Efficient Evaluation Of Continuous Text Seach Queries,
2011
Singapore Management University
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 …
Active Multiple Kernel Learning For Interactive 3d Object Retrieval Systems,
2011
Singapore Management University
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. …
Mining Direct Antagonistic Communities In Explicit Trust Networks,
2011
Singapore Management University
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 …
A Survey Of Information Diffusion Models And Relevant Problems,
2011
Singapore Management University
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 …
Collaborative Online Learning Of User Generated Content,
2011
Nanyang Technological University
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 …
Active Multiple Kernel Learning For Interactive 3d Object Retrieval Systems,
2011
Singapore Management University
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. …
Cooperative Reinforcement Learning In Topology-Based Multi-Agent Systems,
2011
Singapore Management University
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 …
Direction-Based Surrounder Queries For Mobile Recommendations,
2011
Nagoya University
Direction-Based Surrounder Queries For Mobile Recommendations, Xi Guo, Baihua Zheng, Yoshiharu Ishikawa, Yunjun Gao
Research Collection School Of Computing and Information Systems
Location-based recommendation services recommend objects to the user based on the user’s preferences. In general, the nearest objects are good choices considering their spatial proximity to the user. However, not only the distance of an object to the user but also their directional relationship are important. Motivated by these, we propose a new spatial query, namely a direction-based surrounder (DBS) query, which retrieves the nearest objects around the user from different directions. We define the DBS query not only in a two-dimensional Euclidean space E">EE but also in a road network R">RR . In the Euclidean space E" …
Context-Aware Nearest Neighbor Query On Social Networks,
2011
Singapore Management University
Context-Aware Nearest Neighbor Query On Social Networks, Yazhe Wang, Baihua Zheng
Research Collection School Of Computing and Information Systems
Social networking has grown rapidly over the last few years, and social networks contain a huge amount of content. However, it can be not easy to navigate the social networks to find specific information. In this paper, we define a new type of queries, namely context-aware nearest neighbor (CANN) search over social network to retrieve the nearest node to the query node that matches the context specified. CANN considers both the structure of the social network, and the profile information of the nodes. We design ahyper-graph based index structure to support approximated CANN search efficiently.
Location-Dependent Spatial Query Containment,
2011
University of Massachusetts - Dartmouth
Location-Dependent Spatial Query Containment, Ken C. K. Lee, Brandon Unger, Baihua Zheng, Wang-Chien Lee
Research Collection School Of Computing and Information Systems
Nowadays, location-related information is highly accessible to mobile users via issuing Location-Dependent Spatial Queries (LDSQs) with respect to their locations wirelessly to Location-Based Service (LBS) servers. Due to the limited mobile device battery energy, scarce wireless bandwidth, and heavy LBS server workload, the number of LDSQs submitted over wireless channels to LBS servers for evaluation should be minimized as appropriate. In this paper, we exploit query containment techniques for LDSQs (called LDSQ containment) to enable mobile clients to determine whether the result of a new LDSQ Q′ is completely covered by that of another LDSQ Q previously answered by a …
On Modeling Virality Of Twitter Content,
2011
Singapore Management University
On Modeling Virality Of Twitter Content, Tuan Anh Hoang, Ee Peng Lim, Palakorn Achananuparp, Jing Jiang, Feida Zhu
Research Collection School Of Computing and Information Systems
Twitter is a popular microblogging site where users can easily use mobile phones or desktop machines to generate short messages to be shared with others in realtime. Twitter has seen heavy usage in many recent international events including Japan earthquake, Iran election, etc. In such events, many tweets may become viral for different reasons. In this paper, we study the virality of socio-political tweet content in the Singapore’s 2011 general election (GE2011). We collected tweet data generated by about 20K Singapore users from 1 April 2011 till 12 May 2011, and the follow relationships among them. We introduce several quantitative …
Using Social Annotations For Trend Discovery In Scientific Publications,
2011
Singapore Management University
Using Social Annotations For Trend Discovery In Scientific Publications, Meiqun Hu, Ee Peng Lim, Jing Jiang
Research Collection School Of Computing and Information Systems
Social tags and citing documents are two forms of social annotations to scientific publications. These social annotations provide useful contextual and temporal information for the annotated work, which encapsulates the attention and interest of the annotators. In this work, we explore the use of social annotations for discovering trends in scientific publications. We propose a trend discovery process that employs trend estimation and trend selection and ranking for analyzing the emerging trends shown in the social annotation profiles. The proposed sigmoid trend estimator allows us to characterize and compare how much, when and how fast the trends emerge. To perform …
The Niddk Central Repository At 8 Years—Ambition, Revision, Use And Impact,
2011
CUNY Queens College
The Niddk Central Repository At 8 Years—Ambition, Revision, Use And Impact, Charles F. Turner, Huaqin Pan, Gregg W. Silk, Mary-Anne Ardini, Vesselina Bakalov, Stephanie Bryant, Susanna Cantor, Kung-Yen Chang, Michael Delatte, Paul Eggers, Laxminarayana Ganapathi, Sujatha Lakshmikanthan, Joshua Levy, Sheping Li, Joseph Pratt, Norma Pugh, Ying Qin, Rebekah Rasooly, Helen Ray, Jean E. Richardson, Amanda Flynn Riley, Susan M. Rogers, Charlotte Scheper, Sylvia Tan, Stacie White, Philip C. Cooley
Publications and Research
The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Central Repository makes data and biospecimens from NIDDK-funded research available to the broader scientific community. It thereby facilitates: the testing of new hypotheses without new data or biospecimen collection; pooling data across several studies to increase statistical power; and informative genetic analyses using the Repository’s well-curated phenotypic data. This article describes the initial database plan for the Repository and its revision using a simpler model. Among the lessons learned were the trade-offs between the complexity of a database design and the costs in time and money of implementation; the …
