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Articles 421 - 450 of 511
Full-Text Articles in Computer Engineering
Analysis Of Tradeoffs Between Buffer And Qos Requirements In Wireless Networks, Raphael Rom, Hwee-Pink Tan
Analysis Of Tradeoffs Between Buffer And Qos Requirements In Wireless Networks, Raphael Rom, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
In this paper, we consider the scheduling problem where data packets from K input-flows need to be delivered to K corresponding wireless receivers over a heterogeneous wireless channel. Our objective is to design a wireless scheduler that achieves good throughput and fairness performance while minimizing the buffer requirement at each wireless receiver. This is a challenging problem due to the unique characteristics of the wireless channel. We propose a novel idea of exploiting both the long-term and short-term error behavior of the wireless channel in the scheduler design. In addition to typical first-order Quality of Service (QoS) metrics such as …
Admission Control For Differentiated Services In Future Generation Cdma Networks, Hwee-Pink Tan, Rudesindo Núñez-Queija, Adriana F. Gabor, Onno J. Boxma
Admission Control For Differentiated Services In Future Generation Cdma Networks, Hwee-Pink Tan, Rudesindo Núñez-Queija, Adriana F. Gabor, Onno J. Boxma
Research Collection School Of Computing and Information Systems
Future Generation CDMA wireless systems, e.g., 3G, can simultaneously accommodate flow transmissions of users with widely heterogeneous applications. As radio resources are limited, we propose an admission control rule that protects users with stringent transmission bit-rate requirements (“streaming traffic”) while offering sufficient capacity over longer time intervals to delay-tolerant users (“elastic traffic”). While our strategy may not satisfy classical notions of fairness, we aim to reduce congestion and increase overall throughput of elastic users. Using time-scale decomposition, we develop approximations to evaluate the performance of our differentiated admission control strategy to support integrated services with transmission bit-rate requirements in a …
Large-Scale Near-Duplicate Web Video Search: Challenge And Opportunity, Wan-Lei Zhao, Song Tan, Chong-Wah Ngo
Large-Scale Near-Duplicate Web Video Search: Challenge And Opportunity, Wan-Lei Zhao, Song Tan, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
The massive amount of near-duplicate and duplicate web videos has presented both challenge and opportunity to multimedia computing. On one hand, browsing videos on Internet becomes highly inefficient for the need to repeatedly fast-forward videos of similar content. On the other hand, the tremendous amount of somewhat duplicate content also makes some traditionally difficult vision tasks become simple and easy. For example, annotating pictures can be as simple as recycling the tags of Internet images retrieved from image search engines. Such tasks, of either to eliminate or to recycle near-duplicates, can usually be achieved by the nearest neighbor search of …
Exploring Inter-Concept Relationship With Context Space For Semantic Video Indexing, Xiao-Yong Wei, Yu-Gang Jiang, Chong-Wah Ngo
Exploring Inter-Concept Relationship With Context Space For Semantic Video Indexing, Xiao-Yong Wei, Yu-Gang Jiang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Semantic concept detectors are often individually and independently developed. Using peripherally related concepts for leveraging the power of joint detection, which is referred to as context-based concept fusion (CBCF), has been one of the focus studies in recent years. This paper proposes the construction of a context space and the exploration of the space for CBCF. Context space considers the global consistency of concept relationship, addresses the problem of missing annotation, and is extensible for cross-domain contextual fusion. The space is linear and can be built by modeling the inter-concept relationship through annotation provided by either manual labeling or machine …
Learning And Inferencing In User Ontology For Personalized Semantic Web Search, Xing Jiang, Ah-Hwee Tan
Learning And Inferencing In User Ontology For Personalized Semantic Web Search, Xing Jiang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
User modeling is aimed at capturing the users’ interests in a working domain, which forms the basis of providing personalized information services. In this paper, we present an ontology based user model, called user ontology, for providing personalized information service in the Semantic Web. Different from the existing approaches that only use concepts and taxonomic relations for user modeling, the proposed user ontology model utilizes concepts, taxonomic relations, and non-taxonomic relations in a given domain ontology to capture the users’ interests. As a customized view of the domain ontology, a user ontology provides a richer and more precise representation of …
Visual Word Proximity And Linguistics For Semantic Video Indexing And Near-Duplicate Retrieval, Yu-Gang Jiang, Chong-Wah Ngo
