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Articles 451 - 480 of 1355
Full-Text Articles in Computer Sciences
Discovering And Exploiting Causal Dependencies For Robust Mobile Context-Aware Recommenders, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang
Discovering And Exploiting Causal Dependencies For Robust Mobile Context-Aware Recommenders, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
Acquisition of context poses unique challenges to mobile context-aware recommender systems. The limited resources in these systems make minimizing their context acquisition a practical need, and the uncertainty in the mobile environment makes missing and erroneous context inputs a major concern. In this paper, we propose an approach based on Bayesian networks (BNs) for building recommender systems that minimize context acquisition. Our learning approach iteratively trims the BN-based context model until it contains only the minimal set of context parameters that are important to a user. In addition, we show that a two-tiered context model can effectively capture the causal …
Efficient Near-Duplicate Keyframe Retrieval With Visual Language Models, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo
Efficient Near-Duplicate Keyframe Retrieval With Visual Language Models, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Near-duplicate keyframe retrieval is a critical task for video similarity measure, video threading and tracking. In this paper, instead of using expensive point-to-point matching on keypoints, we investigate the visual language models built on visual keywords to speed up the near-duplicate keyframe retrieval. The main idea is to estimate a visual language model on visual keywords for each keyframe and compare keyframes by the likelihood of their visual language models. Experiments on a subset of TRECVID-2004 video corpus show that visual language models built on visual keywords demonstrate promising performance for near-duplicate keyframe retrieval, which greatly speed up the retrieval …
An Examination Of Online Product Comparison Service: Fit Between Product Type And Disposition Style, Fiona Fui-Hoon Nah, W. Hong, L. Chen, H. Lee
An Examination Of Online Product Comparison Service: Fit Between Product Type And Disposition Style, Fiona Fui-Hoon Nah, W. Hong, L. Chen, H. Lee
Research Collection School Of Computing and Information Systems
Horizontal and vertical disposition styles are two main formats used in product comparison service on e-commerce websites. In this research, we hypothesize that there is a fit between product type (‘think’ vs. ‘feel’ product) and disposition style (horizontal vs. vertical style), where horizontal disposition style is more appropriate for ‘feel’ products and vertical disposition style is a better fit for ‘think’ products. An experiment will be carried out to test the hypotheses.
Appraisal - Who Needs It?, M. Thulasidas
Appraisal - Who Needs It?, M. Thulasidas
Research Collection School Of Computing and Information Systems
WE GO through this ordeal every year when our boss- es appraise our performance. Our career progression, bonus and salary depend on it. So, we spend sleepless nights agonising over it.
Entrepreneurial Opportunities And Market Analysis Of The Information Technology And Software Development Sector Of Pakistan, Toshio Fujita, Hassan Tajuddin
Entrepreneurial Opportunities And Market Analysis Of The Information Technology And Software Development Sector Of Pakistan, Toshio Fujita, Hassan Tajuddin
Business Review
This study investigates the Information Technology and the Software Development sector of Pakistan. It discusses the reasons for the lack of trust in Pakistani IT companies and different problems faced by an entrepreneur starting an IT company in Pakistan. The data was analyzed by qualitative content analysis. The findings are discussed with reference to previous research, and implications for entrepreneurial setups are noted.
