Open Access. Powered by Scholars. Published by Universities.®

Databases and Information Systems Commons™

Open Access. Powered by Scholars. Published by Universities.®

Singapore Management University

Discipline
Keyword
Publication Year
Publication
Publication Type

Articles 2221 - 2250 of 3560

Full-Text Articles in Databases and Information Systems

Generative Modeling Of Entity Comparisons In Text, Maksim Tkachenko, Hady W. Lauw Nov 2014

Generative Modeling Of Entity Comparisons In Text, Maksim Tkachenko, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Users frequently rely on online reviews for decision making. In addition to allowing users to evaluate the quality of individual products, reviews also support comparison shopping. One key user activity is to compare two (or more) products based on a specific aspect. However, making a comparison across two different reviews, written by different authors, is not always equitable due to the different standards and preferences of individual authors. Therefore, we focus instead on comparative sentences, whereby two products are compared directly by a review author within a single sentence. We study the problem of comparative relation mining. Given a set …

Go to article

Exploiting Geographical Neighborhood Characteristics For Location Recommendation, Yong Liu, Wei Wei, Aixin Sun, Chunyan Miao Nov 2014

Exploiting Geographical Neighborhood Characteristics For Location Recommendation, Yong Liu, Wei Wei, Aixin Sun, Chunyan Miao

Research Collection School Of Computing and Information Systems

Geographical characteristics derived from the historical check-in data have been reported effective in improving location recommendation accuracy. However, previous studies mainly exploit geographical characteristics from a user’s perspective, via modeling the geographical distribution of each individual user’s check-ins. In this paper, we are interested in exploiting geographical characteristics from a location perspective, by modeling the geographical neighborhood of a location. The neighborhood is modeled at two levels: the instance-level neighborhood defined by a few nearest neighbors of the location, and the region-level neighborhood for the geographical region where the location exists. We propose a novel recommendation approach, namely Instance-Region Neighborhood …

Go to article

Player Acceptance Of Human Computation Games: An Aesthetic Perspective, Xiaohui Wang, Dion Hoe Lian Goh, Ee Peng Lim, Adrian Wei Liang Vu Nov 2014

Player Acceptance Of Human Computation Games: An Aesthetic Perspective, Xiaohui Wang, Dion Hoe Lian Goh, Ee Peng Lim, Adrian Wei Liang Vu

Research Collection School Of Computing and Information Systems

Human computation games (HCGs) are applications that use games to harness human intelligence to perform computations that cannot be effectively done by software systems alone. Despite their increasing popularity, insufficient research has been conducted to examine the predictors of player acceptance for HCGs. In particular, prior work underlined the important role of game enjoyment in predicting acceptance of entertainment technology without specifying its driving factors. This study views game enjoyment through a taxonomy of aesthetic experiences and examines the effect of aesthetic experience, usability and information quality on player acceptance of HCGs. Results showed that aesthetic experience and usability were …

Go to article

On Joint Modeling Of Topical Communities And Personal Interest In Microblogs, Tuan-Anh Hoang, Ee Peng Lim Nov 2014

On Joint Modeling Of Topical Communities And Personal Interest In Microblogs, Tuan-Anh Hoang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

In this paper, we propose the Topical Communities and Personal Interest (TCPI) model for simultaneously modeling topics, topical communities, and users’ topical interests in microblogging data. TCPI considers different topical communities while differentiating users’ personal topical interests from those of topical communities, and learning the dependence of each user on the affiliated communities to generate content. This makes TCPI different from existing models that either do not consider the existence of multiple topical communities, or do not differentiate between personal and community’s topical interests. Our experiments on two Twitter datasets show that TCPI can effectively mine the representative topics for …

Go to article

Online Passive Aggressive Active Learning And Its Applications, Jing Lu, Peilin Zhao, Steven C. H. Hoi Nov 2014

Online Passive Aggressive Active Learning And Its Applications, Jing Lu, Peilin Zhao, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

We investigate online active learning techniques for classification tasks in data stream mining applications. Unlike traditional learning approaches (either batch or online learning) that often require to request the class label of each incoming instance, online active learning queries only a subset of informative incoming instances to update the classification model, which aims to maximize classification performance using minimal human labeling effort during the entire online stream data mining task. In this paper, we present a new family of algorithms for online active learning called Passive-Aggressive Active (PAA) learning algorithms by adapting the popular Passive-Aggressive algorithms in an online active …

