Databases and Information Systems | Open Access Articles

Vireo@Trecvid 2011: Instance Search, Semantic Indexing, Multimedia Event Detection And Known-Item Search, Chong-Wah Ngo, Shi-Ai Zhu, Wei Zhang, Chun-Chet Tan, Ting Yao, Lei Pang, Hung-Khoon Tan

Research Collection School Of Computing and Information Systems

The vireo group participated in four tasks: instance search, semantic indexing, multimedia event detection and known-item search. In this paper,we will present our approaches and discuss the evaluation results.

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Modeling Social Strength In Social Media Community Via Kernel-Based Learning, Jinfeng Zhuang, Tao Mei, Steven C. H. Hoi, Xian-Sheng Hua, Shipeng Li

Research Collection School Of Computing and Information Systems

Modeling continuous social strength rather than conventional binary social ties in the social network can lead to a more precise and informative description of social relationship among people. In this paper, we study the problem of social strength modeling (SSM) for the users in a social media community, who are typically associated with diverse form of data. In particular, we take Flickr---the most popular online photo sharing community---as an example, in which users are sharing their experiences through substantial amounts of multimodal contents (e.g., photos, tags, geo-locations, friend lists) and social behaviors (e.g., commenting and joining interest groups). Such heterogeneous …

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Understanding And Protecting Privacy: Formal Semantics And Principled Audit Mechanisms, Anupam Datta, Jeremiah Blocki, Nicolas Christin, Henry Deyoung, Deepak Garg, Limin Jia, Dilsun Kaynar, Arunesh Sinha

Research Collection School Of Computing and Information Systems

Privacy has become a significant concern in modern society as personal information about individuals is increasingly collected, used, and shared, often using digital technologies, by a wide range of organizations. Certain information handling practices of organizations that monitor individuals’ activities on the Web, data aggregation companies that compile massive databases of personal information, cell phone companies that collect and use location data about individuals, online social networks and search engines—while enabling useful services—have aroused much indignation and protest in the name of privacy. Similarly, as healthcare organizations are embracing electronic health record systems and patient portals to enable patients, employees, …

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Context-Based Friend Suggestion In Online Photo-Sharing Community, Ting Yao, Chong-Wah Ngo, Tao Mei

Research Collection School Of Computing and Information Systems

With the popularity of social media, web users tend to spend more time than before for sharing their experience and interest in online photo-sharing sites. The wide variety of sharing behaviors generate different metadata which pose new opportunities for the discovery of communities. We propose a new approach, named context-based friend suggestion, to leverage the diverse form of contextual cues for more effective friend suggestion in the social media community. Different from existing approaches, we consider both visual and geographical cues, and develop two user-based similarity measurements, i.e., visual similarity and geo similarity for characterizing user relationship. The problem of …

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Determination Of Sin2Θeff W Using Jet Charge Measurements In Hadronic Z Decays, D. Buskulic, M. Thulasidas

Research Collection School Of Computing and Information Systems

The electroweak mixing angle is determined with high precision from measurements of the mean dierence between forward and backward hemisphere charges in hadronic decays of the Z. A data sample of 2:5 million hadronic Z decays recorded over the period 1990 to 1994 in the ALEPH detector at LEP is used. The mean charge separation between event hemispheres containing the original quark and antiquark is measured for b b and cc events in subsamples selected by their long lifetimes or using fast D 's. The corresponding average charge separation for light quarks is measured in an inclusive sample from the …

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Sire: A Social Image Retrieval Engine, Steven C. H. Hoi, Pengcheng Wu

Research Collection School Of Computing and Information Systems

With the explosive growth of social media applications on the internet, billions of social images have been made available in many social media web sites nowadays. This has presented an open challenge of web-scale social image search. Unlike existing commercial web search engines that often adopt text based retrieval, in this demo, we present a novel web-based multimodal paradigm for large-scale social image retrieval, termed "Social Image Retrieval Engine" (SIRE), which effectively exploits both textual and visual contents to narrow down the semantic gap between high-level concepts and low-level visual features. A relevance feedback mechanism is also equipped to learn …

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Modeling 3d Articulated Motions With Conformal Geometry Videos (Cgvs), Dao T. P. Quynh, Ying He, Xiaoming Chen, Jiazhi Xia, Qian Sun, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

