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A Survey Of Techniques And Challenges In Underwater Localization, Hwee-Pink Tan, Roee Diamant, Winston K. G. Seah, Marc Waldmeyer
A Survey Of Techniques And Challenges In Underwater Localization, Hwee-Pink Tan, Roee Diamant, Winston K. G. Seah, Marc Waldmeyer
Research Collection School Of Computing and Information Systems
Underwater Wireless Sensor Networks (UWSNs) are expected to support a variety of civilian and military applications. Sensed data can only be interpreted meaningfully when referenced to the location of the sensor, making localization an important problem. While global positioning system (GPS) receivers are commonly used in terrestrial WSNs to achieve this, this is infeasible in UWSNs as GPS signals do not propagate through water. Acoustic communications is the most promising mode of communication underwater. However, underwater acoustic channels are characterized by harsh physical layer conditions with low bandwidth, high propagation delay and high bit error rate. Moreover, the variable speed …
Packed, Printable, And Polymorphic Return-Oriented Programming, Kangjie Lu, Dabi Zou, Weiping Wen, Debin Gao
Packed, Printable, And Polymorphic Return-Oriented Programming, Kangjie Lu, Dabi Zou, Weiping Wen, Debin Gao
Research Collection School Of Computing and Information Systems
Return-oriented programming (ROP) is an attack that has been shown to be able to circumvent W ⊕ X protection. However, it was not clear if ROP can be made as powerful as non-ROP malicious code in other aspects, e.g., be packed to make static analysis difficult, be printable to evade non-ASCII filtering, be polymorphic to evade signature-based detection, etc. Research in these potential advances in ROP is important in designing counter-measures. In this paper, we show that ROP code could be packed, printable, and polymorphic. We demonstrate this by proposing a packer that produces printable and polymorphic ROP code. It …
Improved Ordinary Measure And Image Entropy Theory Based Intelligent Copy Detection Method, Dengpan Ye, Longfei Ma, Lina Wang, Robert H. Deng
Improved Ordinary Measure And Image Entropy Theory Based Intelligent Copy Detection Method, Dengpan Ye, Longfei Ma, Lina Wang, Robert H. Deng
Research Collection School Of Computing and Information Systems
Nowadays, more and more multimedia websites appear in social network. It brings some security problems, such as privacy, piracy, disclosure of sensitive contents and so on. Aiming at copyright protection, the copy detection technology of multimedia contents becomes a hot topic. In our previous work, a new computer-based copyright control system used to detect the media has been proposed. Based on this system, this paper proposes an improved media feature matching measure and an entropy based copy detection method. The Levenshtein Distance was used to enhance the matching degree when using for feature matching measure in copy detection. For entropy …
Tamper Detection In The Epc Network Using Digital Watermarking, Shui-Hua Han, Chao-Hsien Chu, Zongwei Luo
Tamper Detection In The Epc Network Using Digital Watermarking, Shui-Hua Han, Chao-Hsien Chu, Zongwei Luo
Research Collection School Of Computing and Information Systems
One of the most relevant problems in radio frequency identification (RFID) technology is the lack of security measures in its wireless communication channel between the reader and tag. This article analyzes potential data tampering threats in the electronic product code (EPC) network and proposes solutions using fragile watermarking technologies.
