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Predicting Outcome For Collaborative Featured Article Nomination In Wikipedia, Meiqun Hu, Ee Peng Lim, Ramayya Krishnan May 2009

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 …


Sharing Hierarchical Mobile Multimedia Content Using The Mobitop System, Quang Minh Nguyen, Thi Nhu Quynh Kim, Dion Hoe-Lian Goh, Ee-Peng Lim, Yin-Leng Theng, Kalyani Chatterjea, Chew-Hung Chang, Aixin Sun, Khasfariyati Razikin May 2009

Sharing Hierarchical Mobile Multimedia Content Using The Mobitop System, Quang Minh Nguyen, Thi Nhu Quynh Kim, Dion Hoe-Lian Goh, Ee-Peng Lim, Yin-Leng Theng, Kalyani Chatterjea, Chew-Hung Chang, Aixin Sun, Khasfariyati Razikin

Research Collection School Of Computing and Information Systems

We introduce MobiTOP (Mobile Tagging of Objects and People), a map-based application which allows users to contribute and share geo-referenced multimedia annotations via mobile devices. An important feature of MobiTOP is that annotations are hierarchical, allowing annotations to be annotated to an arbitrary depth. MobiTOP's interface was designed using a participatory design methodology to ensure that the user interface meets the needs of potential users. In an evaluation, a group of student-teachers involved in a geographical field study were tasked to collaboratively identify rock formations using the MobiTOP system. The students who were in the field were guided by their …


A Self-Organizing Neural Network Architecture For Intentional Planning Agents, Budhitama Subagdja, Ah-Hwee Tan May 2009

A Self-Organizing Neural Network Architecture For Intentional Planning Agents, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

This paper presents a model of neural network embodiment of intentions and planning mechanisms for autonomous agents. The model bridges the dichotomy of symbolic and non-symbolic representation in developing agents. Some novel techniques are introduced that enables the neural network to process and manipulate sequential and hierarchical structures of information. It is suggested that by incorporating intentional agent model which relies on explicit symbolic description with self-organizing neural networks that are good at learning and recognizing patterns, the best from both sides can be exploited. This paper demonstrates that plans can be represented as weighted connections and reasoning processes can …


On Mining Rating Dependencies In Online Collaborative Rating Networks, Hady W. Lauw, Ee Peng Lim, Ke Wang May 2009

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 …


A Novel Framework For Efficient Automated Singer Identification In Large Music Databases, Jialie Shen, John Shepherd, Bin Cui, Kian-Lee Tan May 2009

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 …


Zeros And Ones, M. Thulasidas May 2009

Zeros And Ones, M. Thulasidas

Research Collection School Of Computing and Information Systems

Computers are notorious for their infuriatingly literal obedience. I am sure anyone who has ever worked with a computer has come across the lack of empathy on its part – it follows our instructions to the dot, yet ends up accomplishing something altogether different from what we intend. Let’s spare a thought for the way your glorified adding machine makes sense of things


Joint Ranking For Multilingual Web Search, Wei Gao, Cheng Niu, Ming Zhou, Kam-Fai Wong Apr 2009

Joint Ranking For Multilingual Web Search, Wei Gao, Cheng Niu, Ming Zhou, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Ranking for multilingual information retrieval (MLIR) is a task to rank documents of different languages solely based on their relevancy to the query regardless of query’s language. Existing approaches are focused on combining relevance scores of different retrieval settings, but do not learn the ranking function directly. We approach Web MLIR ranking within the learning-to-rank (L2R) framework. Besides adopting popular L2R algorithms to MLIR, a joint ranking model is created to exploit the correlations among documents, and induce the joint relevance probability for all the documents. Using this method, the relevant documents of one language can be leveraged to improve …


Exploring Hierarchically Organized Georeferenced Multimedia Annotations In The Mobitop System, Thi Nhu Quynh Kim, Khasfariyati Razikin, Dion Hoe-Lian Goh, Yin Leng Theng, Quang Minh Nguyen, Ee-Peng Lim, Aixin Sun, Chew Hung Chang, Kalyani Chatterjea Apr 2009

Exploring Hierarchically Organized Georeferenced Multimedia Annotations In The Mobitop System, Thi Nhu Quynh Kim, Khasfariyati Razikin, Dion Hoe-Lian Goh, Yin Leng Theng, Quang Minh Nguyen, Ee-Peng Lim, Aixin Sun, Chew Hung Chang, Kalyani Chatterjea

Research Collection School Of Computing and Information Systems

We introduce MobiTOP, a map-based interface for accessing hierarchically organized georeferenced annotations. Each annotation contains multimedia content associated with a location, and users are able to annotate existing annotations, in effect creating a hierarchy. MobiTOPs interface was designed using a participatory design methodology to ensure that the user interface meets the needs of potential users. A pilot study to compare the MobiTOP interface with a space-filling thumbnail (SFT) interface suggested that participants preferred the MobiTOP design for accessing annotations even though the SFT interface was conceptually easier to understand resources.


