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Articles 811 - 840 of 1060
Full-Text Articles in Numerical Analysis and Scientific Computing
On Efficient Mutual Nearest Neighbor Query Processing In Spatial Databases, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li
On Efficient Mutual Nearest Neighbor Query Processing In Spatial Databases, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li
Research Collection School Of Computing and Information Systems
This paper studies a new form of nearest neighbor queries in spatial databases, namely, mutual nearest neighbour (MNN) search. Given a set D of objects and a query object q, an MNN query returns from D, the set of objects that are among the k1 (≥ 1) nearest neighbors (NNs) of q; meanwhile, have q as one of their k2(≥ 1) NNs. Although MNN queries are useful in many applications involving decision making, data mining, and pattern recognition, it cannot be efficiently handled by existing spatial query processing approaches. In this paper, we present …
Optimal-Location-Selection Query Processing In Spatial Databases, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li
Optimal-Location-Selection Query Processing In Spatial Databases, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li
Research Collection School Of Computing and Information Systems
This paper introduces and solves a novel type of spatial queries, namely, Optimal-Location-Selection (OLS) search, which has many applications in real life. Given a data object set D_A, a target object set D_B, a spatial region R, and a critical distance d_c in a multidimensional space, an OLS query retrieves those target objects in D_B that are outside R but have maximal optimality. Here, the optimality of a target object b \in D_B located outside R is defined as the number of the data objects from D_A that are inside R and meanwhile have their distances to b not exceeding …
Scalable Verification For Outsourced Dynamic Databases, Hwee Hwa Pang, Jilian Zhang, Kyriakos Mouratidis
Scalable Verification For Outsourced Dynamic Databases, Hwee Hwa Pang, Jilian Zhang, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
Query answers from servers operated by third parties need to be verified, as the third parties may not be trusted or their servers may be compromised. Most of the existing authentication methods construct validity proofs based on the Merkle hash tree (MHT). The MHT, however, imposes severe concurrency constraints that slow down data updates. We introduce a protocol, built upon signature aggregation, for checking the authenticity, completeness and freshness of query answers. The protocol offers the important property of allowing new data to be disseminated immediately, while ensuring that outdated values beyond a pre-set age can be detected. We also …
Spatial Cloaking Revisited: Distinguishing Information Leakage From Anonymity, Kar Way Tan, Yimin Lin, Kyriakos Mouratidis
Spatial Cloaking Revisited: Distinguishing Information Leakage From Anonymity, Kar Way Tan, Yimin Lin, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
Location-based services (LBS) are receiving increasing popularity as they provide convenience to mobile users with on-demand information. The use of these services, however, poses privacy issues as the user locations and queries are exposed to untrusted LBSs. Spatial cloaking techniques provide privacy in the form of k-anonymity; i.e., they guarantee that the (location of the) querying user u is indistinguishable from at least k-1 others, where k is a parameter specified by u at query time. To achieve this, they form a group of k users, including u, and forward their minimum bounding rectangle (termed anonymzing spatial region, ASR) to …
Compositemap: A Novel Framework For Music Similarity Measure, Bingjun Zhang, Jialie Shen, Qiaoliang Xiang, Ye Wang
Compositemap: A Novel Framework For Music Similarity Measure, Bingjun Zhang, Jialie Shen, Qiaoliang Xiang, Ye Wang
Research Collection School Of Computing and Information Systems
With the continuing advances in data storage and communication technology, there has been an explosive growth of music information from different application domains. As an effective technique for organizing, browsing, and searching large data collections, music information retrieval is attracting more and more attention. How to measure and model the similarity between different music items is one of the most fundamental yet challenging research problems. In this paper, we introduce a novel framework based on a multimodal and adaptive similarity measure for various applications. Distinguished from previous approaches, our system can effectively combine music properties from different aspects into a …
The Wisdom Of The Few: A Collaborative Filtering Approach Based On Expert Opinions From The Web, Xavier Amatriain, Neal Lathia, Josep M. Pujol, Haewoon Kwak, Nuria. Oliver