Visual Word Proximity And Linguistics For Semantic Video Indexing And Near-Duplicate Retrieval, Yu-Gang Jiang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Bag-of-visual-words (BoW) has recently become a popular representation to describe video and image content. Most existing approaches, nevertheless, neglect inter-word relatedness and measure similarity by bin-to-bin comparison of visual words in histograms. In this paper, we explore the linguistic and ontological aspects of visual words for video analysis. Two approaches, soft-weighting and constraint-based earth mover’s distance (CEMD), are proposed to model different aspects of visual word linguistics and proximity. In soft-weighting, visual words are cleverly weighted such that the linguistic meaning of words is taken into account for bin-to-bin histogram comparison. In CEMD, a cross-bin matching algorithm is formulated such …
Learning Image‐Text Associations, Tao Jiang, Ah-Hwee Tan
Learning Image‐Text Associations, Tao Jiang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Web information fusion can be defined as the problem of collating and tracking information related to specific topics on the World Wide Web. Whereas most existing work on Web information fusion has focused on text-based multidocument summarization, this paper concerns the topic of image and text association, a cornerstone of cross-media Web information fusion. Specifically, we present two learning methods for discovering the underlying associations between images and texts based on small training data sets. The first method based on vague transformation measures the information similarity between the visual features and the textual features through a set of predefined domain-specific …
Integrated Cognitive Architectures: A Survey, Hui-Qing Chong, Ah-Hwee Tan, Gee-Wah Ng
Integrated Cognitive Architectures: A Survey, Hui-Qing Chong, Ah-Hwee Tan, Gee-Wah Ng
Research Collection School Of Computing and Information Systems
This article aims to present an account of the state of the art research in the field of integrated cognitive architectures by providing a review of six cognitive architectures, namely Soar, ACT-R, ICARUS, BDI, the subsumption architecture and CLARION. We conduct a detailed functional comparison by looking at a wide range of cognitive components, including perception, memory, goal representation, planning, problem solving, reasoning, learning, and relevance to neurobiology. In addition, we study the range of benchmarks and applications that these architectures have been applied to. Although no single cognitive architecture has provided a full solution with the level of human …
Modelling Situation Awareness For Context‐Aware Decision Support, Yu-Hong Feng, Teck-Hou Teng, Ah-Hwee Tan
Modelling Situation Awareness For Context‐Aware Decision Support, Yu-Hong Feng, Teck-Hou Teng, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Situation awareness modelling is popularly used in the command and control domain for situation assessment and decision support. However, situation models in real-world applications are typically complex and not easy to use. This paper presents a Context-aware Decision Support (CaDS) system, which consists of a situation model for shared situation awareness modelling and a group of entity agents, one for each individual user, for focused and customized decision support. By incorporating a rule-based inference engine, the entity agents provide functions including event classification, action recommendation, and proactive decision making. The implementation and the performance of the proposed system are demonstrated …
Fusing Semantics, Observability, Reliability And Diversity Of Concept Detectors For Video Search, Xiao-Yong Wei, Chong-Wah Ngo
Fusing Semantics, Observability, Reliability And Diversity Of Concept Detectors For Video Search, Xiao-Yong Wei, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Effective utilization of semantic concept detectors for large-scale video search has recently become a topic of intensive studies. One of main challenges is the selection and fusion of appropriate detectors, which considers not only semantics but also the reliability of detectors, observability and diversity of detectors in target video domains. In this paper, we present a novel fusion technique which considers different aspects of detectors for query answering. In addition to utilizing detectors for bridging the semantic gap of user queries and multimedia data, we also address the issue of "observability gap" among detectors which could not be directly inferred …
Ontology-Based Visual Word Matching For Near-Duplicate Retrieval, Yu-Gang Jiang, Chong-Wah Ngo
Ontology-Based Visual Word Matching For Near-Duplicate Retrieval, Yu-Gang Jiang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper proposes a novel approach to exploit the ontological relationship of visual words by linguistic reasoning. A visual word ontology is constructed to facilitate the rigorous evaluation of linguistic similarity across visual words. The linguistic similarity measurement enables cross-bin matching of visual words, compromising the effectiveness and speed of conventional keypoint matching and bag-of-word approaches. A constraint EMD is proposed and experimented to efficiently match visual words. Empirical findings indicate that the proposed approach offers satisfactory performance to near-duplicate retrieval, while still enjoying the merit of speed efficiency compared with other techniques.
