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Articles 7831 - 7860 of 10509
Full-Text Articles in Entire DC Network
An Analytical And Experimental Comparison Of Csp Extensions And Tools, Ling Shi, Yang Liu, Jun Sun, Jin Song Dong, Gustavo Carvalho
An Analytical And Experimental Comparison Of Csp Extensions And Tools, Ling Shi, Yang Liu, Jun Sun, Jin Song Dong, Gustavo Carvalho
Research Collection School Of Computing and Information Systems
Communicating Sequential Processes (CSP) has been widely applied to modeling and analyzing concurrent systems. There have been considerable efforts on enhancing CSP by taking data and other system aspects into account. For instance, CSP M combines CSP with a functional programming language whereas CSP# integrates high-level CSP-like process operators with low-level procedure code. Little work has been done to systematically compare these CSP extensions, which may have subtle and substantial differences. In this paper, we compare CSP M and CSP# not only on their syntax, but also operational semantics as well as their supporting tools such as FDR, ProB, and …
Poster Abstract: Towards Crowd-Aware Sensing Platform For Metropolitan Environments, Saumay Pushp, Chulhong Min, Youngki Lee, Chi Harold Liu, Junehwa Song
Poster Abstract: Towards Crowd-Aware Sensing Platform For Metropolitan Environments, Saumay Pushp, Chulhong Min, Youngki Lee, Chi Harold Liu, Junehwa Song
Research Collection School Of Computing and Information Systems
In this paper, we propose an in-situ Crowd-aware Sensing Platform, called "CrowdMon", which envisions the cooperation among mobile users in highly crowded urban areas such as metro and square. CrowdMon establishes a spontaneous connection from co-located users in a semantic proximity and enables them to share contextual information such as location, ambient music, and mood of places. To the best of our knowledge, CrowdMon is the first attempt to support crowd-aware services at a platform level. We show interesting use cases of CrowdMon and an initial system design to realize the crowd-based context sharing.
Mining Coherent Anomaly Collections On Web Data, Hanbo Dai, Feida Zhu, Ee-Peng Lim, Hwee Hwa Pang
Mining Coherent Anomaly Collections On Web Data, Hanbo Dai, Feida Zhu, Ee-Peng Lim, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
The recent boom of weblogs and social media has attached increasing importance to the identification of suspicious users with unusual behavior, such as spammers or fraudulent reviewers. A typical spamming strategy is to employ multiple dummy accounts to collectively promote a target, be it a URL or a product. Consequently, these suspicious accounts exhibit certain coherent anomalous behavior identifiable as a collection. In this paper, we propose the concept of Coherent Anomaly Collection (CAC) to capture this kind of collections, and put forward an efficient algorithm to simultaneously find the top-K disjoint CACs together with their anomalous behavior patterns. Compared …
Impact Of Multimedia In Sina Weibo: Popularity And Life Span, Xun Zhao, Feida Zhu, Weining Qian, Aoying Zhou
Impact Of Multimedia In Sina Weibo: Popularity And Life Span, Xun Zhao, Feida Zhu, Weining Qian, Aoying Zhou
Research Collection School Of Computing and Information Systems
Multimedia contents such as images and videos are widely used in social network sites nowadays. Sina Weibo, a Chinese microblogging service, is one of the first microblog platforms to incorporate multimedia content sharing features. This work provides statistical analysis on how multimedia contents are produced, consumed, and propagated in Sina Weibo. Based on 230 million tweets and 1.8 million user profiles in Sina Weibo, we study the impact of multimedia contents on the popularity of both users and tweets as well as tweet life span. Our preliminary study shows that multimedia tweets dominant pure text ones in SinaWeibo. Multimedia contents …
Automatic Generation Of Provably Correct Embedded Systems, Shang-Wei Lin, Yang Liu, Pao-Ann Hsiung, Jun Sun, Jin Song Dong
Automatic Generation Of Provably Correct Embedded Systems, Shang-Wei Lin, Yang Liu, Pao-Ann Hsiung, Jun Sun, Jin Song Dong
Research Collection School Of Computing and Information Systems
With the demand for new and complicated features, embedded systems are becoming more and more difficult to design and verify. Even if the design of a system is verified, how to guarantee the consistency between the design and its implementation remains a big issue. As a solution, we propose a framework that can help a system designer to model his or her embedded system using a high-level modeling language, verify the design of the system, and automatically generate executable software codes whose behavior semantics are consistent with that of the high-level model. We use two case studies to demonstrate the …