Structural Analysis Of The Hot Spots In The Binding Between H1n1 Ha And The 2di Antibody: Do Mutations Of H1n1 From 1918 To 2009 Affect Much On This Binding?, Qian Liu, Steven C. H. Hoi, Chinh T. T. Su, Zhenhua Li, Chee-Keong Kwoh, Limsoon Wong, Jinyan Li
Structural Analysis Of The Hot Spots In The Binding Between H1n1 Ha And The 2di Antibody: Do Mutations Of H1n1 From 1918 To 2009 Affect Much On This Binding?, Qian Liu, Steven C. H. Hoi, Chinh T. T. Su, Zhenhua Li, Chee-Keong Kwoh, Limsoon Wong, Jinyan Li
Research Collection School Of Computing and Information Systems
Worldwide and substantial mortality caused by the 2009 H1N1 influenza A has stimulated a new surge of research on H1N1 viruses. An epitope conservation has been learned in the HA1 protein that allows antibodies to cross-neutralize both 1918 and 2009 H1N1. However, few works have thoroughly studied the binding hot spots in those two antigen–antibody interfaces which are responsible for the antibody cross-neutralization. We apply predictive methods to identify binding hot spots at the epitope sites of the HA1 proteins and at the paratope sites of the 2D1 antibody. We find that the six mutations at the HA1's epitope from …
Spectral Geometry Image: Image Based 3d Models For Digital Broadcasting Applications, Boon Seng Chew, Lap Pui Chau, Ying He, Dayong Wang, Steven C. H. Hoi
Spectral Geometry Image: Image Based 3d Models For Digital Broadcasting Applications, Boon Seng Chew, Lap Pui Chau, Ying He, Dayong Wang, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
The use of 3D models for progressive transmission and broadcasting applications is an interesting challenge due to the nature and complexity of such content. In this paper, a new image format for the representation of 3D progressive model is proposed. The powerful spectral analysis is combined with the state of art Geometry Image(GI) to encode static 3D models into spectral geometry images(SGI) for robust 3D shape representation. Based on the 3D model's surface characteristics, SGI separated the geometrical image into low and high frequency layers to achieve effective Level of Details(LOD) modeling. For SGI, the connectivity data of the model …
Enhancing Brand Equity Through Flow And Telepresence: A Comparison Of 2d And 3d Virtual Worlds, Fiona Fui-Hoon Nah, B. Eschenbrenner, D. Dewester
Enhancing Brand Equity Through Flow And Telepresence: A Comparison Of 2d And 3d Virtual Worlds, Fiona Fui-Hoon Nah, B. Eschenbrenner, D. Dewester
Research Collection School Of Computing and Information Systems
This research uses theories of flow, telepresence, positive emotions, and brand equity to examine the effect of using two-dimensional versus three-dimensional virtual world environments on telepresence, enjoyment, brand equity, and behavioral intention. The findings suggest that the 3D virtual world environment produces both positive and negative effects on brand equity when compared to the 2D environment. The positive effect of the 3D virtual world environment on brand equity occurs through telepresence, a specific aspect of flow, as well as enjoyment. The negative effect on brand equity can be explained using distraction-conflict theory in which attentional conflicts faced by users of …
Effective Communication Of Software Development Knowledge Through Community Portals, Christoph Treude, Margaret-Anne Storey
Effective Communication Of Software Development Knowledge Through Community Portals, Christoph Treude, Margaret-Anne Storey
Research Collection School Of Computing and Information Systems
Knowledge management plays an important role in many software organizations. Knowledge can be captured and distributed using a variety of media, including traditional help files and manuals, videos, technical articles, wikis, and blogs. In recent years, web-based community portals have emerged as an important mechanism for combining various communication channels. However, there is little advice on how they can be effectively deployed in a software project.In this paper, we present a first study of a community portal used by a closed source software project. Using grounded theory, we develop a model that characterizes documentation artifacts along several dimensions, such as …
Mining Top-K Large Structural Patterns In A Massive Network, Feida Zhu, Qiang Qu, David Lo, Xifeng Yan, Jiawei Han, Philip S. Yu
Mining Top-K Large Structural Patterns In A Massive Network, Feida Zhu, Qiang Qu, David Lo, Xifeng Yan, Jiawei Han, Philip S. Yu
Research Collection School Of Computing and Information Systems