A Dynamic Attribute-Based Load Shedding Scheme For Data Stream Management Systems, Amit Ahuja, Yiu-Kai D. Ng
A Dynamic Attribute-Based Load Shedding Scheme For Data Stream Management Systems, Amit Ahuja, Yiu-Kai D. Ng
Faculty Publications
A data stream being transmitted over a network channel with capacity less than the data transmission rate of the data stream causes sequential network problems. In this paper, we present a new approach for shedding less-informative attribute data from a data stream to maintain a data transmission rate less than the network channel capacity. A scheme for shedding attributes and their data, instead of tuples, becomes imperative in data stream load shedding, since shedding a complete tuple would lead to shedding informative attribute data along with less-informative attribute data in the tuple. Our load shedding approach handles intra-stream, as well …
Genetic Evolution Of Hierarchical Behavior Structures, Brian G. Woolley, Gilbert L. Peterson
Genetic Evolution Of Hierarchical Behavior Structures, Brian G. Woolley, Gilbert L. Peterson
Faculty Publications
The development of coherent and dynamic behaviors for mobile robots is an exceedingly complex endeavor ruled by task objectives, environmental dynamics and the interactions within the behavior structure. This paper discusses the use of genetic programming techniques and the unified behavior framework to develop effective control hierarchies using interchangeable behaviors and arbitration components. Given the number of possible variations provided by the framework, evolutionary programming is used to evolve the overall behavior design. Competitive evolution of the behavior population incrementally develops feasible solutions for the domain through competitive ranking. By developing and implementing many simple behaviors independently and then evolving …
An Artificial Immune System-Inspired Multiobjective Evolutionary Algorithm With Application To The Detection Of Distributed Computer Network Intrusions, Charles R. Haag, Gary B. Lamont, Paul D. L. Williams, Gilbert L. Peterson
An Artificial Immune System-Inspired Multiobjective Evolutionary Algorithm With Application To The Detection Of Distributed Computer Network Intrusions, Charles R. Haag, Gary B. Lamont, Paul D. L. Williams, Gilbert L. Peterson
Faculty Publications
Today's signature-based intrusion detection systems are reactive in nature and storage-limited. Their operation depends upon catching an instance of an intrusion or virus and encoding it into a signature that is stored in its anomaly database, providing a window of vulnerability to computer systems during this time. Further, the maximum size of an Internet Protocol-based message requires the database to be huge in order to maintain possible signature combinations. In order to tighten this response cycle within storage constraints, this paper presents an innovative Artificial Immune System-inspired Multiobjective Evolutionary Algorithm. This distributed intrusion detection system (IDS) is intended to measure …
Investigating Real-Time Sonar Performance Predictions Using Beowulf Clustering, Charles Lane Cartledge
Investigating Real-Time Sonar Performance Predictions Using Beowulf Clustering, Charles Lane Cartledge
Computer Science Theses & Dissertations
Predicting sonar performance, critical to using any sonar to its maximum effectiveness, is computationally intensive and typically the results are based on data from the past and may not be applicable to the current water conditions. This paper discusses how Beowulf clustering techniques were investigated and applied to achieve real-time sonar performance prediction capabilities based on commercially off the shelf (COTS) hardware and software. A sonar system measures ambient noise in real-time. Based on the active sonar range scale, new ambient measurements can be available every 1 to 24 seconds. Traditional sonar performance prediction techniques operated serially and often took …
Improving Memory-Based Collaborative Filtering Using A Factor-Based Approach, Zhenxue Zhang, Dongsong Zhang, Zhiling Guo
Improving Memory-Based Collaborative Filtering Using A Factor-Based Approach, Zhenxue Zhang, Dongsong Zhang, Zhiling Guo
Research Collection School Of Computing and Information Systems
Collaborative Filtering (CF) systems generate recommendations for a user by aggregating item ratings of other like-minded users. The memory-based approach is a common technique used in CF. This approach first uses statistical methods such as Pearson’s Correlation Coefficient to measure user similarities based on their previous ratings on different items. Users will then be grouped into different neighborhood depending on the calculated similarities. Finally, the system will generate predictions on how a user would rate a specific item by aggregating ratings on the item cast by the identified neighbors of his/her. However, current memory-based CF method only measures user similarities …
Is Interpersonal Trust A Necessary Condition For Organisational Learning?, Siu Loon Hoe
Is Interpersonal Trust A Necessary Condition For Organisational Learning?, Siu Loon Hoe
Research Collection School Of Computing and Information Systems
The organisational behaviour and management literature has devoted a lot attention on various factors affecting organisational learning. While there has been much work done to examine trust in promoting organisational learning, there is a lack of consensus on the specific type of trust involved. The purpose of this paper is to highlight the importance of interpersonal trust in promoting organisational learning and propose a research agenda to test the extent of interpersonal trust on organisational learning. This paper contributes to the existing organisational learning literature by specifying a specific form of trust, interpersonal trust, which promotes organisational learning and proposing …
Learning Causal Models For Noisy Biological Data Mining: An Application To Ovarian Cancer Detection, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang
Learning Causal Models For Noisy Biological Data Mining: An Application To Ovarian Cancer Detection, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
Undetected errors in the expression measurements from highthroughput DNA microarrays and protein spectroscopy could seriously affect the diagnostic reliability in disease detection. In addition to a high resilience against such errors, diagnostic models need to be more comprehensible so that a deeper understanding of the causal interactions among biological entities like genes and proteins may be possible. In this paper, we introduce a robust knowledge discovery approach that addresses these challenges. First, the causal interactions among the genes and proteins in the noisy expression data are discovered automatically through Bayesian network learning. Then, the diagnosis of a disease based on …
Generating Job Schedules For Vessel Operations In A Container Terminal, Thin Yin Leong, Hoong Chuin Lau
Generating Job Schedules For Vessel Operations In A Container Terminal, Thin Yin Leong, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
No abstract provided.