Modeling Video Hyperlinks With Hypergraph For Web Video Reranking, Hung-Khoon Tan, Chong-Wah Ngo, Xiao Wu
Modeling Video Hyperlinks With Hypergraph For Web Video Reranking, Hung-Khoon Tan, Chong-Wah Ngo, Xiao Wu
Research Collection School Of Computing and Information Systems
In this paper, we investigate a novel approach of exploiting visual-duplicates for web video reranking using hypergraph. Current graph-based reranking approaches consider mainly the pair-wise linking of keyframes and ignore reliability issues that are inherent in such representation. We exploit higher order relation to overcome the issues of missing links in visual-duplicate keyframes and in addition identify the latent relationships among keyframes. Based on hypergraph, we consider two groups of video threads: visual near-duplicate threads and story threads, to hyperlink web videos and describe the higher order information existing in video content. To facilitate reranking using random walk algorithm, the …
Bag-Of-Visual-Words Expansion Using Visual Relatedness For Video Indexing, Yu-Gang Jiang, Chong-Wah Ngo
Bag-Of-Visual-Words Expansion Using Visual Relatedness For Video Indexing, Yu-Gang Jiang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Bag-of-visual-words (BoW) has been popular for visual classification in recent years. In this paper, we propose a novel BoW expansion method to alleviate the effect of visual word correlation problem. We achieve this by diffusing the weights of visual words in BoW based on visual word relatedness, which is rigorously defined within a visual ontology. The proposed method is tested in video indexing experiment on TRECVID-2006 video retrieval benchmark, and an improvement of 7% over the traditional BoW is reported.
Searching Blogs And News: A Study On Popular Queries, Aixin Sun, Meishan Hu, Ee Peng Lim
Searching Blogs And News: A Study On Popular Queries, Aixin Sun, Meishan Hu, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Blog/news search engines are very important channels to reach information about the real-time happenings. In this paper, we study the popular queries collected over one year period and compare their search results returned by a blog search engine (i.e., Technorati) and a news search engine (i.e., Google News). We observed that the numbers of hits returned by the two search engines for the same set of queries were highly correlated, suggesting that blogs often provide commentary to current events reported in news. As many popular queries are related to some events, we further observed a high cohesiveness among the returned …
Integrating Temporal Difference Methods And Self‐Organizing Neural Networks For Reinforcement Learning With Delayed Evaluative Feedback, Ah-Hwee Tan, Ning Lu, Dan Xiao
Integrating Temporal Difference Methods And Self‐Organizing Neural Networks For Reinforcement Learning With Delayed Evaluative Feedback, Ah-Hwee Tan, Ning Lu, Dan Xiao
Research Collection School Of Computing and Information Systems
This paper presents a neural architecture for learning category nodes encoding mappings across multimodal patterns involving sensory inputs, actions, and rewards. By integrating adaptive resonance theory (ART) and temporal difference (TD) methods, the proposed neural model, called TD fusion architecture for learning, cognition, and navigation (TD-FALCON), enables an autonomous agent to adapt and function in a dynamic environment with immediate as well as delayed evaluative feedback (reinforcement) signals. TD-FALCON learns the value functions of the state-action space estimated through on-policy and off-policy TD learning methods, specifically state-action-reward-state-action (SARSA) and Q-learning. The learned value functions are then used to determine the …
Multimodal News Story Clustering With Pairwise Visual Near-Duplicate Constraint, Xiao Wu, Chong-Wah Ngo, Alexander G. Hauptmann
Multimodal News Story Clustering With Pairwise Visual Near-Duplicate Constraint, Xiao Wu, Chong-Wah Ngo, Alexander G. Hauptmann
Research Collection School Of Computing and Information Systems