With ever-growing popularity of social networks, web and bio-networks, mining large frequent patterns from a single huge network has become increasingly important. Yet the existing pattern mining methods cannot offer the efficiency desirable for large pattern discovery. We propose Spider- Mine, a novel algorithm to efficiently mine top-K largest frequent patterns from a single massive network with any user-specified probability of 1 − ϵ. Deviating from the existing edge-by-edge (i.e., incremental) pattern-growth framework, SpiderMine achieves its efficiency by unleashing the power of small patterns of a bounded diameter, which we call “spiders”. With the spider structure, our approach adopts a …
Certificateless Cryptography With Kgc Trust Level 3, Guomin Yang, Chik How Tan
Certificateless Cryptography With Kgc Trust Level 3, Guomin Yang, Chik How Tan
Research Collection School Of Computing and Information Systems
A normal certificateless cryptosystem can only achieve KGC trust level 2 according to the trust hierarchy defined by Girault. Although in the seminal paper introducing certificateless cryptography, Al-Riyami and Paterson introduced a binding technique to lift the KGC trust level of their certificateless schemes to level 3, many subsequent work on certificateless cryptography just focused on the constructions of normal certificateless schemes, and a formal study on the general applicability of the binding technique to these existing schemes is still missing. In this paper, to address the KGC trust level issue, we introduce the notion of Key Dependent Certificateless Cryptography …
An Efficient Adaptive Vortex Particle Method For Real-Time Smoke Simulation, Shengfeng He, Hon-Cheng Wong, Un-Hong Wong
An Efficient Adaptive Vortex Particle Method For Real-Time Smoke Simulation, Shengfeng He, Hon-Cheng Wong, Un-Hong Wong
Research Collection School Of Computing and Information Systems
Smoke simulation is one of the interesting topics in computer animation and it usually involves turbulence generation. Efficient generation of realistic turbulent flows becomes one of the challenges in smoke simulation. Vortex particle method, which is a hybrid method that combines grid-based and particle-based approaches, is often used for generating turbulent details. However, it may cause irrational artifacts due to its initial condition and vorticity forcing approach used. In this paper, a new vorticity forcing approach based on the spatial adaptive vorticity confinement is proposed to address this problem. In this approach, the spatial adaptive vorticity confinement force varies with …
Information Quality On The World Wide Web: Development Of A Framework, J. Kandari, E. Jones, Fiona Fui-Hoon Nah, R. Bishu
Information Quality On The World Wide Web: Development Of A Framework, J. Kandari, E. Jones, Fiona Fui-Hoon Nah, R. Bishu
Research Collection School Of Computing and Information Systems
Data consumers are provided with easy online access to information on the World Wide Web. However, consumers face information quality problems in their quest for information. This paper focuses on the development of an instrument to measure information quality (IQ) on the World Wide Web from a user's perspective. Based on a comprehensive review of the literature, 20 important IQ frameworks were identified. These models, though varied in their approach and application, share a number of characteristics regarding their classifications of the attributes of quality. The paper identifies common dimensions that exist across the existing IQ frameworks in the literature …
Structural Complexity And Programmer Team Strategy: An Experimental Test, Narayan Ramasubbu, Chris F. Kemerer, Jeff Min Teck Hong
Structural Complexity And Programmer Team Strategy: An Experimental Test, Narayan Ramasubbu, Chris F. Kemerer, Jeff Min Teck Hong
Research Collection School Of Computing and Information Systems
This study develops and empirically tests the idea that the impact of structural complexity on perfective maintenance of object-oriented software is significantly determined by the team strategy of programmers (independent or collaborative). We analyzed two key dimensions of software structure, coupling and cohesion, with respect to the maintenance effort and the perceived ease-of-maintenance by pairs of programmers. Hypotheses based on the distributed cognition and task interdependence theoretical frameworks were tested using data collected from a controlled lab experiment employing professional programmers. The results show a significant interaction effect between coupling, cohesion, and programmer team strategy on both maintenance effort and …
Defending Against Cross Site Scripting Attacks, Lwin Khin Shar, Hee Beng Kuan Tan
Defending Against Cross Site Scripting Attacks, Lwin Khin Shar, Hee Beng Kuan Tan
Research Collection School Of Computing and Information Systems
Researchers have proposed multiple solutions to cross-site scripting, but vulnerabilities continue to exist in many Web applications due to developers' lack of understanding of the problem and their unfamiliarity with current defenses' strengths and limitations.