The Wisdom Of The Few: A Collaborative Filtering Approach Based On Expert Opinions From The Web, Xavier Amatriain, Neal Lathia, Josep M. Pujol, Haewoon Kwak, Nuria. Oliver
Research Collection School Of Computing and Information Systems
Nearest-neighbor collaborative filtering provides a successful means of generating recommendations for web users. However, this approach suffers from several shortcomings, including data sparsity and noise, the cold-start problem, and scalability. In this work, we present a novel method for recommending items to users based on expert opinions. Our method is a variation of traditional collaborative filtering: rather than applying a nearest neighbor algorithm to the user-rating data, predictions are computed using a set of expert neighbors from an independent dataset, whose opinions are weighted according to their similarity to the user. This method promises to address some of the weaknesses …
Continuous Obstructed Nearest Neighbor Queries In Spatial Databases, Yunjun Gao, Baihua Zheng
Continuous Obstructed Nearest Neighbor Queries In Spatial Databases, Yunjun Gao, Baihua Zheng
Research Collection School Of Computing and Information Systems
In this paper, we study a novel form of continuous nearest neighbor queries in the presence of obstacles, namely continuous obstructed nearest neighbor (CONN) search. It considers the impact of obstacles on the distance between objects, which is ignored by most of spatial queries. Given a data set P, an obstacle set O, and a query line segment q in a two-dimensional space, a CONN query retrieves the nearest neighbor of each point on q according to the obstructed distance, i.e., the shortest path between them without crossing any obstacle. We formulate CONN search, analyze its unique properties, and develop …
On Mining Rating Dependencies In Online Collaborative Rating Networks, Hady W. Lauw, Ee Peng Lim, Ke Wang
On Mining Rating Dependencies In Online Collaborative Rating Networks, Hady W. Lauw, Ee Peng Lim, Ke Wang
Research Collection School Of Computing and Information Systems
The trend of social information processing sees e-commerce and social web applications increasingly relying on user-generated content, such as rating, to determine the quality of objects and to generate recommendations for users. In a rating system, a set of reviewers assign to a set of objects different types of scores based on specific evaluation criteria. In this paper, we seek to determine, for each reviewer and for each object, the dependency between scores on any two given criteria. A reviewer is said to have high dependency between a pair of criteria when his or her rating scores on objects based …
Predicting Outcome For Collaborative Featured Article Nomination In Wikipedia, Meiqun Hu, Ee Peng Lim, Ramayya Krishnan
Predicting Outcome For Collaborative Featured Article Nomination In Wikipedia, Meiqun Hu, Ee Peng Lim, Ramayya Krishnan
Research Collection School Of Computing and Information Systems
In Wikipedia, good articles are wanted. While Wikipedia relies on collaborative effort from online volunteers for quality checking, the process of selecting top quality articles is time consuming. At present, the duty of decision making is shouldered by only a couple of administrators. Aiming to assist in the quality checking cycles so as to cope with the exponential growth of online contributions to Wikipedia, this work studies the task of predicting the outcome of featured article (FA) nominations. We analyze FA candidate (FAC) sessions collected over a period of 3.5 years, and examine the extent to which consensus has been …
A Novel Framework For Efficient Automated Singer Identification In Large Music Databases, Jialie Shen, John Shepherd, Bin Cui, Kian-Lee Tan
A Novel Framework For Efficient Automated Singer Identification In Large Music Databases, Jialie Shen, John Shepherd, Bin Cui, Kian-Lee Tan
Research Collection School Of Computing and Information Systems
Over the past decade, there has been explosive growth in the availability of multimedia data, particularly image, video, and music. Because of this, content-based music retrieval has attracted attention from the multimedia database and information retrieval communities. Content-based music retrieval requires us to be able to automatically identify particular characteristics of music data. One such characteristic, useful in a range of applications, is the identification of the singer in a musical piece. Unfortunately, existing approaches to this problem suffer from either low accuracy or poor scalability. In this article, we propose a novel scheme, called Hybrid Singer Identifier (HSI), for …
An Incremental Threshold Method For Continuous Text Search Queries, Kyriakos Mouratidis, Hwee Hwa Pang