3D articulated motions are widely used in entertainment, sports, military, and medical applications. Among various techniques for modeling 3D motions, geometry videos (GVs) are a compact representation in that each frame is parameterized to a 2D domain, which captures the 3D geometry (x, y, z) to a pixel (r, g, b) in the image domain. As a result, the widely studied image/video processing techniques can be directly borrowed for 3D motion. This paper presents conformal geometry videos (CGVs), a novel extension of the traditional geometry videos by taking into the consideration of the isometric nature of 3D articulated motions. We …

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Retrieval-Based Face Annotation By Weak Label Regularized Local Coordinate Coding, Dayong Wang, Steven C. H. Hoi, Ying He, Jianke Zhu

Research Collection School Of Computing and Information Systems

Retrieval-based face annotation is a promising paradigm in mining massive web facial images for automated face annotation. Such an annotation paradigm usually encounters two key challenges. The first challenge is how to efficiently retrieve a short list of most similar facial images from facial image databases, and the second challenge is how to effectively perform annotation by exploiting these similar facial images and their weak labels which are often noisy and incomplete. In this paper, we mainly focus on tackling the second challenge of the retrieval-based face annotation paradigm. In particular, we propose an effective Weak Label Regularized Local Coordinate …

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Four-Jet Final State Production In E+E- Collisions At Centre-Of-Mass Energies Of 130 And 136 Gev, D. Buskulic, M. Thulasidas

Research Collection School Of Computing and Information Systems

The four-jet final state is analyzed to search for hadronic decays of pair-produced heavy particles. The analysis uses the ALEPH data collected at LEP in November 1995 at centre-of-mass energies of 130 and 136 GeV, corresponding to a total integrated luminosity of 5.7 pb1 . An excess of four-jet events is observed with respect to the standard model predictions. In addition, these events exhibit an enhancement in the sum of the two di-jet masses around 105 GeV/c 2 . The properties of these events are studied and compared to the expectations from standard processes and to pair production hypotheses

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Wsm 2011: Third Acm Workshop On Social Media, Steven C. H. Hoi, Michal Jacovi, Ioannis Kompatsiaris, Jiebo Luo, Konstantinos Tserpes

Research Collection School Of Computing and Information Systems

The Third Workshop on Social Media (WSM2011) continues the series of Workshops on Social Media in 2009 and 2010 and has been established as a platform for the presentation and discussion of the latest, key research issues in social media analysis, exploration, search, mining, and emerging new social media applications. It is held in conjunction with the ACM International Multimedia Conference (MM'11) at Scottsdale, Arizona, USA, 2011 and has attracted contributions on various aspects of social media including data mining from social media, content organization, geo-localization, personalization, recommendation systems, user experience, machine learning and social media approaches and architectures for …

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Gender Differences In Virtual Collaboration On A Creative Design Task, Shu Schiller, Fiona Nah, Brian Mennecke, Keng Siau

Research Collection School Of Computing and Information Systems

Collaboration is an important activity in every organization because it fundamentally affects work processes and organizational outcomes. Diversity adds complexity to the mechanism of virtual teams because teams routinely operate virtually by spanning temporal, geographic, national, and cultural boundaries. One important way to decode such complexity is to understand gender differences and their impacts on virtual modes of collaboration. In this research, we examine gender differences and how they influence outcomes and attitudes on virtual collaboration in the context of team gender composition. Phase one of our study involved male-male dyads and female-female dyads that collaborated virtually in Second Life. …

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Validation Of A Model Of Information Systems User Competency, Brenda Eschenbrenner, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

IS user competency, or the ability to realize the fullest potential and the greatest performance from IS use, is important for IS users. However, which factors contribute to IS user competency is unclear. Based on the findings of previous research, a model of IS user competency was developed that focuses on IS-specific characteristics: (i) domain knowledge of and skills in IS, (ii) willingness to try and to explore IS, and (iii) capability of perceiving IS value. The model was validated using the survey approach and the findings suggest that all three factors are pivotal to IS user competency, with willingness …

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An Effective Approach For Topicspecific Opinion Summarization, Binyang Li, Lanjun Zhou, Wei Gao, Kam-Fai Wong, Zhongyu Wei