Go to article

Entity Linking On Microblogs With Spatial And Temporal Signals, Yuan Fang, Ming-Wei Chang Oct 2014

Entity Linking On Microblogs With Spatial And Temporal Signals, Yuan Fang, Ming-Wei Chang

Research Collection School Of Computing and Information Systems

Microblogs present an excellent opportunity for monitoring and analyzing world happenings. Given that words are often ambiguous, entity linking becomes a crucial step towards understanding microblogs. In this paper, we re-examine the problem of entity linking on microblogs. We first observe that spatiotemporal (i.e., spatial and temporal) signals play a key role, but they are not utilized in existing approaches. Thus, we propose a novel entity linking framework that incorporates spatiotemporal signals through a weakly supervised process. Using entity annotations1 on real-world data, our experiments show that the spatiotemporal model improves F1 by more than 10 points over existing systems. …

Go to article

Cost-Sensitive Online Classification, Jialei Wang, Peilin Zhao, Steven C. H. Hoi Oct 2014

Cost-Sensitive Online Classification, Jialei Wang, Peilin Zhao, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Both cost-sensitive classification and online learning have been extensively studied in data mining and machine learning communities, respectively. However, very limited study addresses an important intersecting problem, that is, “Cost-Sensitive Online Classification". In this paper, we formally study this problem, and propose a new framework for Cost-Sensitive Online Classification by directly optimizing cost-sensitive measures using online gradient descent techniques. Specifically, we propose two novel cost-sensitive online classification algorithms, which are designed to directly optimize two well-known cost-sensitive measures: (i) maximization of weighted sum of sensitivity and specificity, and (ii) minimization of weighted misclassification cost. We analyze the theoretical bounds of …

Go to article

Time-Series Data Mining In Transportation: A Case Study On Singapore Public Train Commuter Travel Patterns, Roy Ka Wei Lee, Tin Seong Kam Oct 2014

Time-Series Data Mining In Transportation: A Case Study On Singapore Public Train Commuter Travel Patterns, Roy Ka Wei Lee, Tin Seong Kam

Research Collection School Of Computing and Information Systems

The adoption of smart cards technologies and automated data collection systems (ADCS) in transportation domain had provided public transport planners opportunities to amass a huge and continuously increasing amount of time-series data about the behaviors and travel patterns of commuters. However the explosive growth of temporal related databases has far outpaced the transport planners’ ability to interpret these data using conventional statistical techniques, creating an urgent need for new techniques to support the analyst in transforming the data into actionable information and knowledge. This research study thus explores and discusses the potential use of time-series data mining, a relatively new …

Go to article

A Multi-Dimensional Image Quality Prediction Model For User-Generated Images In Social Networks, You Yang, Xu Wang, Tao Guan, Jialie Shen, Li Yu Oct 2014

A Multi-Dimensional Image Quality Prediction Model For User-Generated Images In Social Networks, You Yang, Xu Wang, Tao Guan, Jialie Shen, Li Yu

Research Collection School Of Computing and Information Systems

User-generated images (UGIs) are currently proliferating within social networks. These images contain multi-dimensional data, including the image itself, text and the social links of the owner. UGIs can be utilized for self-presentation, news dissemination and other purposes, and the quality of the image should be able to reveal these social functionalities. However, it is challenging to predict UGI quality utilizing existing models, such as image quality assessment, recommender systems or others, because these models have difficulties processing multi-dimensional data simultaneously. To address this problem, we propose a multi-dimensional image quality prediction model for UGIs in social networks. In this model, …

Go to article

Build Emotion Lexicon From Microblogs By Combining Effects Of Seed Words And Emoticons In A Heterogeneous Graph, Kaisong Song, Shi Feng, Wei Gao, Daling Wang, Ling Chen, Chengqi Zhang Sep 2014

Build Emotion Lexicon From Microblogs By Combining Effects Of Seed Words And Emoticons In A Heterogeneous Graph, Kaisong Song, Shi Feng, Wei Gao, Daling Wang, Ling Chen, Chengqi Zhang

Research Collection School Of Computing and Information Systems

As an indispensable resource for emotion analysis, emotion lexicons have attracted increasing attention in recent years. Most existing methods focus on capturing the single emotional effect of words rather than the emotion distributions which are helpful to model multiple complex emotions in a subjective text. Meanwhile, automatic lexicon building methods are overly dependent on seed words but neglect the effect of emoticons which are natural graphical labels of fine-grained emotion. In this paper, we propose a novel emotion lexicon building framework that leverages both seed words and emoticons simultaneously to capture emotion distributions of candidate words more accurately. Our method …