An Incremental Threshold Method For Continuous Text Search Queries, Kyriakos Mouratidis, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
A text filtering system monitors a stream of incoming documents, to identify those that match the interest profiles of its users. The user interests are registered at a server as continuous text search queries. The server constantly maintains 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 …
Describing Fuzzy Sets Using A New Concept: Fuzzify Functor, Kexin Wei, Zhaoxia Wang, Quan Wang
Describing Fuzzy Sets Using A New Concept: Fuzzify Functor, Kexin Wei, Zhaoxia Wang, Quan Wang
Research Collection School Of Computing and Information Systems
This paper proposed a fuzzify functor as an extension of the concept of fuzzy sets. The fuzzify functor and the first-order operated fuzzy set are defined. From the theory analysis, it can be observed that when the fuzzify functor acts on a simple crisp set, we get the first order fuzzy set or type-1 fuzzy set. By operating the fuzzify functor on fuzzy sets, we get the higher order fuzzy sets or higher type fuzzy sets and their membership functions. Using the fuzzify functor we can exactly describe the type-1 fuzzy sets, type-2 fuzzy sets and higher type or higher …
Opaque: Protecting Path Privacy In Directions Search, Ken C. K. Lee, Wang-Chien Lee, Hong Va Leong, Baihua Zheng
Opaque: Protecting Path Privacy In Directions Search, Ken C. K. Lee, Wang-Chien Lee, Hong Va Leong, Baihua Zheng
Research Collection School Of Computing and Information Systems
Directions search returns the shortest path from a source to a destination on a road network. However, the search interests of users may be exposed to the service providers, thus raising privacy concerns. For instance, a path query that finds a path from a resident address to a clinic may lead to a deduction about "who is related to what disease". To protect user privacy from accessing directions search services, we introduce the OPAQUE system, which consists of two major components: (1) an obfuscator that formulates obfuscated path queries by mixing true and fake sources/destinations; and (2) an obfuscated path …
Fast Object Search On Road Networks, Ken C. K. Lee, Wang-Chien Lee, Baihua Zheng
Fast Object Search On Road Networks, Ken C. K. Lee, Wang-Chien Lee, Baihua Zheng
Research Collection School Of Computing and Information Systems
In this paper, we present ROAD, a general framework to evaluate Location-Dependent Spatial Queries (LDSQ)s that searches for spatial objects on road networks. By exploiting search space pruning technique and providing a dynamic object mapping mechanism, ROAD is very efficient and flexible for various types of queries, namely, range search and nearest neighbor search, on objects over large-scale networks. ROAD is named after its two components, namely, Route Overlay and Association Directory, designed to address the network traversal and object access aspects of the framework. In ROAD, a large road network is organized as a hierarchy of interconnected regional sub-networks …
Continuous Visible Nearest Neighbour Queries, Yunjun Gao, Baihua Zheng, Wang-Chien Lee, Gencai Chen
Continuous Visible Nearest Neighbour Queries, Yunjun Gao, Baihua Zheng, Wang-Chien Lee, Gencai Chen
Research Collection School Of Computing and Information Systems
In this paper, we identify and solve a new type of spatial queries, called continuous visible nearest neighbor (CVNN) search. Given a data set P, an obstacle set O, and a query line segment q, a CVNN query returns a set of (p, R) tuples such that p ? P is the nearest neighbor (NN) to every point r along the interval R ? q as well as p is visible to r. Note that p may be NULL, meaning that all points in P are invisible to all points in R, due to the obstruction of some obstacles in …
Stochastic Modeling Western Paintings For Effective Classification, Jialie Shen
Stochastic Modeling Western Paintings For Effective Classification, Jialie Shen
Research Collection School Of Computing and Information Systems
As one of the most important cultural heritages, classical western paintings have always played a special role in human live and been applied for many different purposes. While image classification is the subject of a plethora of related publications, relatively little attention has been paid to automatic categorization of western classical paintings which could be a key technique of modern digital library, museums and art galleries. This paper studies automatic classification on large western painting image collection. We propose a novel framework to support automatic classification on large western painting image collections. With this framework, multiple visual features can be …
Web Social Mining, Hady W. Lauw, Ee Peng Lim
Web Social Mining, Hady W. Lauw, Ee Peng Lim
Research Collection School Of Computing and Information Systems
No abstract provided.