A Hubel Wiesel Model Of Early Concept Generalization Based On Local Correlation Of Input Features, Sepideh Sadeghi, Kiruthika Ramanathan
A Hubel Wiesel Model Of Early Concept Generalization Based On Local Correlation Of Input Features, Sepideh Sadeghi, Kiruthika Ramanathan
Research Collection School Of Computing and Information Systems
Hubel Wiesel models, successful in visual processing algorithms, have only recently been used in conceptual representation. Despite the biological plausibility of a Hubel-Wiesel like architecture for conceptual memory and encouraging preliminary results, there is no implementation of how inputs at each layer of the hierarchy should be integrated for processing by a given module, based on the correlation of the features. In our paper, we propose the input integration framework - a set of operations performed on the inputs to the learning modules of the Hubel Wiesel model of conceptual memory. These operations weight the modules as being general or …
A Generic Framework For Three-Factor Authentication: Preserving Security And Privacy In Distributed Systems, Xinyi Huang, Yang Xiang, Ashley Chonka, Jianying Zhou, Robert H. Deng
A Generic Framework For Three-Factor Authentication: Preserving Security And Privacy In Distributed Systems, Xinyi Huang, Yang Xiang, Ashley Chonka, Jianying Zhou, Robert H. Deng
Research Collection School Of Computing and Information Systems
As part of the security within distributed systems, various services and resources need protection from unauthorized use. Remote authentication is the most commonly used method to determine the identity of a remote client. This paper investigates a systematic approach for authenticating clients by three factors, namely password, smart card, and biometrics. A generic and secure framework is proposed to upgrade two-factor authentication to three-factor authentication. The conversion not only significantly improves the information assurance at low cost but also protects client privacy in distributed systems. In addition, our framework retains several practice-friendly properties of the underlying two-factor authentication, which we …
Taxisim: A Multiagent Simulation Platform For Evaluating Taxi Fleet Operations, Shih-Fen Cheng, Thi Duong Nguyen
Taxisim: A Multiagent Simulation Platform For Evaluating Taxi Fleet Operations, Shih-Fen Cheng, Thi Duong Nguyen
Research Collection School Of Computing and Information Systems
Taxi service is an important mode of public transportation in most metropolitan areas since it provides door-to-door convenience in the public domain. Unfortunately, despite all the convenience taxis bring, taxi fleets are also extremely inefficient to the point that over 50% of its operation time could be spent in idling state. Improving taxi fleet operation is an extremely challenging problem, not just because of its scale, but also due to fact that taxi drivers are self-interested agents that cannot be controlled centrally. To facilitate the study of such complex and decentralized system, we propose to construct a multiagent simulation platform …
General Construction Of Chameleon All-But-One Trapdoor Functions, Shengli Liu, Junzuo Lai, Robert H. Deng
General Construction Of Chameleon All-But-One Trapdoor Functions, Shengli Liu, Junzuo Lai, Robert H. Deng
Research Collection School Of Computing and Information Systems
Lossy trapdoor functions enable black-box construction of public key encryption (PKE) schemes secure against chosen-ciphertext attack [18]. Recently, a more efficient black-box construction of public key encryption was given in [13] with the help of chameleon all-but-one trapdoor functions (ABO-TDFs). In this paper, we propose a black-box construction for transforming any ABO-TDFs into chameleon ABO-TDFs with the help of chameleon hash functions. Instantiating the proposed general black-box construction of chameleon ABO-TDFs, we obtain the first chameleon ABO-TDFs based on the Decisional Diffie-Hellman (DDH) assumption.
Online Auc Maximization, Peilin Zhao, Steven C. H. Hoi, Rong Jin, Tianbo Yang
Online Auc Maximization, Peilin Zhao, Steven C. H. Hoi, Rong Jin, Tianbo Yang
Research Collection School Of Computing and Information Systems
Most studies of online learning measure the performance of a learner by classification accuracy, which is inappropriate for applications where the data are unevenly distributed among different classes. We address this limitation by developing online learning algorithm for maximizing Area Under the ROC curve (AUC), a metric that is widely used for measuring the classification performance for imbalanced data distributions. The key challenge of online AUC maximization is that it needs to optimize the pairwise loss between two instances from different classes. This is in contrast to the classical setup of online learning where the overall loss is a sum …
Generating Aspect-Oriented Multi-Document Summarization With Event-Aspect Model, Peng Li, Yinglin Wang, Wei Gao, Jing Jiang
Generating Aspect-Oriented Multi-Document Summarization With Event-Aspect Model, Peng Li, Yinglin Wang, Wei Gao, Jing Jiang
Research Collection School Of Computing and Information Systems
In this paper, we propose a novel approach to automatic generation of aspect-oriented summaries from multiple documents. We first develop an event-aspect LDA model to cluster sentences into aspects. We then use extended LexRank algorithm to rank the sentences in each cluster. We use Integer Linear Programming for sentence selection. Key features of our method include automatic grouping of semantically related sentences and sentence ranking based on extension of random walk model. Also, we implement a new sentence compression algorithm which use dependency tree instead of parser tree. We compare our method with four baseline methods. Quantitative evaluation based on …
Relevant Knowledge Helps In Choosing Right Teacher: Active Query Selection For Ranking Adaptation, Peng Cai, Wei Gao, Kam-Fai Wong, Aoying Zhou