Go to article

Sharing Political News: The Balancing Act Of Intimacy And Socialization In Selective Exposure, Jisun An, Daniele Quercia, Meeyoung Cha, Krishna Gummadi, Jon Crowcroft Sep 2014

Sharing Political News: The Balancing Act Of Intimacy And Socialization In Selective Exposure, Jisun An, Daniele Quercia, Meeyoung Cha, Krishna Gummadi, Jon Crowcroft

Research Collection School Of Computing and Information Systems

One might think that, compared to traditional media, social media sites allow people to choose more freely what to read and what to share, especially for politically oriented news. However, reading and sharing habits originate from deeply ingrained behaviors that might be hard to change. To test the extent to which this is true, we propose a Political News Sharing (PoNS) model that holistically captures four key aspects of social psychology: gratification, selective exposure, socialization, and trust & intimacy. Using real instances of political news sharing in Twitter, we study the predictive power of these features. As one might expect, …

Go to article

Graph Matching By Simplified Convex-Concave Relaxation Procedure, Zhiyong Liu, Hong Qiao, Xu Yang, Steven C. H. Hoi Sep 2014

Graph Matching By Simplified Convex-Concave Relaxation Procedure, Zhiyong Liu, Hong Qiao, Xu Yang, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

The convex and concave relaxation procedure (CCRP) was recently proposed and exhibited state-of-the-art performance on the graph matching problem. However, CCRP involves explicitly both convex and concave relaxations which typically are difficult to find, and thus greatly limit its practical applications. In this paper we propose a simplified CCRP scheme, which can be proved to realize exactly CCRP, but with a much simpler formulation without needing the concave relaxation in an explicit way, thus significantly simplifying the process of developing CCRP algorithms. The simplified CCRP can be generally applied to any optimizations over the partial permutation matrix, as long as …

Go to article

A Study Of Age Gaps Between Online Friends, Lizi Liao, Jing Jiang, Ee Peng Lim, Heyan Huang Sep 2014

A Study Of Age Gaps Between Online Friends, Lizi Liao, Jing Jiang, Ee Peng Lim, Heyan Huang

Research Collection School Of Computing and Information Systems

User attribute extraction on social media has gain considerable attention, while existing methods are mostly supervised which suffer great diffi- culty in insufficient gold standard data. In this paper, we validate a strong hypothesis based on homophily and adapt it to ensure the certainty of user attribute we extracted via weakly supervised propagation. Homophily, the theory which states that people who are similar tend to become friends, has been well studied in the setting of online social networks. When we focus on age attribute, based on this theory, online friends tend to have similar age. In this work, we take …

Go to article

An Exploratory Study On Software Microblogger Behaviors, Yuan Tian, David Lo Sep 2014

An Exploratory Study On Software Microblogger Behaviors, Yuan Tian, David Lo

Research Collection School Of Computing and Information Systems

Microblogging services are growing rapidly in the recent years. Twitter, one of the most popular microblogging sites, has gained more than 500 millions users. Thousands of developers are also using Twitter to communicate with one another and microblog about software-related topics such as programming languages, code libraries, etc. Understanding the behaviors of software microbloggers is one of the needed first steps toward building automated tools to encourage software microblogging activities and harness software microblogging to improve various software engineering activities. In this paper, we investigate the behaviors of software microbloggers in terms of their microblogging frequency, generated contents, and interactions …

Go to article

Press: A Novel Framework Of Trajectory Compression In Road Networks, Renchu Song, Weiwei Sun, Baihua Zheng, Yu Zheng Sep 2014

Press: A Novel Framework Of Trajectory Compression In Road Networks, Renchu Song, Weiwei Sun, Baihua Zheng, Yu Zheng

Research Collection School Of Computing and Information Systems

Location data becomes more and more important. In this paper, we focus on the trajectory data, and propose a new framework, namely PRESS (Paralleled Road-Network-Based Trajectory Compression), to effectively compress trajectory data under road network constraints. Different from existing work, PRESS proposes a novel representation for trajectories to separate the spatial representation of a trajectory from the temporal representation, and proposes a Hybrid Spatial Compression (HSC) algorithm and error Bounded Temporal Compression (BTC) algorithm to compress the spatial and temporal information of trajectories respectively. PRESS also supports common spatial-temporal queries without fully decompressing the data. Through an extensive experimental study …