Story clustering is a critical step for news retrieval, topic mining, and summarization. Nonetheless, the task remains highly challenging owing to the fact that news topics exhibit clusters of varying densities, shapes, and sizes. Traditional algorithms are found to be ineffective in mining these types of clusters. This paper offers a new perspective by exploring the pairwise visual cues deriving from near-duplicate keyframes (NDK) for constraint-based clustering. We propose a constraint-driven co-clustering algorithm (CCC), which utilizes the near-duplicate constraints built on top of text, to mine topic-related stories and the outliers. With CCC, the duality between stories and their underlying …
Columbia University/Vireo-Cityu/Irit Trecvid2008 High-Level Feature Extraction And Interactive Video Search, Shih-Fu Chang, Junfeng He, Yu-Gang Jiang, Elie El Khoury, Chong-Wah Ngo, Akira Yanagawa, Eric Zavesky
Columbia University/Vireo-Cityu/Irit Trecvid2008 High-Level Feature Extraction And Interactive Video Search, Shih-Fu Chang, Junfeng He, Yu-Gang Jiang, Elie El Khoury, Chong-Wah Ngo, Akira Yanagawa, Eric Zavesky
Research Collection School Of Computing and Information Systems
In this report, we present overview and comparative analysis of our HLF detection system, which achieves the top performance among all type-A submissions in 2008. We also describe preliminary evaluation of our video search system, CuZero, in the interactive search task.
Concept Detection: Convergence To Local Features And Opportunities Beyond, Shih-Fu Chang, Junfeng He, Yu-Gang Jiang, Elie El Khoury, Chong-Wah Ngo, Akira Yanagawa, Eric Zavesky
Concept Detection: Convergence To Local Features And Opportunities Beyond, Shih-Fu Chang, Junfeng He, Yu-Gang Jiang, Elie El Khoury, Chong-Wah Ngo, Akira Yanagawa, Eric Zavesky
Research Collection School Of Computing and Information Systems
No abstract provided.
Competitive Equilibrium In E-Commerce: Pricing And Outsourcing, Parijat Dube, Zhen Liu, Laura Wynter, Cathy Xia
Competitive Equilibrium In E-Commerce: Pricing And Outsourcing, Parijat Dube, Zhen Liu, Laura Wynter, Cathy Xia
Research Collection School Of Computing and Information Systems
The success of firms engaged in e-commerce depends on their ability to understand and exploit the dynamics of the market. One component of this is the ability to extract maximum profit and minimize costs in the face of the harsh competition that the internet provides. We present a general framework for modeling the competitive equilibrium across two firms, or across a firm and the market as a whole. Within this framework, we study pricing choices and analyze the decision to outsource IT capability. Our framework is novel in that it allows for any number of distributions on usage levels, price–QoS …
Self-Organizing Neural Architectures And Cooperative Learning In A Multiagent Environment, Dan Xiao, Ah-Hwee Tan
Self-Organizing Neural Architectures And Cooperative Learning In A Multiagent Environment, Dan Xiao, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Temporal-Difference–Fusion Architecture for Learning, Cognition, and Navigation (TD-FALCON) is a generalization of adaptive resonance theory (a class of self-organizing neural networks) that incorporates TD methods for real-time reinforcement learning. In this paper, we investigate how a team of TD-FALCON networks may cooperate to learn and function in a dynamic multiagent environment based on minefield navigation and a predator/prey pursuit tasks. Experiments on the navigation task demonstrate that TD-FALCON agent teams are able to adapt and function well in a multiagent environment without an explicit mechanism of collaboration. In comparison, traditional Q-learning agents using gradient-descent-based feedforward neural networks, trained with the …
A Two-Phase Approach To Interactivity Enhancement For Large-Scale Distributed Virtual Environments, Nguyen Binh Duong Ta, Suiping Zhou
A Two-Phase Approach To Interactivity Enhancement For Large-Scale Distributed Virtual Environments, Nguyen Binh Duong Ta, Suiping Zhou
