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Articles 3181 - 3210 of 4266
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Community-Based Classification Of Noun Phrases In Twitter, Freddy Chong Tat Chua, William W. Cohen, Justin Betterridge, Ee-Peng Lim
Community-Based Classification Of Noun Phrases In Twitter, Freddy Chong Tat Chua, William W. Cohen, Justin Betterridge, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Many event monitoring systems rely on counting known keywords in streaming text data to detect sudden spikes in frequency. But the dynamic and conversational nature of Twitter makes it hard to select known keywords for monitoring. Here we consider a method of automatically finding noun phrases (NPs) as keywords for event monitoring in Twitter. Finding NPs has two aspects, identifying the boundaries for the subsequence of words which represent the NP, and classifying the NP to a specific broad category such as politics, sports, etc. To classify an NP, we define the feature vector for the NP using not just …
Lagrangian Relaxation For Large-Scale Multi-Agent Planning, Geoff Gordon, Pradeep Varakantham, William Yeoh, Hoong Chuin Lau, Shih-Fen Cheng
Lagrangian Relaxation For Large-Scale Multi-Agent Planning, Geoff Gordon, Pradeep Varakantham, William Yeoh, Hoong Chuin Lau, Shih-Fen Cheng
Research Collection School Of Computing and Information Systems
Multi-agent planning is a well-studied problem with various applications including disaster rescue, urban transportation and logistics, both for autonomous agents and for decision support to humans. Due to computational constraints, existing research typically focuses on one of two scenarios: unstructured domains with many agents where we are content with heuristic solutions, or domains with small numbers of agents or special structure where we can provide provably near-optimal solutions. By contrast, in this paper, we focus on providing provably near-optimal solutions for domains with large numbers of agents, by exploiting a common domain-general property: if individual agents each have limited influence …
Effect Of Business Intelligence And It Infrastructure Flexibility On Organizational Agility, Xiaofeng Chen, Keng Siau
Effect Of Business Intelligence And It Infrastructure Flexibility On Organizational Agility, Xiaofeng Chen, Keng Siau
Research Collection School Of Computing and Information Systems
There is a growing use of business intelligence (BI) for better management decisions in different industries. However, empirical studies on BI are still scarce in academic research. This research investigates BI from an organizational agility perspective. Organizational agility is the ability to sense and respond to market opportunities and threats with speed. Drawing on systems theory and literature on organizational agility, business intelligence, and IT infrastructure flexibility, we hypothesize that BI use and IT infrastructure flexibility are two major antecedents to organizational agility. We developed a research model to examine the effect of BI use and IT infrastructure flexibility on …
Agent-Based Virtual Humans In Co-Space: An Evaluative Study, Yilin Kang, Ah-Hwee Tan, Fiona Fui-Hoon Nah
Agent-Based Virtual Humans In Co-Space: An Evaluative Study, Yilin Kang, Ah-Hwee Tan, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
Co-Space refers to interactive virtual environment modelled after the real world in terms of look-and-feel, functionalities and services. We have developed a 3D virtual world named Nan yang Technological University (NTU) Co-Space populated with virtual human characters. Three key requirements of realistic virtual humans in the virtual world have been identified, namely (1) autonomy: agents can function on their own, (2) interactivity: agents can interact naturally with players, and (3) personality: agents can exhibit human traits and characteristics. Working towards these challenges, we propose a brain-inspired agent architecture that integrates goal-directed autonomy, natural language interaction and human-like personality. We conducted …
Do Hackers Seek Variety? An Empirical Analysis Of Website Defacements, Kok Wei Ooi, Seung-Hyun Kim, Qiu-Hong Wang, Kai Lung Hui
Do Hackers Seek Variety? An Empirical Analysis Of Website Defacements, Kok Wei Ooi, Seung-Hyun Kim, Qiu-Hong Wang, Kai Lung Hui
Research Collection School Of Computing and Information Systems
The importance of securing the cyberspace is higher than ever along with the evolution of cyber attacks launched by hackers with malicious intention. However, there has been little research to understand the hackers who are the most important agents determining the landscape of information security. This paper investigates the behaviors of hackers using a longitudinal dataset of defacement attacks. Based on theories of economics of criminal behaviors and variety seeking, we find that hackers seek variety in choosing their victims in terms of region, hacking method, and the type of operating systems; as their prior experience is focused in terms …
Extracting And Normalizing Entity-Actions From Users' Comments, Swapna Gottipati, Jing Jiang
Extracting And Normalizing Entity-Actions From Users' Comments, Swapna Gottipati, Jing Jiang
Research Collection School Of Computing and Information Systems
With the growing popularity of opinion-rich resources on the Web, new opportunities and challenges arise and aid people in actively using such information to understand the opinions of others. Opinion mining process currently focuses on extracting the sentiments of the users on products, social, political and economical issues. In many instances, users not only express their sentiments but also contribute their ideas, requests and suggestions through comments. Such comments are useful for domain experts and are referred to as actionable content. Extracting actionable knowledge from online social media has attracted a growing interest from both academia and the industry. We …
Reputation As Public Policy For Internet Security: A Field Study, Qian Tang, Leigh L. Linden, John S. Quarterman, Andrew Whinston
Reputation As Public Policy For Internet Security: A Field Study, Qian Tang, Leigh L. Linden, John S. Quarterman, Andrew Whinston
Research Collection School Of Computing and Information Systems
Cybersecurity is a national priority in this big data era. Because of the lack of incentives and the existence of negative externality, companies often underinvest in addressing security risks and accidents, despite government and industry recommendations. In the present article, we propose a method that utilizes reputation through information disclosure to motivate companies to behave pro-socially, improving their Internet security. Using outbound spam as a proxy for Internet security, we conducted a quasiexperimental field study for eight countries through SpamRankings.net. This outgoingspam-based study shows that information disclosure on outgoing spam can help reduce outgoing spam, approximately by 16 percent. This …