Go to article

The Use Of Geospatial Clustering In Analysing Health Risk Profile, Sue-Mae Yeo, Tin Seong Kam, Kai Xin Thia, Dan Wu Sep 2014

The Use Of Geospatial Clustering In Analysing Health Risk Profile, Sue-Mae Yeo, Tin Seong Kam, Kai Xin Thia, Dan Wu

Research Collection School Of Computing and Information Systems

Background & Hypothesis: The first law of geography states that “everything is related to everything else, but near things are more related than distant things”. This study aims to demonstrate how local indicator of spatial association (LISA) statistics are used to group patients with similar chronic diseases into natural clusters of hotspots found within northern Singapore by incorporating the proximity of their home locations explicitly. Methods: Anonymised chronic patient data collected from Khoo Teck Puat Hospital in 2013 were used for analyses. The data was mapped based on patients' residential addresses. A layer of hexagonal grid objects, each with a …

Go to article

Clear: A Real-Time Online Observatory For Bursty And Viral Events, Runquan Xie, Feida Zhu, Hui Ma, Wei Xie, Chen Lin Sep 2014

Clear: A Real-Time Online Observatory For Bursty And Viral Events, Runquan Xie, Feida Zhu, Hui Ma, Wei Xie, Chen Lin

Research Collection School Of Computing and Information Systems

We describe our demonstration of CLEar (Clairaudient Ear), a real-time online platform for detecting, monitoring, summarizing, contextualizing and visualizing bursty and viral events, those triggering a sudden surge of public interest and going viral on micro-blogging platforms. This task is challenging for existing methods as they either use complicated topic models to analyze topics in a off-line manner or define temporal structure of fixed granularity on the data stream for online topic learning, leaving them hardly scalable for real-time stream like that of Twitter. In this demonstration of CLEar, we present a three-stage system: First, we show …

Go to article

Interestingness-Driven Diffussion Process Summarization In Dynamic Networks, Qiang Qu, Siyuan Liu, Christian Jensen, Feida Zhu, Christos Faloutsos Sep 2014

Interestingness-Driven Diffussion Process Summarization In Dynamic Networks, Qiang Qu, Siyuan Liu, Christian Jensen, Feida Zhu, Christos Faloutsos

Research Collection School Of Computing and Information Systems

The widespread use of social networks enables the rapid diffusion of information, e.g., news, among users in very large communities. It is a substantial challenge to be able to observe and understand such diffusion processes, which may be modeled as networks that are both large and dynamic. A key tool in this regard is data summarization. However, few existing studies aim to summarize graphs/networks for dynamics. Dynamic networks raise new challenges not found in static settings, including time sensitivity and the needs for online interestingness evaluation and summary traceability, which render existing techniques inapplicable. We study the topic of dynamic …

Go to article

Online Probabilistic Learning For Fuzzy Inference System, Richard Jayadi Oentaryo, Meng Joo Er, San Linn, Xiang Li Sep 2014

Online Probabilistic Learning For Fuzzy Inference System, Richard Jayadi Oentaryo, Meng Joo Er, San Linn, Xiang Li

Research Collection School Of Computing and Information Systems

Online learning is a key methodology for expert systems to gracefully cope with dynamic environments. In the context of neuro-fuzzy systems, research efforts have been directed toward developing online learning methods that can update both system structure and parameters on the fly. However, the current online learning approaches often rely on heuristic methods that lack a formal statistical basis and exhibit limited scalability in the face of large data stream. In light of these issues, we develop a new Sequential Probabilistic Learning for Adaptive Fuzzy Inference System (SPLAFIS) that synergizes the Bayesian Adaptive Resonance Theory (BART) and Rule-Wise Decoupled Extended …

Go to article

Linking Lightweight And Heavyweight Systems Analysis By Converting Service Responsibility Tables Into Uml Diagrams, X. Tan, S. Alter, Keng Siau Sep 2014

Linking Lightweight And Heavyweight Systems Analysis By Converting Service Responsibility Tables Into Uml Diagrams, X. Tan, S. Alter, Keng Siau