Research Collection School Of Computing and Information Systems
Distributed virtual environments (DVEs) are distributed systems that allow multiple geographically distributed clients (users) to interact simultaneously in a computer-generated, shared virtual world. Applications of DVEs can be seen in many areas nowadays, such as online games, military simulations, collaborative designs, etc. To support large-scale DVEs with real-time interactions among thousands or even more distributed clients, a geographically distributed server architecture (GDSA) is generally needed, and the virtual world can be partitioned into many distinct zones to distribute the load among the servers. Due to the geographic distributions of clients and servers in such architectures, it is essential to efficiently …
Practical Elimination Of Near-Duplicates From Web Video Search, Xiao Wu, Alexander G. Hauptmann, Chong-Wah Ngo
Practical Elimination Of Near-Duplicates From Web Video Search, Xiao Wu, Alexander G. Hauptmann, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Current web video search results rely exclusively on text keywords or user-supplied tags. A search on typical popular video often returns many duplicate and near-duplicate videos in the top results. This paper outlines ways to cluster and filter out the nearduplicate video using a hierarchical approach. Initial triage is performed using fast signatures derived from color histograms. Only when a video cannot be clearly classified as novel or nearduplicate using global signatures, we apply a more expensive local feature based near-duplicate detection which provides very accurate duplicate analysis through more costly computation. The results of 24 queries in a data …
Evaluating Bag-Of-Visual-Words Representations In Scene Classification, Jun Yang, Yu-Gang Jiang, Alexander G. Hauptmann, Chong-Wah Ngo
Evaluating Bag-Of-Visual-Words Representations In Scene Classification, Jun Yang, Yu-Gang Jiang, Alexander G. Hauptmann, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Based on keypoints extracted as salient image patches, an image can be described as a “bag of visual words” and this representation has been used in scene classification. The choice of dimension, selection, and weighting of visual words in this representation is crucial to the classification performance but has not been thoroughly studied in previous work. Given the analogy between this representation and the bag-of-words representation of text documents, we apply techniques used in text categorization, including term weighting, stop word removal, feature selection, to generate image representations that differ in the dimension, selection, and weighting of visual words. The …
Ontology-Enriched Semantic Space For Video Search, Xiao-Yong Wei, Chong-Wah Ngo
Ontology-Enriched Semantic Space For Video Search, Xiao-Yong Wei, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Multimedia-based ontology construction and reasoning have recently been recognized as two important issues in video search, particularly for bridging semantic gap. The lack of coincidence between low-level features and user expectation makes concept-based ontology reasoning an attractive midlevel framework for interpreting high-level semantics. In this paper, we propose a novel model, namely ontology-enriched semantic space (OSS), to provide a computable platform for modeling and reasoning concepts in a linear space. OSS enlightens the possibility of answering conceptual questions such as a high coverage of semantic space with minimal set of concepts, and the set of concepts to be developed for …
Insults In Your Inbox, M. Thulasidas
Insults In Your Inbox, M. Thulasidas
Research Collection School Of Computing and Information Systems
Email is a boon at work, but aggressive staff may use it to inflict humiliation. Most of its impact has been positive. An email from the big boss to all@yourcompany, for instance, is a fair substitute for a general communication meet- ing. In smaller teams, email often saves meetings and increases productivity.