Continuous Monitoring Of Top-K Queries Over Sliding Windows, Kyriakos Mouratidis, Spiridon Bakiras, Dimitris Papadias
Continuous Monitoring Of Top-K Queries Over Sliding Windows, Kyriakos Mouratidis, Spiridon Bakiras, Dimitris Papadias
Research Collection School Of Computing and Information Systems
Given a dataset P and a preference function f, a top-k query retrieves the k tuples in P with the highest scores according to f. Even though the problem is well-studied in conventional databases, the existing methods are inapplicable to highly dynamic environments involving numerous long-running queries. This paper studies continuous monitoring of top-k queries over a fixed-size window W of the most recent data. The window size can be expressed either in terms of the number of active tuples or time units. We propose a general methodology for top-k monitoring that restricts processing to the sub-domains of the workspace …
The Business Model Of "Software-As-A-Service", Dan Ma
The Business Model Of "Software-As-A-Service", Dan Ma
Research Collection School Of Computing and Information Systems
The emergence of the software-as-a-service (SaaS) business model has attracted great attentions from both researchers and practitioners. SaaS vendors deliver on-demand information processing services to users, and thus offer computing utility rather than the standalone software itself. In this work, the author propose an analytical model to study the competition between the SaaS and the traditional COTS (commercial off-the-shelf) solutions for software applications. The author show that when software applications become open, modulated, and standardized, the SaaS business model will take a significant market share. In addition, under certain market conditions, offering users an easy exit option through the software …
Near-Duplicate Keyframe Retrieval With Visual Keywords And Semantic Context, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo
Near-Duplicate Keyframe Retrieval With Visual Keywords And Semantic Context, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Near-duplicate keyframes (NDK) play a unique role in large-scale video search, news topic detection and tracking. In this paper, we propose a novel NDK retrieval approach by exploring both visual and textual cues from the visual vocabulary and semantic context respectively. The vocabulary, which provides entries for visual keywords, is formed by the clustering of local keypoints. The semantic context is inferred from the speech transcript surrounding a keyframe. We experiment the usefulness of visual keywords and semantic context, separately and jointly, using cosine similarity and language models. By linearly fusing both modalities, performance improvement is reported compared with the …
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 …
Cross-Lingual Query Suggestion Using Query Logs Of Different Languages, Wei Gao, Cheng Niu, Jian-Yun Nie, Ming Zhou, Jian Hu, Kam-Fai Wong, Hsiao-Wuen Hon
Cross-Lingual Query Suggestion Using Query Logs Of Different Languages, Wei Gao, Cheng Niu, Jian-Yun Nie, Ming Zhou, Jian Hu, Kam-Fai Wong, Hsiao-Wuen Hon
Research Collection School Of Computing and Information Systems
Query suggestion aims to suggest relevant queries for a given query, which help users better specify their information needs. Previously, the suggested terms are mostly in the same language of the input query. In this paper, we extend it to cross-lingual query suggestion (CLQS): for a query in one language, we suggest similar or relevant queries in other languages. This is very important to scenarios of cross-language information retrieval (CLIR) and cross-lingual keyword bidding for search engine advertisement. Instead of relying on existing query translation technologies for CLQS, we present an effective means to map the input query of one …
Continuous Medoid Queries Over Moving Objects, Stavros Papadopoulos, Dimitris Sacharidis, Kyriakos Mouratidis
Continuous Medoid Queries Over Moving Objects, Stavros Papadopoulos, Dimitris Sacharidis, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
In the k-medoid problem, given a dataset P, we are asked to choose kpoints in P as the medoids. The optimal medoid set minimizes the average Euclidean distance between the points in P and their closest medoid. Finding the optimal k medoids is NP hard, and existing algorithms aim at approximate answers, i.e., they compute medoids that achieve a small, yet not minimal, average distance. Similarly in this paper, we also aim at approximate solutions. We consider, however, the continuous version of the problem, where the points in P move and our task is to maintain the medoid set on-the-fly …
Analyzing Feature Trajectories For Event Detection, Qi He, Kuiyu Chang, Ee Peng Lim
Analyzing Feature Trajectories For Event Detection, Qi He, Kuiyu Chang, Ee Peng Lim
Research Collection School Of Computing and Information Systems