Research Collection School Of Computing and Information Systems

Heavyweight systems analysis approaches such as the use of Unified Modeling Language (UML) are inappropriate for business professionals who nonetheless need to participate actively in systems analysis and design processes to ensure that the system requirements reflect their needs. This paper proposes the use of a lightweight analysis approach based on Service Responsibility Tables (SRTs) to serve as a front-end to UML diagrams. Business professionals (with or without the help of IT professionals) can use this lightweight approach to specify at least part of system requirements. Subsequently, IT professionals can perform heavyweight analysis for the design and implementation of hardware …

Go to article

Opinion Mining Of Sociopolitical Comments From Social Media, Swapna Gottipati Aug 2014

Opinion Mining Of Sociopolitical Comments From Social Media, Swapna Gottipati

Dissertations and Theses Collection (Open Access)

Opinions are central to almost all human activities by influencing greatly the decision making process. In this thesis, we present the problems of mining issues, extracting entities and suggestive opinions towards the entities, detecting thoughtful comments, and extracting stances and ideological expressions from online comments in the sociopolitical domain. This study is essential for opinion mining applications that are beneficial for policy makers, government sectors and social organizations. Much work has been done to try to uncover consumer sentiments from online comments to help businesses improve their products and services. However, sociopolitical opinion mining poses new challenges due to complex …

Go to article

Integrating Motivated Learning And K-Winner-Take-All To Coordinate Multi-Agent Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Janusz Starzyk, Yuan-Sin Tan, Loo-Nin Teow Aug 2014

Integrating Motivated Learning And K-Winner-Take-All To Coordinate Multi-Agent Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Janusz Starzyk, Yuan-Sin Tan, Loo-Nin Teow

Research Collection School Of Computing and Information Systems

This work addresses the coordination issue in distributed optimization problem (DOP) where multiple distinct and time-critical tasks are performed to satisfy a global objective function. The performance of these tasks has to be coordinated due to the sharing of consumable resources and the dependency on non-consumable resources. Knowing that it can be sub-optimal to predefine the performance of the tasks for large DOPs, the multi-agent reinforcement learning (MARL) framework is adopted wherein an agent is used to learn the performance of each distinct task using reinforcement learning. To coordinate MARL, we propose a novel coordination strategy integrating Motivated Learning (ML) …

Go to article

Integrating Motivated Learning And K-Winner-Take-All To Coordinate Multi-Agent Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Janusz Starzyk, Yuan-Sin Tan, Loo-Nin Teow Aug 2014

Integrating Motivated Learning And K-Winner-Take-All To Coordinate Multi-Agent Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Janusz Starzyk, Yuan-Sin Tan, Loo-Nin Teow

Research Collection School Of Computing and Information Systems

This work addresses the coordination issue in distributed optimization problem (DOP) where multiple distinct and time-critical tasks are performed to satisfy a global objective function. The performance of these tasks has to be coordinated due to the sharing of consumable resources and the dependency on non-consumable resources. Knowing that it can be sub-optimal to predefine the performance of the tasks for large DOPs, the multi-agent reinforcement learning (MARL) framework is adopted wherein an agent is used to learn the performance of each distinct task using reinforcement learning. To coordinate MARL, we propose a novel coordination strategy integrating Motivated Learning (ML) …

Go to article

Gta-M: Greedy Trajectory-Aware (M Copies) Routing For Airborne Networks, Xiaoping Ma, Hwee Xian Tan, Alvin C. Valera Aug 2014

Gta-M: Greedy Trajectory-Aware (M Copies) Routing For Airborne Networks, Xiaoping Ma, Hwee Xian Tan, Alvin C. Valera

Research Collection School Of Computing and Information Systems

Airborne networks have potential applications in both civilian and military domains - such as passenger in-flight Internet connectivity, air traffic control and in intelligence, surveillance and reconnaissance (ISR) activities. However, airborne networks suffer from frequent disruptions due to high node mobility, ad hoc connectivity and line-of-sight blockages. These challenges can be alleviated through the use of disruption-tolerant networking (DTN) techniques. In this paper, we propose GTA-m, a multi-copy greedy trajectory-aware routing protocol for airborne networks. GTA-m employs DTN capabilities and exploits the use of flight information to forwarded bundles greedily to intended destination(s). To alleviate the local minima issues that …

Go to article

Utilizing Microblogs For Improving Automatic News High-Lights Extraction, Zhongyu Wei, Wei Gao Aug 2014

Utilizing Microblogs For Improving Automatic News High-Lights Extraction, Zhongyu Wei, Wei Gao