Cost-Time Sensitive Decision Tree With Missing Values, Shichao Zhang, Xiaofeng Zhu, Jilian Zhang, Chengqi Zhang
Cost-Time Sensitive Decision Tree With Missing Values, Shichao Zhang, Xiaofeng Zhu, Jilian Zhang, Chengqi Zhang
Research Collection School Of Computing and Information Systems
Cost-sensitive decision tree learning is very important and popular in machine learning and data mining community. There are many literatures focusing on misclassification cost and test cost at present. In real world application, however, the issue of time-sensitive should be considered in cost-sensitive learning. In this paper, we regard the cost of time-sensitive in cost-sensitive learning as waiting cost (referred to WC), a novelty splitting criterion is proposed for constructing cost-time sensitive (denoted as CTS) decision tree for maximal decrease the intangible cost. And then, a hybrid test strategy that combines the sequential test with the batch test strategies is …
Towards Optimal Bag-Of-Features For Object Categorization And Semantic Video Retrieval, Yu-Gang Jiang, Chong-Wah Ngo, Jun Yang
Towards Optimal Bag-Of-Features For Object Categorization And Semantic Video Retrieval, Yu-Gang Jiang, Chong-Wah Ngo, Jun Yang
Research Collection School Of Computing and Information Systems
Bag-of-features (BoF) deriving from local keypoints has recently appeared promising for object and scene classification. Whether BoF can naturally survive the challenges such as reliability and scalability of visual classification, nevertheless, remains uncertain due to various implementation choices. In this paper, we evaluate various factors which govern the performance of BoF. The factors include the choices of detector, kernel, vocabulary size and weighting scheme. We offer some practical insights in how to optimize the performance by choosing good keypoint detector and kernel. For the weighting scheme, we propose a novel soft-weighting method to assess the significance of a visual word …
Maximizing Broadcast And Multicast Traffic Load Through Link-Rate Diversity In Wireless Mesh Networks, Chun Tung Chou, Bao Hua Liu, Archan Misra
Maximizing Broadcast And Multicast Traffic Load Through Link-Rate Diversity In Wireless Mesh Networks, Chun Tung Chou, Bao Hua Liu, Archan Misra
Research Collection School Of Computing and Information Systems
This paper studies some of the fundamental challenges and opportunities associated with the network-layer broadcast and multicast in a multihop multirate wireless mesh network (WMN). In particular, we focus on exploiting the ability of nodes to perform link-layer broadcasts at different rates (with correspondingly different coverage areas). We first show how, in the broadcast wireless medium, the available capacity at a mesh node for a multicast transmission is not just a function of the aggregate pre-existing traffic load of other interfering nodes, but intricately coupled to the actual (sender, receiver) set and the link-layer rate of each individual transmission. We …
Social Network Structures In Open Source Software Development Teams, Y. Long, Keng Siau
Social Network Structures In Open Source Software Development Teams, Y. Long, Keng Siau
Research Collection School Of Computing and Information Systems
Drawing on social network theories and previous studies, this research examines the dynamics of social network structures in open source software (OSS) teams. Three projects were selected from SourceForge.net in terms of their similarities as well as their differences. Monthly data were extracted from the bug tracking systems in order to achieve a longitudinal view of the interaction pattern of each project. Social network analysis was used to generate the indices of social structure. The finding suggests that the interaction pattern of OSS projects evolves from a single hub at the beginning to a corel periphery model as the projects …
Mining Generalized Associations Of Semantic Relations From Textual Web Content, Tao Jiang, Ah-Hwee Tan, We Wang
Mining Generalized Associations Of Semantic Relations From Textual Web Content, Tao Jiang, Ah-Hwee Tan, We Wang
Research Collection School Of Computing and Information Systems
Traditional text mining techniques transform free text into flat bags of words representation, which does not preserve sufficient semantics for the purpose of knowledge discovery. In this paper, we present a two-step procedure to mine generalized associations of semantic relations conveyed by the textual content of Web documents. First, RDF (resource description framework) metadata representing semantic relations are extracted from raw text using a myriad of natural language processing techniques. The relation extraction process also creates a term taxonomy in the form of a sense hierarchy inferred from WordNet. Then, a novel generalized association pattern mining algorithm (GP-Close) is applied …