Tuning On-Air Signatures For Balancing Performance And Confidentiality, Baihua Zheng, Wang-Chien Lee, Peng Liu, Dik Lun Lee, Xuhua Ding
Tuning On-Air Signatures For Balancing Performance And Confidentiality, Baihua Zheng, Wang-Chien Lee, Peng Liu, Dik Lun Lee, Xuhua Ding
Research Collection School Of Computing and Information Systems
In this paper, we investigate the trade off between performance and confidentiality in signature-based air indexing schemes for wireless data broadcast. Two metrics, namely, false drop probability and false guess probability, are defined to quantify the filtering efficiency and confidentiality loss of a signature scheme. Our analysis reveals that false drop probability and false guess probability share a similar trend as the tuning parameters of a signature scheme change and it is impossible to achieve a low false drop probability and a high false guess probability simultaneously. In order to balance the performance and confidentiality, we perform an analysis to …
Computing Medoids In Large Spatial Datasets, Kyriakos Mouratidis, Dimitris Papadias, Spiros Papadimitriou
Computing Medoids In Large Spatial Datasets, Kyriakos Mouratidis, Dimitris Papadias, Spiros Papadimitriou
Research Collection School Of Computing and Information Systems
In this chapter, we consider a class of queries that arise in spatial decision making and resource allocation applications. Assume that a company wants to open a number of warehouses in a city. Let P be the set of residential blocks in the city. P represents customer locations to be potentially served by the company. At the same time, P also comprises the candidate warehouse locations because the warehouses themselves must be opened in some residential blocks.
Efficient Valid Scope Computation For Location-Dependent Spatial Queries In Mobile And Wireless Environments, Ken C. K. Lee, Wang-Chien Lee, Hong Va Leong, Brandon Unger, Baihua Zheng
Efficient Valid Scope Computation For Location-Dependent Spatial Queries In Mobile And Wireless Environments, Ken C. K. Lee, Wang-Chien Lee, Hong Va Leong, Brandon Unger, Baihua Zheng
Research Collection School Of Computing and Information Systems
In mobile and wireless environments, mobile clients can access information with respect to their locations by submitting Location-Dependent Spatial Queries (LDSQs) to Location-Based Service (LBS) servers. Owing to scarce wireless channel bandwidth and limited client battery life, frequent LDSQ submission from clients must be avoided. Observing that LDSQs issued from similar client positions would normally return the same results, we explore the idea of valid scope, that represents a spatial area in which a set of LDSQs will retrieve exactly the same query results. With a valid scope derived and an LDSQ result cached at the client side, a client …
Quality-Aware Collaborative Question Answering: Methods And Evaluation, Maggy Anastasia Suryanto, Ee Peng Lim, Aixin Sun, Roger Hsiang-Li Chiang
Quality-Aware Collaborative Question Answering: Methods And Evaluation, Maggy Anastasia Suryanto, Ee Peng Lim, Aixin Sun, Roger Hsiang-Li Chiang
Research Collection School Of Computing and Information Systems
Community Question Answering (QA) portals contain questions and answers contributed by hundreds of millions of users. These databases of questions and answers are of great value if they can be used directly to answer questions from any user. In this research, we address this collaborative QA task by drawing knowledge from the crowds in community QA portals such as Yahoo! Answers. Despite their popularity, it is well known that answers in community QA portals have unequal quality. We therefore propose a quality-aware framework to design methods that select answers from a community QA portal considering answer quality in addition to …
Localized Monitoring Of Knn Queries In Wireless Sensor Networks, Yuxia Yao, Xueyan Tang, Ee Peng Lim