Research Collection School Of Computing and Information Systems

Topic-specific opinion summarization (TOS) plays an important role in helping users digest online opinions, which targets to extract a summary of opinion expressions specified by a query, i.e. topic-specific opinionated information (TOI). A fundamental problem in TOS is how to effectively represent the TOI of an opinion so that salient opinions can be summarized to meet user’s preference. Existing approaches for TOS are either limited by the mismatch between topic-specific information and its corresponding opinionated information or lack of ability to measure opinionated information associated with different topics, which in turn affect the performance seriously. In this paper, we represent …

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Tag-Based Social Image Search With Visual-Text Joint Hypergraph Learning, Yue Gao, Meng Wang, Huanboo Luan, Jialie Shen, Shuicheng Yan, Dacheng Tao

Research Collection School Of Computing and Information Systems

Tag-based social image search has attracted great interest and how to order the search results based on relevance level is a research problem. Visual content of images and tags have both been investigated. However, existing methods usually employ tags and visual content separately or sequentially to learn the image relevance. This paper proposes a tag-based image search with visual-text joint hypergraph learning. We simultaneously investigate the bag-of-words and bag-of-visual-words representations of images and accomplish the relevance estimation with a hypergraph learning approach. Each textual or visual word generates a hyperedge in the constructed hypergraph. We conduct experiments with a real-world …

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A Brain-Inspired Model Of Hierarchical Planner, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Hierarchical planning is an approach of planning by composing and executing hierarchically arranged plans to solve some problems. Most symbolic-based hierarchical planners have been devised to allow the knowledge to be described expressively. However, a great challenge is to automatically seek and acquire new plans on the fly. This paper presents a novel neural-based model of hierarchical planning that can seek and acquired new plans on-line if the necessary knowledge are lacking. Inspired by findings in neuropsychology, plans can be inherently learnt, retrieved, and manipulated simultaneously rather than discretely processed like in most symbolic approaches. Using a multi-channel adaptive resonance …

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Consistent Community Identification In Complex Networks, Haewoon Kwak, Young-Ho Eom, Yoonchan Choi, Hawoong Jeong

Research Collection School Of Computing and Information Systems

We have found that known community identification algorithms produce inconsistent communities when the node ordering changes at input. We use the pairwise membership probability and consistency to quantify the level of consistency across multiple runs of an algorithm. Based on these two metrics, we address the consistency problem without compromising the modularity. The key insight of the algorithm is to use pairwise membership probabilities as link weights. It offers a new tool in the study of community structures and their evolutions.

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Coping With Distance: An Empirical Study Of Communication On The Jazz Platform, Renuka Sindhgatta, Bikram Sengupta, Subhajit Datta

Research Collection School Of Computing and Information Systems

Global software development - which is characterized by teams separated by physical distance and/or time-zone differences - has traditionally posed significant communication challenges. Often these have caused delays in completing tasks, or created misalignment across sites leading to re-work. In recent years, however, a new breed of development environments with rich collaboration features have emerged to facilitate cross-site work in distributed projects. In this paper we revisit the question "does distance matter?" in the context of IBM Jazz Platform -- a state-of-the-art collaborative development environment. We study the ecosystem of a large distributed team of around 300 members across 35 …

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Finding Relevant Answers In Software Forums, Swapna Gottopati, David Lo, Jing Jiang

Research Collection School Of Computing and Information Systems

Online software forums provide a huge amount of valuable content. Developers and users often ask questions and receive answers from such forums. The availability of a vast amount of thread discussions in forums provides ample opportunities for knowledge acquisition and summarization. For a given search query, current search engines use traditional information retrieval approach to extract webpages containing relevant keywords. However, in software forums, often there are many threads containing similar keywords where each thread could contain a lot of posts as many as 1,000 or more. Manually finding relevant answers from these long threads is a painstaking task to …

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Unsupervised Multiple Kernel Learning, Jinfeng Zhuang, Jialei Wang, Steven C. H. Hoi, Xiangyang Lan

Research Collection School Of Computing and Information Systems

Traditional multiple kernel learning (MKL) algorithms are essentially supervised learning in the sense that the kernel learning task requires the class labels of training data. However, class labels may not always be available prior to the kernel learning task in some real world scenarios, e.g., an early preprocessing step of a classification task or an unsupervised learning task such as dimension reduction. In this paper, we investigate a problem of Unsupervised Multiple Kernel Learning (UMKL), which does not require class labels of training data as needed in a conventional multiple kernel learning task. Since a kernel essentially defines pairwise similarity …