Research Collection School Of Computing and Information Systems

Story highlights form a succinct single-document summary consisting of 3-4 highlight sentences that reflect the gist of a news article. Automatically producing news highlights is very challenging. We propose a novel method to improve news highlights extraction by using microblogs. The hypothesis is that microblog posts, although noisy, are not only indicative of important pieces of information in the news story, but also inherently “short and sweet” resulting from the artificial compression effect due to the length limit. Given a news article, we formulate the problem as two rank-then-extract tasks: (1) we find a set of indicative tweets and use …

Go to article

Guest Editorial: Special Issue On Brain Inspired Models Of Cognitive Memory, Huajin Tang, Kiruthika Ramanathan, Ning Nign Aug 2014

Guest Editorial: Special Issue On Brain Inspired Models Of Cognitive Memory, Huajin Tang, Kiruthika Ramanathan, Ning Nign

Research Collection School Of Computing and Information Systems

Current memory technologies have experienced significant progress in terms of storage capacity, operation speed, integration capability, etc. However, their functions are highly constrained in storing and transferring data in space and time, prompting the need for improvement. In contrast to physical memories, the biological counterpart – cognitive memory – has versatile functions. For instance, human memory stores data associatively such that different modalities of data could be retrieved simultaneously; it can learn different concepts, categorize and store them in an organized manner; it can process and store data concurrently and in a distributed fashion; it can restore content even if …

Go to article

Urban Planning Process: Can Technology Enhance Participatory Communication?, Rojin Vishkaie, Richard Levy, Anthony Tang Aug 2014

Urban Planning Process: Can Technology Enhance Participatory Communication?, Rojin Vishkaie, Richard Levy, Anthony Tang

Research Collection School Of Computing and Information Systems

Oftentimes, within the urban planning process, urban planners and GIS experts must work together using desktop Computer-Aided Design (CAD) and Geographic Information System (GIS). However, participatory communication and visualization which are important in the urban planning process, are not a central focus in the design of current computer-aided planning technologies. This study tends to provide an understanding of technological challenges and complexities urban planners and GIS experts encounter while engaging in a participatory environment during the urban planning process. This study also explores the perceptions of urban planners and GIS experts about the potential impact and usefulness of interactive surfaces …

Go to article

Direct Neighbor Search, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang Aug 2014

Direct Neighbor Search, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

In this paper we study a novel query type, called direct neighbor query. Two objects in a dataset are direct neighbors (DNs) if a window selection may exclusively retrieve these two objects. Given a source object, a DN search computes all of its direct neighbors in the dataset. The DNs define a new type of affinity that differs from existing formulations (e.g., nearest neighbors, nearest surrounders, reverse nearest neighbors, etc.) and finds application in domains where user interests are expressed in the form of windows, i.e., multi-attribute range selections. Drawing on key properties of the DN relationship, we develop an …

Go to article

Semantic Visualization For Spherical Representation, Tuan M. V. Le, Hady W. Lauw Aug 2014

Semantic Visualization For Spherical Representation, Tuan M. V. Le, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Visualization of high-dimensional data such as text documents is widely applicable. The traditional means is to find an appropriate embedding of the high-dimensional representation in a low-dimensional visualizable space. As topic modeling is a useful form of dimensionality reduction that preserves the semantics in documents, recent approaches aim for a visualization that is consistent with both the original word space, as well as the semantic topic space. In this paper, we address the semantic visualization problem. Given a corpus of documents, the objective is to simultaneously learn the topic distributions as well as the visualization coordinates of documents. We propose …

Go to article

Collaborative Online Multitask Learning, Guangxia Li, Steven C. H. Hoi, Kuiyu Chang, Wenting Liu, Ramesh Jain Aug 2014

Collaborative Online Multitask Learning, Guangxia Li, Steven C. H. Hoi, Kuiyu Chang, Wenting Liu, Ramesh Jain

Research Collection School Of Computing and Information Systems

We study the problem of online multitask learning for solving multiple related classification tasks in parallel, aiming at classifying every sequence of data received by each task accurately and efficiently. One practical example of online multitask learning is the micro-blog sentiment detection on a group of users, which classifies micro-blog posts generated by each user into emotional or non-emotional categories. This particular online learning task is challenging for a number of reasons. First of all, to meet the critical requirements of online applications, a highly efficient and scalable classification solution that can make immediate predictions with low learning cost is …

Go to article

First Prev Next Last