More Anti-Chain Based Refinement Checking, Ting Wang, Songzheng Song, Jun Sun, Yang Liu, Jin Song Dong, Xinyu Wang, Shanping Li
More Anti-Chain Based Refinement Checking, Ting Wang, Songzheng Song, Jun Sun, Yang Liu, Jin Song Dong, Xinyu Wang, Shanping Li
Research Collection School Of Computing and Information Systems
Refinement checking plays an important role in system verification. It establishes properties of an implementation by showing a refinement relationship between the implementation and a specification. Recently, it has been shown that anti-chain based approaches increase the efficiency of trace refinement checking significantly. In this work, we study the problem of adopting anti-chain for stable failures refinement checking, failures-divergence refinement checking and probabilistic refine checking (i.e., a probabilistic implementation against a non-probabilistic specification). We show that the first two problems can be significantly improved, because the state space of the product model may be reduced dramatically. Though applying anti-chain for …
A Generalized Cluster Centroid Based Classifier For Text Categorization, Guansong Pang, Shengyi Jiang
A Generalized Cluster Centroid Based Classifier For Text Categorization, Guansong Pang, Shengyi Jiang
Research Collection School Of Computing and Information Systems
In this paper, a Generalized Cluster Centroid based Classifier (GCCC) and its variants for text categorization are proposed by utilizing a clustering algorithm to integrate two wellknown classifiers, i.e., the K-nearest-neighbor (KNN) classifier and the Rocchio classifier. KNN, a lazy learning method, suffers from inefficiency in online categorization while achieving remarkable effectiveness. Rocchio, which has efficient categorization performance, fails to obtain an expressive categorization model due to its inherent linear separability assumption. Our proposed method mainly focuses on two points: one point is that we use a clustering algorithm to strengthen the expressiveness of the Rocchio model; another one is …
Cross-View Graph Embedding, Zhiwu Huang, S. Shan, H. Zhang, S. Lao, X. Chen
Cross-View Graph Embedding, Zhiwu Huang, S. Shan, H. Zhang, S. Lao, X. Chen
Research Collection School Of Computing and Information Systems
Recently, more and more approaches are emerging to solve the cross-view matching problem where reference samples and query samples are from different views. In this paper, inspired by Graph Embedding, we propose a unified framework for these cross-view methods called Cross-view Graph Embedding. The proposed framework can not only reformulate most traditional cross-view methods (e.g., CCA, PLS and CDFE), but also extend the typical single-view algorithms (e.g., PCA, LDA and LPP) to cross-view editions. Furthermore, our general framework also facilitates the development of new cross-view methods. In this paper, we present a new algorithm named Cross-view Local Discriminant Analysis (CLODA) …
An Empirical Study Of Bugs In Machine Learning Systems, Ferdian Thung, Shaowei Wang, David Lo, Lingxiao Jiang
An Empirical Study Of Bugs In Machine Learning Systems, Ferdian Thung, Shaowei Wang, David Lo, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
Many machine learning systems that include various data mining, information retrieval, and natural language processing code and libraries have being used in real world applications. Search engines, internet advertising systems, product recommendation systems are sample users of these algorithm intensive code and libraries. Machine learning code and toolkits have also been used in many recent studies on software mining and analytics that aim to automate various software engineering tasks. With the increasing number of important applications of machine learning systems, the reliability of such systems is also becoming increasingly important. A necessary step for ensuring reliability of such systems is …
An Improved Authentication Scheme For H.264/Svc And Its Performance Evaluation Over Non-Stationary Wireless Mobile Networks, Yifan Zhao, Swee-Won Lo, Robert H. Deng, Xuhua Ding
An Improved Authentication Scheme For H.264/Svc And Its Performance Evaluation Over Non-Stationary Wireless Mobile Networks, Yifan Zhao, Swee-Won Lo, Robert H. Deng, Xuhua Ding