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Software Process Evaluation: A Machine Learning Approach, Ning Chen, Steven C. H. Hoi, Xiaokui Xiao

Research Collection School Of Computing and Information Systems

Software process evaluation is essential to improve software development and the quality of software products in an organization. Conventional approaches based on manual qualitative evaluations (e.g., artifacts inspection) are deficient in the sense that (i) they are time-consuming, (ii) they suffer from the authority constraints, and (iii) they are often subjective. To overcome these limitations, this paper presents a novel semi-automated approach to software process evaluation using machine learning techniques. In particular, we formulate the problem as a sequence classification task, which is solved by applying machine learning algorithms. Based on the framework, we define a new quantitative indicator to …

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Are There Contagion Effects In Information Technology And Business Process Outsourcing?, Arti Mann, Robert J. Kauffman, Kunsoo Han, Barrie R. Nault

Research Collection School Of Computing and Information Systems

We model the diffusion of IT outsourcing using announcements about IT outsourcing deals. We estimate a lognormal diffusion curve to test whether IT outsourcing follows a pure diffusion process or there are contagion effects involved. The methodology permits us to study the consequences of outsourcing events, especially mega-deals with IT contract amounts that exceed US$1 billion. Mega-deals act, we theorize, as precipitating events that create a strong basis for contagion effects and are likely to affect decision-making by other firms in an industry. Then, we evaluate the role of different communication channels in the diffusion process of IT outsourcing by …

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Enabling Gpu Acceleration With Messaging Middleware, Randall E. Duran, Li Zhang, Tom Hayhurst

Research Collection School Of Computing and Information Systems

Graphics processing units (GPUs) offer great potential for accelerating processing for a wide range of scientific and business applications. However, complexities associated with using GPU technology have limited its use in applications. This paper reviews earlier approaches improving GPU accessibility, and explores how integration with middleware messaging technologies can further improve the accessibility and usability of GPU-enabled platforms. The results of a proof-of-concept integration between an open-source messaging middleware platform and a general-purpose GPU platform using the CUDA framework are presented. Additional applications of this technique are identified and discussed as potential areas for further research.

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Learning Human Emotion Patterns For Modeling Virtual Humans, Shu Feng, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Emotion modeling is a crucial part in modeling virtual humans. Although various emotion models have been proposed, most of them focus on designing specific appraisal rules. As there is no unified framework for emotional appraisal, the appraisal variables have to be defined beforehand and evaluated in a subjective way. In this paper, we propose an emotion model based on machine learning methods by taking the following position: an emotion model should mirror actual human emotion in the real world and connect tightly with human inner states, such as drives, motivations and personalities. Specifically, a self-organizing neural model called Emotional Appraisal …

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Efficient Evaluation Of Continuous Text Seach Queries, Kyriakos Mouratidis, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Consider a text filtering server that monitors a stream of incoming documents for a set of users, who register their interests in the form of continuous text search queries. The task of the server is to constantly maintain for each query a ranked result list, comprising the recent documents (drawn from a sliding window) with the highest similarity to the query. Such a system underlies many text monitoring applications that need to cope with heavy document traffic, such as news and email monitoring.In this paper, we propose the first solution for processing continuous text queries efficiently. Our objective is to …

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Active Multiple Kernel Learning For Interactive 3d Object Retrieval Systems, Steven C. H. Hoi, Rong Jin

Research Collection School Of Computing and Information Systems

An effective relevance feedback solution plays a key role in interactive intelligent 3D object retrieval systems. In this work, we investigate the relevance feedback problem for interactive intelligent 3D object retrieval, with the focus on studying effective machine learning algorithms for improving the user's interaction in the retrieval task. One of the key challenges is to learn appropriate kernel similarity measure between 3D objects through the relevance feedback interaction with users. We address this challenge by presenting a novel framework of Active multiple kernel learning (AMKL), which exploits multiple kernel learning techniques for relevance feedback in interactive 3D object retrieval. …

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Mining Direct Antagonistic Communities In Explicit Trust Networks, David Lo, Didi Surian, Zhang Kuan, Ee Peng Lim

