Databases and Information Systems Commons^™

A Modular Kernel Linear Discriminant Analysis Of Gabor Features For Improved Face Recognition, Neeharika Gudur

Electrical & Computer Engineering Theses & Dissertations

Automatic face recognition is one of the major challenges in computer vision and pattern analysis. This thesis presents an efficient face recognition system that is robust with regards to changes in illumination, facial expressions and partial occlusions. Modular Kernel Linear Discriminant Analysis performed on Gabor Features obtained from the face images is employed for improving face recognition accuracy. A face image is pre-processed using the 2D Gabor wavelet transform to achieve invariance to illumination in images. Modular approaches that divide the pre-processed images into smaller sub-images provide improved accuracy, as the facial variations in an image are confined to local …

Neighborhood Defined Adaboost Based Mixture Of Color Components For Efficient Skin Segmentation, Ramya Reddy Maaram

Electrical & Computer Engineering Theses & Dissertations

A skin segmentation algorithm robust to illumination changes and skin-like backgrounds is developed in this thesis. So far skin pixel classification has been limited to only individual color spaces and there has not been a comprehensive evaluation of which color components or combination of color components would provide the best classification accuracy, Color components in a given color space form the feature set for the classification of skin pixels. The combination of the color components or the features present within a single color space may not be the best when it comes to skin pixel classification as the discriminatory power …

Product Complexity: A Definition And Impacts On Operations, Mark A. Jacobs

MIS/OM/DS Faculty Publications

The difficulty for organizations arises because neither complexity nor its impacts on performance are well understood (Fisher & Ittner, 1999b). The mechanisms through which it affects cost, quality, delivery, and flexibility need to be explained (Ramdas, 2003). However, this cannot happen until complexity can be explained theoretically. But, to build theory there must first be a common understanding about the construct of interest (Wacker, 2004). Only then can researchers operationalize it and search for meaningful relationships. In light of this, I develop a definition of complexity below. A sampling of the operations management literature is then presented within the context …

A Multitude Of Opinions: Mining Online Rating Data, Hady Wirawan Lauw, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Online rating system is a popular feature of Web 2.0 applications. It typically involves a set of reviewers assigning rating scores (based on various evaluation criteria) to a set of objects. We identify two objectives for research on online rating data, namely achieving effective evaluation of objects and learning behaviors of reviewers/objects. These two objectives have conventionally been pursued separately. We argue that the future research direction should focus on the integration of these two objectives, as well as the integration between rating data and other types of data.

Analyzing Service Usage Patterns: Methodology And Simulation, Qianhui (Althea) Liang, Jen-Yao Chung

Research Collection School Of Computing and Information Systems

This paper proposes that service mining technology will power the construction of new business services via both intra- and inter-enterprise service assembly within the Service Oriented Architecture (SOA) framework. We investigate the methodologies of service mining at the component level of service usage. We also demonstrate how mining of service usage patterns is intended to be used to improve different aspects of service composition. Simulation experiments conducted for mining at the component level are analyzed. The processing details within a general service mining deployment are demonstrated.

Om-Based Video Shot Retrieval By One-To-One Matching, Yuxin Peng, Chong-Wah Ngo, Jianguo Xiao

Research Collection School Of Computing and Information Systems

This paper proposes a new approach for shot-based retrieval by optimal matching (OM), which provides an effective mechanism for the similarity measure and ranking of shots by one-to-one matching. In the proposed approach, a weighted bipartite graph is constructed to model the color similarity between two shots. Then OM based on Kuhn-Munkres algorithm is employed to compute the maximum weight of a constructed bipartite graph as the shot similarity value by one-to-one matching among frames. To improve the speed efficiency of OM, two improved algorithms are also proposed: bipartite graph construction based on subshots and bipartite graph construction based on …

I Tube, You Tube, Everybody Tubes: Analyzing The World’S Largest User Generated Content Video System, Meeyoung Cha, Haewoon Kwak, Pablo Rodriguez, Yong-Yeol Ahn, Sue. Moon

Research Collection School Of Computing and Information Systems

User Generated Content (UGC) is re-shaping the way people watch video and TV, with millions of video producers and consumers. In particular, UGC sites are creating new viewing patterns and social interactions, empowering users to be more creative, and developing new business opportunities. To better understand the impact of UGC systems, we have analyzed YouTube, the world's largest UGC VoD system. Based on a large amount of data collected, we provide an in-depth study of YouTube and other similar UGC systems. In particular, we study the popularity life-cycle of videos, the intrinsic statistical properties of requests and their relationship with …

Gapprox: Mining Frequent Approximate Patterns From A Massive Network, Chen Chen, Xifeng Yan, Feida Zhu, Jiawei Han