Localized Monitoring Of Knn Queries In Wireless Sensor Networks, Yuxia Yao, Xueyan Tang, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Wireless sensor networks have been widely used in civilian and military applications. Primarily designed for monitoring purposes, many sensor applications require continuous collection and processing of sensed data. Due to the limited power supply for sensor nodes, energy efficiency is a major performance concern in query processing. In this paper, we focus on continuous kNN query processing in object tracking sensor networks. We propose a localized scheme to monitor nearest neighbors to a query point. The key idea is to establish a monitoring area for each query so that only the updates relevant to the query are collected. The monitoring …
Partially Materialized Digest Scheme: An Efficient Verification Method For Outsourced Databases, Kyriakos Mouratidis, Dimitris Sacharidis, Hwee Hwa Pang
Partially Materialized Digest Scheme: An Efficient Verification Method For Outsourced Databases, Kyriakos Mouratidis, Dimitris Sacharidis, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
In the outsourced database model, a data owner publishes her database through a third-party server; i.e., the server hosts the data and answers user queries on behalf of the owner. Since the server may not be trusted, or may be compromised, users need a means to verify that answers received are both authentic and complete, i.e., that the returned data have not been tampered with, and that no qualifying results have been omitted. We propose a result verification approach for one-dimensional queries, called Partially Materialized Digest scheme (PMD), that applies to both static and dynamic databases. PMD uses separate indexes …
Quc-Tree: Integrating Query Context Information For Efficient Music Retrieval, Jialie Shen, Dacheng Tao, Xuelong Li
Quc-Tree: Integrating Query Context Information For Efficient Music Retrieval, Jialie Shen, Dacheng Tao, Xuelong Li
Research Collection School Of Computing and Information Systems
In this paper, we introduce a novel indexing scheme-query context tree (QUC-tree) to facilitate efficient query sensitive music search under different query contexts. Distinguished from the previous approaches, QUC-tree is a balanced multiway tree structure, where each level represents the data space at different dimensionality. Before the tree structure construction, principle component analysis (PCA) is applied for data analysis and transforming the raw composite features into a new feature space sorted by the importance of acoustic features. The PCA transformed data and reduced dimensions in the upper levels can alleviate suffering from dimensionality curse. To accurately mimic human perception, an …
Dynamic Web Service Selection For Reliable Web Service Composition, San-Yih Hwang, Ee Peng Lim, Chien-Hsiang Lee, Cheng-Hung Chen
Dynamic Web Service Selection For Reliable Web Service Composition, San-Yih Hwang, Ee Peng Lim, Chien-Hsiang Lee, Cheng-Hung Chen
Research Collection School Of Computing and Information Systems
This paper studies the dynamic web service selection problem in a failure-prone environment, which aims to determine a subset of Web services to be invoked at run-time so as to successfully orchestrate a composite web service. We observe that both the composite and constituent web services often constrain the sequences of invoking their operations and therefore propose to use finite state machine to model the permitted invocation sequences of Web service operations. We assign each state of execution an aggregated reliability to measure the probability that the given state will lead to successful execution in the context where each web …
Text Mining In Radiology Reports, Tianxia Gong, Chew Lim Tan, Tze-Yun Leong, Cheng Kiang Lee, Boon Chuan Pang, C. C. Tchoyoson Lim, Qi Tian, Suisheng Tang, Zhuo Zhang
Text Mining In Radiology Reports, Tianxia Gong, Chew Lim Tan, Tze-Yun Leong, Cheng Kiang Lee, Boon Chuan Pang, C. C. Tchoyoson Lim, Qi Tian, Suisheng Tang, Zhuo Zhang
Research Collection School Of Computing and Information Systems