Relevant Knowledge Helps In Choosing Right Teacher: Active Query Selection For Ranking Adaptation, Peng Cai, Wei Gao, Kam-Fai Wong, Aoying Zhou
Research Collection School Of Computing and Information Systems
Learning to adapt in a new setting is a common challenge to our knowledge and capability. New life would be easier if we actively pursued supervision from the right mentor chosen with our relevant but limited prior knowledge. This variant principle of active learning seems intuitively useful to many domain adaptation problems. In this paper, we substantiate its power for advancing automatic ranking adaptation, which is important in web search since it's prohibitive to gather enough labeled data for every search domain for fully training domain-specific rankers. For the cost-effectiveness, it is expected that only those most informative instances in …
A Hybrid Agent Architecture Integrating Desire, Intention And Reinforcement Learning, Ah-Hwee Tan, Yew-Soon Ong, Akejariyawong Tapanuj
A Hybrid Agent Architecture Integrating Desire, Intention And Reinforcement Learning, Ah-Hwee Tan, Yew-Soon Ong, Akejariyawong Tapanuj
Research Collection School Of Computing and Information Systems
This paper presents a hybrid agent architecture that integrates the behaviours of BDI agents, specifically desire and intention, with a neural network based reinforcement learner known as Temporal DifferenceFusion Architecture for Learning and COgNition (TD-FALCON). With the explicit maintenance of goals, the agent performs reinforcement learning with the awareness of its objectives instead of relying on external reinforcement signals. More importantly, the intention module equips the hybrid architecture with deliberative planning capabilities, enabling the agent to purposefully maintain an agenda of actions to perform and reducing the need of constantly sensing the environment. Through reinforcement learning, plans can also be …
Scalable Multiagent Planning Using Probabilistic Inference, Akshat Kumar, Shlomo Zilberstein, Marc Toussaint
Scalable Multiagent Planning Using Probabilistic Inference, Akshat Kumar, Shlomo Zilberstein, Marc Toussaint
Research Collection School Of Computing and Information Systems
Multiagent planning has seen much progress with the development of formal models such as Dec-POMDPs. However, the complexity of these models -- NEXP-Complete even for two agents -- has limited scalability. We identify certain mild conditions that are sufficient to make multiagent planning amenable to a scalable approximation w.r.t. the number of agents. This is achieved by constructing a graphical model in which likelihood maximization is equivalent to plan optimization. Using the Expectation-Maximization framework for likelihood maximization, we show that the necessary inference can be decomposed into processes that often involve a small subset of agents, thereby facilitating scalability. We …
Generating Aspect-Oriented Multi-Document Summarization With Event-Aspect Model, Peng Li, Yinglin Wang, Wei Gao, Jing Jiang
Generating Aspect-Oriented Multi-Document Summarization With Event-Aspect Model, Peng Li, Yinglin Wang, Wei Gao, Jing Jiang
Research Collection School Of Computing and Information Systems
In this paper, we propose a novel approach to automatic generation of aspect-oriented summaries from multiple documents. We first develop an event-aspect LDA model to cluster sentences into aspects. We then use extended LexRank algorithm to rank the sentences in each cluster. We use Integer Linear Programming for sentence selection. Key features of our method include automatic grouping of semantically related sentences and sentence ranking based on extension of random walk model. Also, we implement a new sentence compression algorithm which use dependency tree instead of parser tree. We compare our method with four baseline methods. Quantitative evaluation based on …
Unsupervised Discovery Of Discourse Relations For Eliminating Intra-Sentence Polarity Ambiguities, Lanjun Zhou, Binyang Li, Wei Gao, Zhongyu Wei, Kam-Fai Wong
Unsupervised Discovery Of Discourse Relations For Eliminating Intra-Sentence Polarity Ambiguities, Lanjun Zhou, Binyang Li, Wei Gao, Zhongyu Wei, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
Polarity classification of opinionated sentences with both positive and negative sentiments1 is a key challenge in sentiment analysis. This paper presents a novel unsupervised method for discovering intra-sentence level discourse relations for eliminating polarity ambiguities. Firstly, a discourse scheme with discourse constraints on polarity was defined empirically based on Rhetorical Structure Theory (RST). Then, a small set of cuephrase-based patterns were utilized to collect a large number of discourse instances which were later converted to semantic sequential representations (SSRs). Finally, an unsupervised method was adopted to generate, weigh and filter new SSRs without cue phrases for recognizing discourse relations. Experimental …
Solution Pluralism And Metaheuristics, Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau, Frederic H. Murphy, David Harlan Wood
Solution Pluralism And Metaheuristics, Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau, Frederic H. Murphy, David Harlan Wood
Research Collection School Of Computing and Information Systems
Solution pluralism is an approach to problem solving and deliberation. It employs a plurality of distinct solutions for a decision problem for aiding decision making. The concept is well established in existing practice, although perhaps not recognized as such. This paper: (1) presents the concept as a generalization of established practice, (2) briefly describes successful uses of the concept in practice, and (3) presents several areas that appear would benefit from application of the concept. Throughout, the role of metaheuristics in finding the pluralities of solutions is emphasized.