Opaque: Protecting Path Privacy In Directions Search, Ken C. K. Lee, Wang-Chien Lee, Hong Va Leong, Baihua Zheng Apr 2009

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 …


An Incremental Threshold Method For Continuous Text Search Queries, Kyriakos Mouratidis, Hwee Hwa Pang Apr 2009

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 …


Efficient Evaluation Of Multiple Preference Queries, Hou U Leong, Nikos Mamaoulis, Kyriakos Mouratidis Apr 2009

Efficient Evaluation Of Multiple Preference Queries, Hou U Leong, Nikos Mamaoulis, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

Consider multiple users searching for a hotel room, based on size, cost, distance to the beach, etc. Users may have variable preferences expressed by different weights on the attributes of the searched objects. Although individual preference queries can be evaluated by selecting the object in the database with the highest aggregate score, in the case of multiple requests at the same time, a single object cannot be assigned to more than one users. The challenge is to compute a fair 1-1 matching between the queries and a subset of the objects. We model this as a stable-marriage problem and propose …


House Of Cards, M. Thulasidas Mar 2009

House Of Cards, M. Thulasidas

Research Collection School Of Computing and Information Systems

We are in dire straits - no doubt about it. Our banks and financial edifices are collapsing. Those left standing also look shaky. The financial industry as a whole is battling to survive. And, as its frontline warriors, we will bear the brunt of the blood- bath sure to ensue any minute now. A good opportunity to play solitaire?


Continuous Visible Nearest Neighbour Queries, Yunjun Gao, Baihua Zheng, Wang-Chien Lee, Gencai Chen Mar 2009

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 …


Web Query Recommendation Via Sequential Query Prediction, Qi He, Daxin Jiang, Zhen Liao, Steven C. H. Hoi, Kuiyu Chang, Ee Peng Lim, Hang Li Mar 2009

Web Query Recommendation Via Sequential Query Prediction, Qi He, Daxin Jiang, Zhen Liao, Steven C. H. Hoi, Kuiyu Chang, Ee Peng Lim, Hang Li

Research Collection School Of Computing and Information Systems

Web query recommendation has long been considered a key feature of search engines. Building a good Web query recommendation system, however, is very difficult due to the fundamental challenge of predicting users' search intent, especially given the limited user context information. In this paper, we propose a novel "sequential query prediction" approach that tries to grasp a user's search intent based on his/her past query sequence and its resemblance to historical query sequence models mined from massive search engine logs. Different query sequence models were examined, including the naive variable length N-gram model, Variable Memory Markov (VMM) model, and our …


Fast Object Search On Road Networks, Ken C. K. Lee, Wang-Chien Lee, Baihua Zheng Mar 2009

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 …


Stochastic Modeling Western Paintings For Effective Classification, Jialie Shen Feb 2009

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 …


Learning Image‐Text Associations, Tao Jiang, Ah-Hwee Tan Feb 2009

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 …


Localized Monitoring Of Knn Queries In Wireless Sensor Networks, Yuxia Yao, Xueyan Tang, Ee Peng Lim Jan 2009

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 Jan 2009

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 Jan 2009

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 …


Chaos And Uncertainty, M. Thulasidas Jan 2009

Chaos And Uncertainty, M. Thulasidas

Research Collection School Of Computing and Information Systems

The end of 2008 in the finance industry can be summarized in two words – chaos and uncertainty. The subprime crisis, where everybody lost; the dizzying commodity price movements; the pink slip syndrome; the spectacular bank busts; and the gargantuan bail-outs all vouch for it.


Computing Medoids In Large Spatial Datasets, Kyriakos Mouratidis, Dimitris Papadias, Spiros Papadimitriou Jan 2009

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.


Web Social Mining, Hady W. Lauw, Ee Peng Lim Jan 2009

Web Social Mining, Hady W. Lauw, Ee Peng Lim

Research Collection School Of Computing and Information Systems

No abstract provided.


Continuous Monitoring Of Spatial Queries, Kyriakos Mouratidis Jan 2009

Continuous Monitoring Of Spatial Queries, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

No abstract provided.


Quality-Aware Collaborative Question Answering: Methods And Evaluation, Maggy Anastasia Suryanto, Ee Peng Lim, Aixin Sun, Roger Hsiang-Li Chiang Jan 2009

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 …


Tuning On-Air Signatures For Balancing Performance And Confidentiality, Baihua Zheng, Wang-Chien Lee, Peng Liu, Dik Lun Lee, Xuhua Ding Jan 2009

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 …


Dynamic Web Service Selection For Reliable Web Service Composition, San-Yih Hwang, Ee Peng Lim, Chien-Hsiang Lee, Cheng-Hung Chen Jan 2009

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 …


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 Jan 2009

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 …


Modelling Situation Awareness For Context‐Aware Decision Support, Yu-Hong Feng, Teck-Hou Teng, Ah-Hwee Tan Jan 2009

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 …