Semantic Computing In Real-World: Vertical And Horizontal Application Within Enterprise And On The Web,
2011
Wright State University - Main Campus
Semantic Computing In Real-World: Vertical And Horizontal Application Within Enterprise And On The Web, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Kino: A Generic Document Management System For Biologists Using Sa-Rest And Faceted Search,
2011
Wright State University - Main Campus
Kino: A Generic Document Management System For Biologists Using Sa-Rest And Faceted Search, Ajith Harshana Ranabahu, Priti Parikh, Maryam Panahiazar, Amit P. Sheth
Kno.e.sis Publications
Document management has become an important consideration for the scientific community over the last decade. Human knowledge is central to many scientific domains, thus it is not possible to completely automate the document management process. Managing scientific documents require a semi-automatic approach to overcome issues of large volume, yet support the human participation in the process. In this paper we present Kino, a set of tools that streamline the document management process in life science domains. Kino is integrated with National Center for Biomedical Ontology (NCBO), providing scientists access to quality domain models. Annotated documents are indexed using a faceted …
Spectral Geometry Image: Image Based 3d Models For Digital Broadcasting Applications,
2011
Nanyang Technological University
Spectral Geometry Image: Image Based 3d Models For Digital Broadcasting Applications, Boon Seng Chew, Lap Pui Chau, Ying He, Dayong Wang, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
The use of 3D models for progressive transmission and broadcasting applications is an interesting challenge due to the nature and complexity of such content. In this paper, a new image format for the representation of 3D progressive model is proposed. The powerful spectral analysis is combined with the state of art Geometry Image(GI) to encode static 3D models into spectral geometry images(SGI) for robust 3D shape representation. Based on the 3D model's surface characteristics, SGI separated the geometrical image into low and high frequency layers to achieve effective Level of Details(LOD) modeling. For SGI, the connectivity data of the model …
Privacy Beyond Single Sensitive Attribute,
2011
Singapore Management University
Privacy Beyond Single Sensitive Attribute, Yuan Fang, Mafruz Zaman Ashrafi, See Kiong Ng
Research Collection School Of Computing and Information Systems
Publishing individual specific microdata has serious privacy implications. The k-anonymity model has been proposed to prevent identity disclosure from microdata, and the work on ℓ-diversity and t-closeness attempt to address attribute disclosure. However, most current work only deal with publishing microdata with a single sensitive attribute (SA), whereas real life scenarios often involve microdata with multiple SAs that may be multi-valued. This paper explores the issue of attribute disclosure in such scenarios. We propose a method called CODIP (Complete Disjoint Projections) that outlines a general solution to deal with the shortcomings in a naïve approach. We also introduce two measures, …
An Efficient Adaptive Vortex Particle Method For Real-Time Smoke Simulation,
2011
Singapore Management University
An Efficient Adaptive Vortex Particle Method For Real-Time Smoke Simulation, Shengfeng He, Hon-Cheng Wong, Un-Hong Wong
Research Collection School Of Computing and Information Systems
Smoke simulation is one of the interesting topics in computer animation and it usually involves turbulence generation. Efficient generation of realistic turbulent flows becomes one of the challenges in smoke simulation. Vortex particle method, which is a hybrid method that combines grid-based and particle-based approaches, is often used for generating turbulent details. However, it may cause irrational artifacts due to its initial condition and vorticity forcing approach used. In this paper, a new vorticity forcing approach based on the spatial adaptive vorticity confinement is proposed to address this problem. In this approach, the spatial adaptive vorticity confinement force varies with …
Structural Analysis Of The Hot Spots In The Binding Between H1n1 Ha And The 2di Antibody: Do Mutations Of H1n1 From 1918 To 2009 Affect Much On This Binding?,
2011
Nanyang Technological University
Structural Analysis Of The Hot Spots In The Binding Between H1n1 Ha And The 2di Antibody: Do Mutations Of H1n1 From 1918 To 2009 Affect Much On This Binding?, Qian Liu, Steven C. H. Hoi, Chinh T. T. Su, Zhenhua Li, Chee-Keong Kwoh, Limsoon Wong, Jinyan Li
Research Collection School Of Computing and Information Systems
Worldwide and substantial mortality caused by the 2009 H1N1 influenza A has stimulated a new surge of research on H1N1 viruses. An epitope conservation has been learned in the HA1 protein that allows antibodies to cross-neutralize both 1918 and 2009 H1N1. However, few works have thoroughly studied the binding hot spots in those two antigen–antibody interfaces which are responsible for the antibody cross-neutralization. We apply predictive methods to identify binding hot spots at the epitope sites of the HA1 proteins and at the paratope sites of the 2D1 antibody. We find that the six mutations at the HA1's epitope from …
When Recommendation Meets Mobile: Contextual And Personalised Recommendation On The Go,
2011
Nanyang Technological University
When Recommendation Meets Mobile: Contextual And Personalised Recommendation On The Go, Jinfeng Zhuang, Tao Mei, Steven C. H. Hoi, Ying-Qing Xu, Shipeng Li
Research Collection School Of Computing and Information Systems
Mobile devices are becoming ubiquitous. People use their phones as a personal concierge discovering and making decisions anywhere and anytime. Understanding user intent on the go therefore becomes important for task completion on the phone. While existing efforts have predominantly focused on understanding the explicit user intent expressed by a textual or voice query, this paper presents an approach to context-aware and personalized entity recommendation which understands the implicit intent without any explicit user input on the phone. The approach, highly motivated from a large-scale mobile click-through analysis, is able to rank both the entity types and the entities within …