Structural And Functional Analysis Of Multi-Interface Domains, Liang Zhao, Steven C. H. Hoi, Limsoon Wong, Tobias Hamp, Jinyan Li
Structural And Functional Analysis Of Multi-Interface Domains, Liang Zhao, Steven C. H. Hoi, Limsoon Wong, Tobias Hamp, Jinyan Li
Research Collection School Of Computing and Information Systems
A multi-interface domain is a domain that can shape multiple and distinctive binding sites to contact with many other domains, forming a hub in domain-domain interaction networks. The functions played by the multiple interfaces are usually different, but there is no strict bijection between the functions and interfaces as some subsets of the interfaces play the same function. This work applies graph theory and algorithms to discover fingerprints for the multiple interfaces of a domain and to establish associations between the interfaces and functions, based on a huge set of multi-interface proteins from PDB. We found that about 40% of …
An Automated Pathological Class Level Annotation System For Volumetric Brain Images, Thien Anh Dinh, Tomi Silander, C. C. Tchoyoson Lim, Tze-Yun Leong
An Automated Pathological Class Level Annotation System For Volumetric Brain Images, Thien Anh Dinh, Tomi Silander, C. C. Tchoyoson Lim, Tze-Yun Leong
Research Collection School Of Computing and Information Systems
We introduce an automated, pathological class level annotation system for medical volumetric brain images. While much of the earlier work has mainly focused on annotating regions of interest in medical images, our system does not require annotated region level training data nor assumes perfect segmentation results for the regions of interest; the time and effort needed for acquiring training data are hence significantly reduced. This capability of handling high-dimensional noisy data, however, poses additional technical challenges, since statistical estimation of models for such data is prone to over-fitting. We propose a framework that combines a regularized logistic regression method and …
Action Disambiguation Analysis Using Normalized Google-Like Distance Correlogram, Qianru Sun, Hong Liu
Action Disambiguation Analysis Using Normalized Google-Like Distance Correlogram, Qianru Sun, Hong Liu
Research Collection School Of Computing and Information Systems
Classifying realistic human actions in video remains challenging for existing intro-variability and inter-ambiguity in action classes. Recently, Spatial-Temporal Interest Point (STIP) based local features have shown great promise in complex action analysis. However, these methods have the limitation that they typically focus on Bag-of-Words (BoW) algorithm, which can hardly discriminate actions’ ambiguity due to ignoring of spatial-temporal occurrence relations of visual words. In this paper, we propose a new model to capture this contextual relationship in terms of pairwise features’ co-occurrence. Normalized Google-Like Distance (NGLD) is proposed to numerically measuring this co-occurrence, due to its effectiveness in semantic correlation analysis. …
Audit Mechanisms For Provable Risk Management And Accountable Data Governance, Jeremiah Blocki, Nicolas Christin, Anupam Datta, Arunesh Sinha
Audit Mechanisms For Provable Risk Management And Accountable Data Governance, Jeremiah Blocki, Nicolas Christin, Anupam Datta, Arunesh Sinha
Research Collection School Of Computing and Information Systems
Organizations that collect and use large volumes of personal information are expected under the principle of accountable data governance to take measures to protect data subjects from risks that arise from inapproriate uses of this information. In this paper, we focus on a specific class of mechanisms—audits to identify policy violators coupled with punishments—that organizations such as hospitals, financial institutions, and Web services companies may adopt to protect data subjects from privacy and security risks stemming from inappropriate information use by insiders. We model the interaction between the organization (defender) and an insider (adversary) during the audit process as a …
Us Presidential Election 2012 Prediction Using Census Corrected Twitter Model, Junyu Choy, Michelle L. F. Cheong, Nang Laik Ma, Ping Shung Koo
Us Presidential Election 2012 Prediction Using Census Corrected Twitter Model, Junyu Choy, Michelle L. F. Cheong, Nang Laik Ma, Ping Shung Koo
Research Collection School Of Computing and Information Systems
US Presidential Election 2012 has been a very tight race between the two key candidates. Therewere intense battle between the two key candidates. The election reflects the sentiment of theelectorate towards the achievements of the incumbent President Obama. The campaign lastedseveral months and the effects can be felt in the internet and twitter. The presidential debatesinjected new vigor in the challenger's campaign and successfully captured the electorate of severalstates posing a threat to the incumbent's position. Much of the sentiment in the election has beencaptured in the online discussions. In this paper, we will be using the original model described …
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 …
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 …
(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 …
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 …
Snap-And-Ask: Answering Multimodal Question By Naming Visual Instance, Wei Zhang, Lei Pang, Chong-Wah Ngo
Snap-And-Ask: Answering Multimodal Question By Naming Visual Instance, Wei Zhang, Lei Pang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
In real-life, it is easier to provide a visual cue when asking a question about a possibly unfamiliar topic, for example, asking the question, “Where was this crop circle found?”. Providing an image of the instance is far more convenient than texting a verbose description of the visual properties, especially when the name of the query instance is not known. Nevertheless, having to identify the visual instance before processing the question and eventually returning the answer makes multimodal question-answering technically challenging. This paper addresses the problem of visual-totext naming through the paradigm of answering-by-search in a two-stage computational framework, which …
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 …
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.
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 …
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, …
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 …
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). …
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 …
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 …
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 …
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. …
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.