Research Collection School Of Computing and Information Systems

There has been a recent increase of interest in analyzing trust and friendship networks to gain insights about relationship dynamics among users. Many sites such as Epinions, Facebook, and other social networking sites allow users to declare trusts or friendships between different members of the community. In this work, we are interested in extracting direct antagonistic communities (DACs) within a rich trust network involving trusts and distrusts. Each DAC is formed by two subcommunities with trust relationships among members of each sub-community but distrust relationships across the sub-communities. We develop an efficient algorithm that could analyze large trust networks leveraging …

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A Survey Of Information Diffusion Models And Relevant Problems, Minh Duc Luu, Tuan Anh Hoang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

There has been tremendous interest in diffusion of innovations or information in a social system. Nowadays, social networks (offline as well as online) are considered as important medium for diffusion and large amount of research has been conducted to understand the dynamics of diffusion in social networks. In this work, we review some of the models proposed for diffusion in social networks. We also highlight the major features of these models by dividing the surveyed models into two categories: non-network and network diffusion models. The former refers to user communities without any knowledge about the user relationship network and the …

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Collaborative Online Learning Of User Generated Content, Guangxia Li, Kuiyu Chang, Steven C. H. Hoi, Wenting Liu, Ramesh Jain

Research Collection School Of Computing and Information Systems

We study the problem of online classification of user generated content, with the goal of efficiently learning to categorize content generated by individual user. This problem is challenging due to several reasons. First, the huge amount of user generated content demands a highly efficient and scalable classification solution. Second, the categories are typically highly imbalanced, i.e., the number of samples from a particular useful class could be far and few between compared to some others (majority class). In some applications like spam detection, identification of the minority class often has significantly greater value than that of the majority class. Last …

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Active Multiple Kernel Learning For Interactive 3d Object Retrieval Systems, Steven C. H. Hoi, Rong Jin

Research Collection School Of Computing and Information Systems

An effective relevance feedback solution plays a key role in interactive intelligent 3D object retrieval systems. In this work, we investigate the relevance feedback problem for interactive intelligent 3D object retrieval, with the focus on studying effective machine learning algorithms for improving the user's interaction in the retrieval task. One of the key challenges is to learn appropriate kernel similarity measure between 3D objects through the relevance feedback interaction with users. We address this challenge by presenting a novel framework of Active multiple kernel learning (AMKL), which exploits multiple kernel learning techniques for relevance feedback in interactive 3D object retrieval. …

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Cooperative Reinforcement Learning In Topology-Based Multi-Agent Systems, Dan Xiao, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Topology-based multi-agent systems (TMAS), wherein agents interact with one another according to their spatial relationship in a network, are well suited for problems with topological constraints. In a TMAS system, however, each agent may have a different state space, which can be rather large. Consequently, traditional approaches to multi-agent cooperative learning may not be able to scale up with the complexity of the network topology. In this paper, we propose a cooperative learning strategy, under which autonomous agents are assembled in a binary tree formation (BTF). By constraining the interaction between agents, we effectively unify the state space of individual …

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Full-Text Articles in Databases and Information Systems

Vireo@Trecvid 2011: Instance Search, Semantic Indexing, Multimedia Event Detection And Known-Item Search, Chong-Wah Ngo, Shi-Ai Zhu, Wei Zhang, Chun-Chet Tan, Ting Yao, Lei Pang, Hung-Khoon Tan

Research Collection School Of Computing and Information Systems

Modeling Social Strength In Social Media Community Via Kernel-Based Learning, Jinfeng Zhuang, Tao Mei, Steven C. H. Hoi, Xian-Sheng Hua, Shipeng Li

Research Collection School Of Computing and Information Systems

Understanding And Protecting Privacy: Formal Semantics And Principled Audit Mechanisms, Anupam Datta, Jeremiah Blocki, Nicolas Christin, Henry Deyoung, Deepak Garg, Limin Jia, Dilsun Kaynar, Arunesh Sinha

Research Collection School Of Computing and Information Systems

Context-Based Friend Suggestion In Online Photo-Sharing Community, Ting Yao, Chong-Wah Ngo, Tao Mei

Research Collection School Of Computing and Information Systems

Determination Of Sin2Θeff W Using Jet Charge Measurements In Hadronic Z Decays, D. Buskulic, M. Thulasidas