Research Collection School Of Computing and Information Systems
In this paper, a bit stream-based authentication scheme for H.264/Scalable Video Coding (SVC) is proposed. The proposed scheme seamlessly integrates cryptographic algorithms and erasure correction codes (ECCs) to SVC video streams such that the authenticated streams are format compliant with the SVC specifications and preserve the three dimensional scalability (i. e., spatial, quality and temporal) of the original streams. We implement our scheme on a smart phone and study its performance over a realistic bursty packet-lossy wireless mobile network. Our analysis and experimental results show that the scheme achieves very high verification rates with lower communication overhead and much smaller …
Science And Technology Parks As An Open Innovation Catalyst For Valorization, Arcot Desai Narasimhalu
Science And Technology Parks As An Open Innovation Catalyst For Valorization, Arcot Desai Narasimhalu
Research Collection School Of Computing and Information Systems
This paper sets out by reviewing the key elements of a Science or Technology Park in the context of open innovation. This is followed by a broad scan of Science and Technology Park activity in South and South East Asia. The paper proceeds to discuss Singapore’s continuous efforts to create new Science and Technology park models and presents a new approach the Singapore Management University has pursued for catalyzing valorization. Insights into and recommendations on key issues related to intellectual property, licensing and venture capital that would be of interest to any Science Park are presented later.
Fast And Accurate Psd Matrix Estimation By Row Reduction, Hiroshi Kuwajima, Takashi Washio, Ee Peng Lim
Fast And Accurate Psd Matrix Estimation By Row Reduction, Hiroshi Kuwajima, Takashi Washio, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Fast and accurate estimation of missing relations, e.g., similarity, distance and kernel, among objects is now one of the most important techniques required by major data mining tasks, because the missing information of the relations is needed in many applications such as economics, psychology, and social network communities. Though some approaches have been proposed in the last several years, the practical balance between their required computation amount and obtained accuracy are insufficient for some class of the relation estimation. The objective of this paper is to formalize a problem to quickly and efficiently estimate missing relations among objects from the …
Tournament-Based Teaching, Shannon Christopher Boesch, Sandra Boesch
Tournament-Based Teaching, Shannon Christopher Boesch, Sandra Boesch
Research Collection School Of Computing and Information Systems
Over the past two years we have collaborated to develop a process and set of online games to enable additional feedback to both students and instructors in a classroom setting. We have named the resulting process Tournament-based Teaching due to the extensive use of tournament-based feedback for groups and individuals throughout course delivery. Tournament-based Teaching enables individualized and peer-based learning in a classroom setting and provides additional motivation for students to prepare for classroom sessions. It also provides feedback to instructors, which can be leveraged to provide better schedule classroom sessions.
Information And Competitive Strategy In A Networked Economy, Robert J. Kauffman, Thomas A. Weber, D. J. Wu
Information And Competitive Strategy In A Networked Economy, Robert J. Kauffman, Thomas A. Weber, D. J. Wu
Research Collection School Of Computing and Information Systems
>One of the transformative changes over the past decade has been the way networks have enabled the distributed generation of value and how businesses and organizations have managed to capture a portion of this value. This has resulted in a plethora of innovative business ideas and new strategies. The present special section deals with the incentives for distributed content generation; counterintuitive network effects in the security software market, which features an intrinsic negative externality; and the possibility for collaboration between different platforms in a two-sided market. The included papers offer an interesting mix of theoretical and practical insights. All of …
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 …
Raising The Bar, Jiwei Wang
Raising The Bar, Jiwei Wang
Research Collection School Of Accountancy
No abstract provided.
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 …