Media Landscape In Twitter: A World Of New Conventions And Political Diversity, Jisun An, Meeyoung Cha, Krishna Gummadi, Jon Crowcroft
Media Landscape In Twitter: A World Of New Conventions And Political Diversity, Jisun An, Meeyoung Cha, Krishna Gummadi, Jon Crowcroft
Research Collection School Of Computing and Information Systems
We present a preliminary but groundbreaking study of the media landscape of Twitter. We use public data on whom follows who to uncover common behaviour in media consumption, the relationship between various classes of media, and the diversity of media content which social links may bring. Our analysis shows that there is a non-negligible amount of indirect media exposure, either through friends who follow particular media sources, or via retweeted messages. We show that the indirect media exposure expands the political diversity of news to which users are exposed to a surprising extent, increasing the range by between 60-98%. These …
Cryptanalysis Of Hsiang-Shih's Authentication Scheme For Multi-Server Architecture, Kuo-Hui Yeh, Nai-Wei Lo, Yingjiu Li
Cryptanalysis Of Hsiang-Shih's Authentication Scheme For Multi-Server Architecture, Kuo-Hui Yeh, Nai-Wei Lo, Yingjiu Li
Research Collection School Of Computing and Information Systems
From user point of view, password-based remote user authentication technique is one of the most convenient and easy-to-use mechanisms to provide necessary security on system access. As the number of computer crimes in modern cyberspace has increased dramatically, the robustness of password-based authentication schemes has been investigated by industries and organizations in recent years. In this paper, a well-designed password-based authentication protocol for multi-server communication environment, introduced by Hsiang and Shih, is evaluated. Our security analysis indicates that their scheme is insecure against session key disclosure, server spoofing attack, and replay attack and behavior denial.
Heuristic Algorithms For Balanced Multi-Way Number Partitioning, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang
Heuristic Algorithms For Balanced Multi-Way Number Partitioning, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
Balanced multi-way number partitioning (BMNP) seeks to split a collection of numbers into subsets with (roughly) the same cardinality and subset sum. The problem is NP-hard, and there are several exact and approximate algorithms for it. However, existing exact algorithms solve only the simpler, balanced two-way number partitioning variant, whereas the most effective approximate algorithm, BLDM, may produce widely varying subset sums. In this paper, we introduce the LRM algorithm that lowers the expected spread in subset sums to one third that of BLDM for uniformly distributed numbers and odd subset cardinalities. We also propose Meld, a novel strategy for …
Unsupervised Information Extraction With Distributional Prior Knowledge, Cane Wing-Ki Leung, Jing Jiang, Kian Ming A. Chai, Hai Leong Chieu, Loo-Nin Teow
Unsupervised Information Extraction With Distributional Prior Knowledge, Cane Wing-Ki Leung, Jing Jiang, Kian Ming A. Chai, Hai Leong Chieu, Loo-Nin Teow
Research Collection School Of Computing and Information Systems
We address the task of automatic discovery of information extraction template from a given text collection. Our approach clusters candidate slot fillers to identify meaningful template slots. We propose a generative model that incorporates distributional prior knowledge to help distribute candidates in a document into appropriate slots. Empirical results suggest that the proposed prior can bring substantial improvements to our task as compared to a K-means baseline and a Gaussian mixture model baseline. Specifically, the proposed prior has shown to be effective when coupled with discriminative features of the candidates.