Research Collection School Of Computing and Information Systems

Sire: A Social Image Retrieval Engine, Steven C. H. Hoi, Pengcheng Wu

Research Collection School Of Computing and Information Systems

Modeling 3d Articulated Motions With Conformal Geometry Videos (Cgvs), Dao T. P. Quynh, Ying He, Xiaoming Chen, Jiazhi Xia, Qian Sun, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Retrieval-Based Face Annotation By Weak Label Regularized Local Coordinate Coding, Dayong Wang, Steven C. H. Hoi, Ying He, Jianke Zhu

Research Collection School Of Computing and Information Systems

Four-Jet Final State Production In E+E- Collisions At Centre-Of-Mass Energies Of 130 And 136 Gev, D. Buskulic, M. Thulasidas

Research Collection School Of Computing and Information Systems

Wsm 2011: Third Acm Workshop On Social Media, Steven C. H. Hoi, Michal Jacovi, Ioannis Kompatsiaris, Jiebo Luo, Konstantinos Tserpes

Research Collection School Of Computing and Information Systems

Gender Differences In Virtual Collaboration On A Creative Design Task, Shu Schiller, Fiona Nah, Brian Mennecke, Keng Siau

Research Collection School Of Computing and Information Systems

Validation Of A Model Of Information Systems User Competency, Brenda Eschenbrenner, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

An Effective Approach For Topicspecific Opinion Summarization, Binyang Li, Lanjun Zhou, Wei Gao, Kam-Fai Wong, Zhongyu Wei

Research Collection School Of Computing and Information Systems

Tag-Based Social Image Search With Visual-Text Joint Hypergraph Learning, Yue Gao, Meng Wang, Huanboo Luan, Jialie Shen, Shuicheng Yan, Dacheng Tao

Research Collection School Of Computing and Information Systems

A Brain-Inspired Model Of Hierarchical Planner, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Consistent Community Identification In Complex Networks, Haewoon Kwak, Young-Ho Eom, Yoonchan Choi, Hawoong Jeong

Research Collection School Of Computing and Information Systems

Coping With Distance: An Empirical Study Of Communication On The Jazz Platform, Renuka Sindhgatta, Bikram Sengupta, Subhajit Datta

Research Collection School Of Computing and Information Systems

Finding Relevant Answers In Software Forums, Swapna Gottopati, David Lo, Jing Jiang

Research Collection School Of Computing and Information Systems

Unsupervised Multiple Kernel Learning, Jinfeng Zhuang, Jialei Wang, Steven C. H. Hoi, Xiangyang Lan

Research Collection School Of Computing and Information Systems

Software Process Evaluation: A Machine Learning Approach, Ning Chen, Steven C. H. Hoi, Xiaokui Xiao

Research Collection School Of Computing and Information Systems

Are There Contagion Effects In Information Technology And Business Process Outsourcing?, Arti Mann, Robert J. Kauffman, Kunsoo Han, Barrie R. Nault

Research Collection School Of Computing and Information Systems

Enabling Gpu Acceleration With Messaging Middleware, Randall E. Duran, Li Zhang, Tom Hayhurst

Research Collection School Of Computing and Information Systems

Learning Human Emotion Patterns For Modeling Virtual Humans, Shu Feng, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Efficient Evaluation Of Continuous Text Seach Queries, Kyriakos Mouratidis, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Active Multiple Kernel Learning For Interactive 3d Object Retrieval Systems, Steven C. H. Hoi, Rong Jin

Research Collection School Of Computing and Information Systems

Mining Direct Antagonistic Communities In Explicit Trust Networks, David Lo, Didi Surian, Zhang Kuan, Ee Peng Lim

Research Collection School Of Computing and Information Systems

A Survey Of Information Diffusion Models And Relevant Problems, Minh Duc Luu, Tuan Anh Hoang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Collaborative Online Learning Of User Generated Content, Guangxia Li, Kuiyu Chang, Steven C. H. Hoi, Wenting Liu, Ramesh Jain

Research Collection School Of Computing and Information Systems

Active Multiple Kernel Learning For Interactive 3d Object Retrieval Systems, Steven C. H. Hoi, Rong Jin

Research Collection School Of Computing and Information Systems

Cooperative Reinforcement Learning In Topology-Based Multi-Agent Systems, Dan Xiao, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems