and duration. We close the paper by discussing limitations and opportunities for future work.
A Flexible Mixed Integer Programming Framework For Nurse Scheduling, Murphy Choy, Michelle L. F. Cheong
A Flexible Mixed Integer Programming Framework For Nurse Scheduling, Murphy Choy, Michelle L. F. Cheong
Research Collection School Of Computing and Information Systems
In this paper, a nurse-scheduling model is developed using mixed integer programming model. It is deployed to a general care ward to replace and automate the current manual approach for scheduling. The developed model differs from other similar studies in that it optimizes both hospitals requirement as well as nurse preferences by allowing flexibility in the transfer of nurses from different duties. The model also incorporated additional policies which are part of the hospitals requirement but not part of the legislations. Hospitals key primary mission is to ensure continuous ward care service with appropriate number of nursing staffs and the …
Model Checking Software Architecture Design, Jiexin Zhang, Yang Liu, Jing Sun, Jin Song Dong, Jun Sun
Model Checking Software Architecture Design, Jiexin Zhang, Yang Liu, Jing Sun, Jin Song Dong, Jun Sun
Research Collection School Of Computing and Information Systems
Software Architecture plays an essential role in the high level description of a system design. Despite its importance in the software engineering practice, the lack of formal description and verification support hinders the development of quality architectural models. In this paper, we present an automated approach to the modeling and verification of software architecture designs using the Process Analysis Toolkit (PAT). We present the formal syntax of the Wright# architecture description language together with its operational semantics in Labeled Transition System (LTS). A dedicated model checking module for Wright# is implemented in the PAT verification framework based on the proposed …
Talk Versus Work: Characteristics Of Developer Collaboration On The Jazz Platform, Subhajit Datta, Renuka Sindhgatta, Bikram Sengupta
Talk Versus Work: Characteristics Of Developer Collaboration On The Jazz Platform, Subhajit Datta, Renuka Sindhgatta, Bikram Sengupta
Research Collection School Of Computing and Information Systems
IBM's Jazz initiative offers a state-of-the-art collaborative development environment (CDE) facilitating developer interactions around interdependent units of work. In this paper, we analyze development data across two versions of a major IBM product developed on the Jazz platform, covering in total 19 months of development activity, including 17,000+ work items and 61,000+ comments made by more than 190 developers in 35 locations. By examining the relation between developer talk and work, we find evidence that developers maintain a reasonably high level of connectivity with peer developers with whom they share work dependencies, but the span of a developer's communication goes …
The Shanghai-Hongkong Team At Mediaeval2012: Violent Scene Detection Using Trajectory-Based Features, Yu-Gang Jiang, Qi Dai, Chun Chet Tan, Xiangyang Xue, Chong-Wah Ngo
The Shanghai-Hongkong Team At Mediaeval2012: Violent Scene Detection Using Trajectory-Based Features, Yu-Gang Jiang, Qi Dai, Chun Chet Tan, Xiangyang Xue, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
The Violent Scene Detection task offers a very practical challenge in detecting complex and diverse violent video clips in movies. In this working note paper, we will briefly describe our system and discuss the results, which achieved top performance in mAP@201 and runner-up in mAP@100, among all 35 submissions worldwide. The central component of our system is a set of features derived from the appearance and motion of local patch trajectories [2]. We use these features and SVM classifier as the baseline approach and add in a few other components to further improve the performance. Our findings indicate that the …
Self-Regulating Action Exploration In Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan
Self-Regulating Action Exploration In Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
The basic tenet of a learning process is for an agent to learn for only as much and as long as it is necessary. With reinforcement learning, the learning process is divided between exploration and exploitation. Given the complexity of the problem domain and the randomness of the learning process, the exact duration of the reinforcement learning process can never be known with certainty. Using an inaccurate number of training iterations leads either to the non-convergence or the over-training of the learning agent. This work addresses such issues by proposing a technique to self-regulate the exploration rate and training duration …
Eating Alone, Together: New Forms Of Commensality, Catherine Grevet, Anthony Tang, Elizabeth Mynatt
Eating Alone, Together: New Forms Of Commensality, Catherine Grevet, Anthony Tang, Elizabeth Mynatt
Research Collection School Of Computing and Information Systems
Eating with others, or commensality, is an enjoyable activity that serves many important social functions; however, many individuals eat meals alone due to life circumstances, meaning that they miss out on these social benefits. We developed and deployed a simple technology probe providing social awareness around mealtimes to explore how social systems might help alleviate the loneliness of solitary dining. Our findings suggest that these systems can convey a sense of connectedness around a meal; further, our analysis revealed three themes relevant to systems of this type: that contextually-located peripheral awareness engenders connectedness; that such tools can foster a feeling …
Content Contribution For Revenue Sharing And Reputation: A Dynamic Structural Model, Qian Tang, Bin Gu, Andrew B. Whinston
Content Contribution For Revenue Sharing And Reputation: A Dynamic Structural Model, Qian Tang, Bin Gu, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
This study examines the incentives for content contribution in social media. We propose that exposure and reputation are the major incentives for contributors. Besides, as more and more social media Web sites offer advertising-revenue sharing with some of their contributors, shared revenue provides an extra incentive for contributors who have joined revenue-sharing programs. We develop a dynamic structural model to identify a contributor's underlying utility function from observed contribution behavior. We recognize the dynamic nature of the content-contribution decision-that contributors are forward-looking, anticipating how their decisions affect future rewards. Using data collected from YouTube, we show that content contribution is …
Oto: Online Trust Oracle For User-Centric Trust Establishment, Tiffany Hyun-Jin Kim, Payas Gupta, Jun Han, Emmanuel Owusu, Jason Hong, Adrian Perrig, Debin Gao
Oto: Online Trust Oracle For User-Centric Trust Establishment, Tiffany Hyun-Jin Kim, Payas Gupta, Jun Han, Emmanuel Owusu, Jason Hong, Adrian Perrig, Debin Gao
Research Collection School Of Computing and Information Systems
Malware continues to thrive on the Internet. Besides automated mechanisms for detecting malware, we provide users with trust evidence information to enable them to make informed trust decisions. To scope the problem, we study the challenge of assisting users with judging the trustworthiness of software downloaded from the Internet. Through expert elicitation, we deduce indicators for trust evidence, then analyze these indicators with respect to scalability and robustness. We design OTO, a system for communicating these trust evidence indicators to users, and we demonstrate through a user study the effectiveness of OTO, even with respect to IE’s SmartScreen Filter (SSF). …
Understanding Engagement In Educational Computer Games, Fiona Fui-Hoon Nah, Yunjie Zhou, Adeline Boey, Hanji Li
Understanding Engagement In Educational Computer Games, Fiona Fui-Hoon Nah, Yunjie Zhou, Adeline Boey, Hanji Li
Research Collection School Of Computing and Information Systems
This paper presents an empirical study to understand engagement in educational computer games. Engagement is defined as an experience that occupies an individual’s attention and captures one’s interest. The nature of engagement is viewed as comprising conditions, actions, and outcomes of engagement. The data collection method includes in-depth interviews with 12 educational computer game players who have experienced engagement in playing these games. We used the Grounded Theory (GT) approach to develop an understanding of user engagement in the computer game-based learning context.