We consider the problem of analyzing word trajectories in both time and frequency domains, with the specific goal of identifying important and less-reported, periodic and aperiodic words. A set of words with identical trends can be grouped together to reconstruct an event in a completely un-supervised manner. The document frequency of each word across time is treated like a time series, where each element is the document frequency - inverse document frequency (DFIDF) score at one time point. In this paper, we 1) first applied spectral analysis to categorize features for different event characteristics: important and less-reported, periodic and aperiodic; …
Dynamic Routing Structure For An Rti Taking An Evolutionary Approach Towards Optimization, Matthew Ryan Davis
Dynamic Routing Structure For An Rti Taking An Evolutionary Approach Towards Optimization, Matthew Ryan Davis
Computational Modeling & Simulation Engineering Theses & Dissertations
The Runtime Infrastructure (RTI) is the common communication framework that High Level Architecture (HLA) simulations incorporate to exchange data. By abstracting the network communication layer from simulation, a common protocol for information exchange is achieved, allowing any RTI- based simulation to exchange data with any other. Such commonality can bring a limitation upon the network infrastructure, enforcing all federates to agree on the same communication policy. While this static network structure is not always the case, an optimal choice would be to adhere to the dynamic properties of a network. Static network configurations deny federates the ability to dynamically avoid …
A Security Assessment Of Trusted Platform Modules, Evan R. Sparks
A Security Assessment Of Trusted Platform Modules, Evan R. Sparks
Dartmouth College Undergraduate Theses
Trusted Platform Modules (TPMs) are becoming ubiquitous devices included in newly released personal computers. Broadly speaking, the aim of this technology is to provide a facility for authenticating the platform on which they are running: they are able to measure attest to the authenticity of a hardware and software configuration. Designed to be cheap, commodity devices which motherboard and processor vendors can include in their products with minimal marginal cost, these devices have a good theoretical design. Unfortunately, there exist several practical constraints on the effectiveness of TPMs and the architectures which employ them which leave them open to attack. …
Query Selectivity Estimation For Uncertain Database, Sarvjeet Singh, Chris Mayfield, Rahul Shah, Sunil Prabhakar, Susanne E. Hambrusch
Query Selectivity Estimation For Uncertain Database, Sarvjeet Singh, Chris Mayfield, Rahul Shah, Sunil Prabhakar, Susanne E. Hambrusch
Department of Computer Science Technical Reports
No abstract provided.
Database Support For Probabilistic Attributes And Tuples, Sarvjeet Singh, Chris Mayfield, Rahul Shah, Sunil Prabhakar, Susanne E. Hambrusch, Reynold Cheng
Database Support For Probabilistic Attributes And Tuples, Sarvjeet Singh, Chris Mayfield, Rahul Shah, Sunil Prabhakar, Susanne E. Hambrusch, Reynold Cheng
Department of Computer Science Technical Reports
No abstract provided.
Ensuring Correctness Over Untrusted Private Database, Sarvjeet Singh, Sunil Prabhakar
Ensuring Correctness Over Untrusted Private Database, Sarvjeet Singh, Sunil Prabhakar
Department of Computer Science Technical Reports
No abstract provided.
Relationship Web: Realizing The Memex Vision With The Help Of Semantic Web, Amit P. Sheth
Relationship Web: Realizing The Memex Vision With The Help Of Semantic Web, Amit P. Sheth
Kno.e.sis Publications
Relationship Web takes us from "which document" could have information I need to "what's in the resources" that gives me the insight and knowledge I need for decision making. Dr. Vannevar Bush outlined his vision for Memex in a 1945 Atlantic Monthly article [1]. Describing how the human brain navigates an information space in what he called trailblazing, Dr. Bush said, "It operates by association. With one item in its grasp, it snaps instantly to the next that is suggested by the association of thoughts, in accordance with some intricate web of trails carried by the cells of the brain." …
Conceptual Xml For Systems Analysis, Reema Al-Kamha
Conceptual Xml For Systems Analysis, Reema Al-Kamha
Theses and Dissertations
Because XML has become a new standard for data representation, there is a need for a simple conceptual model that works well with XML-based development. In this research we present a conceptual model for XML, called C-XML, which meets this new need of systems analysts who store their data using XML. We describe our implementation of an automatic conversion from XML Schema to C-XML that preserves information and constraints. With this conversion, we can view an XML Schema instance graphically at a higher level of abstraction. We also describe our implementation of an automatic conversion from C-XML to XML Schema. …