Medical text mining has gained increasing interest in recent years. Radiology reports contain rich information describing radiologist's observations on the patient's medical conditions in the associated medical images. However as most reports are in free text format, the valuable information contained in those reports cannot be easily accessed and used, unless proper text mining has been applied. In this paper we propose a text mining system to extract and use the information in radiology reports. The system consists of three main modules: a medical finding extractor a report and image retriever and a text-assisted image feature extractor In evaluation, the …
A Fast Pruned‐Extreme Learning Machine For Classification Problem, Hai-Jun Rong, Yew-Soon Ong, Ah-Hwee Tan, Zexuan Zhu
A Fast Pruned‐Extreme Learning Machine For Classification Problem, Hai-Jun Rong, Yew-Soon Ong, Ah-Hwee Tan, Zexuan Zhu
Research Collection School Of Computing and Information Systems
Extreme learning machine (ELM) represents one of the recent successful approaches in machine learning, particularly for performing pattern classification. One key strength of ELM is the significantly low computational time required for training new classifiers since the weights of the hidden and output nodes are randomly chosen and analytically determined, respectively. In this paper, we address the architectural design of the ELM classifier network, since too few/many hidden nodes employed would lead to underfitting/overfitting issues in pattern classification. In particular, we describe the proposed pruned-ELM (P-ELM) algorithm as a systematic and automated approach for designing ELM classifier network. P-ELM uses …
Explaining Inferences In Bayesian Networks, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang
Explaining Inferences In Bayesian Networks, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
While Bayesian network (BN) can achieve accurate predictions even with erroneous or incomplete evidence, explaining the inferences remains a challenge. Existing approaches fall short because they do not exploit variable interactions and cannot account for compensations during inferences. This paper proposes the Explaining BN Inferences (EBI) procedure for explaining how variables interact to reach conclusions. EBI explains the value of a target node in terms of the influential nodes in the target's Markov blanket under specific contexts, where the Markov nodes include the target's parents, children, and the children's other parents. Working back from the target node, EBI shows the …
Bias And Controversy In Evaluation Systems, Hady Wirawan Lauw, Ee Peng Lim, Ke Wang
Bias And Controversy In Evaluation Systems, Hady Wirawan Lauw, Ee Peng Lim, Ke Wang
Research Collection School Of Computing and Information Systems
Evaluation is prevalent in real life. With the advent of Web 2.0, online evaluation has become an important feature in many applications that involve information (e.g., video, photo, and audio) sharing and social networking (e.g., blogging). In these evaluation settings, a set of reviewers assign scores to a set of objects. As part of the evaluation analysis, we want to obtain fair reviews for all the given objects. However, the reality is that reviewers may deviate in their scores assigned to the same object, due to the potential bias of reviewers or controversy of objects. The statistical approach of averaging …
Modality Mixture Projections For Semantic Video Event Detection, Jialie Shen, Dacheng Tao, Xuelong Li
Modality Mixture Projections For Semantic Video Event Detection, Jialie Shen, Dacheng Tao, Xuelong Li
Research Collection School Of Computing and Information Systems
Event detection is one of the most fundamental components for various kinds of domain applications of video information system. In recent years, it has gained a considerable interest of practitioners and academics from different areas. While detecting video event has been the subject of extensive research efforts recently, much less existing approach has considered multimodal information and related efficiency issues. In this paper, we use a subspace selection technique to achieve fast and accurate video event detection using a subspace selection technique. The approach is capable of discriminating different classes and preserving the intramodal geometry of samples within an identical …