Research Collection School Of Computing and Information Systems

Recently, there arise a large number of graphs with massive sizes and complex structures in many new applications, such as biological networks, social networks, and the Web, demanding powerful data mining methods. Due to inherent noise or data diversity, it is crucial to address the issue of approximation, if one wants to mine patterns that are potentially interesting with tolerable variations. In this paper, we investigate the problem of mining frequent approximate patterns from a massive network and propose a method called gApprox. gApprox not only finds approximate network patterns, which is the key for many knowledge discovery applications on …

Efficient Discovery Of Frequent Approximate Sequential Patterns, Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu

Research Collection School Of Computing and Information Systems

We propose an efficient algorithm for mining frequent approximate sequential patterns under the Hamming distance model. Our algorithm gains its efficiency by adopting a "break-down-and-build-up" methodology. The "breakdown" is based on the observation that all occurrences of a frequent pattern can be classified into groups, which we call strands. We developed efficient algorithms to quickly mine out all strands by iterative growth. In the "build-up" stage, these strands are grouped up to form the support sets from which all approximate patterns would be identified. A salient feature of our algorithm is its ability to grow the frequent patterns by iteratively …

Realizing The Relationship Web: Morphing Information Access On The Web From Today's Document- And Entity-Centric Paradigm To A Relationship-Centric Paradigm, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Description Logic Programs: Normal Forms, Pascal Hitzler, Andreas Eberhart

Computer Science and Engineering Faculty Publications

The relationship and possible interplay between different knowledge representation and reasoning paradigms is a fundamental topic in artificial intelligence. For expressive knowledge representation for the Semantic Web, two different paradigms - namely Description Logics (DLs) and Logic Programming - are the two most successful approaches. A study of their exact relationships is thus paramount. An intersection of OWL with (function-free non-disjunctive) Datalog, called DLP (for Description Logic Programs), has been described in [1,2]. We provide normal forms for DLP in Description Logic syntax and in Datalog syntax, thus providing a bridge for the researcher and user who is familiar with …

Comparing Disjunctive Well-Founded Semantics, Matthias Knorr, Pascal Hitzler

Computer Science and Engineering Faculty Publications

While the stable model semantics, in the form of Answer Set Programming, has become a successful semantics for disjunctive logic programs, a corresponding satisfactory extension of the well-founded semantics to disjunctive programs remains to be found. The many current proposals for such an extension are so diverse, that even a systematic comparison between them is a challenging task. In order to aid the quest for suitable disjunctive well-founded semantics, we present a systematic approach to a comparison based on level mappings, a recently introduced framework for characterizing logic programming semantics, which was quite successfully used for comparing the major semantics …

Any-World Access To Owl From Prolog, Tobias Matzner, Pascal Hitzler

Computer Science and Engineering Faculty Publications

The W3C standard OWL provides a decidable language for representing ontologies. While its use is rapidly spreading, efforts are being made by researchers worldwide to augment OWL with additional expressive features or by interlacing it with other forms of knowledge representation, in order to make it applicable for even further purposes. In this paper, we integrate OWL with one of the most successful and most widely used forms of knowledge representation, namely Prolog, and present a hybrid approach which layers Prolog on top of OWL in such a way that the open-world semantics of OWL becomes directly accessible within the …

The Programmable Web: Agile, Social, And Grassroots Computing, E. Michael Maximilien, Ajith Harshana Ranabahu

Kno.e.sis Publications

Web services, the semantic Web, and Web 2.0 are three somewhat separate movements trying to make the Web a programmable substrate. While each has achieved some level of success on their own right, it is becoming apparent that the grassroots approach of the Web 2.0 is gaining greater success than the other two. In this paper we analyze each movement, briefly describing its main traits, and outlining its primary assumptions. We then frame the common problem of achieving a programmable Web within the context of distributed computing and software engineering and then attempt to show why Web 2.0 is closest …

Sa-Rest And (S)Mashups: Adding Semantics To Restful Services, Jonathan Lathem, Karthik Gomadam, Amit P. Sheth

Kno.e.sis Publications

The evolution of the Web 2.0 phenomenon has led to the increased adoption of the RESTful services paradigm. RESTful services often take the form of RSS/Atom feeds and AJAX based light weight services. The XML based messaging paradigm of RESTful services has made it possible to compose various services together. Such compositions of RESTful services is widely referred to as Mashups. In this paper, we outline the limitations in current approaches to creating mashups. We address these limitations by proposing a framework called as SA-REST. SA-REST adds semantics to RESTful services. Our proposed framework builds upon the original ideas in …

A Survey Of Schema Matching Research, Roger Blake

College of Management Working Papers and Reports

Schema matching is the process of developing semantic matches between two or more schemas. The purpose of schema matching is generally either to merge two or more databases, or to enable queries on multiple, heterogeneous databases to be formulated on a single schema (Doan and Halevy 2005). This paper develops a taxonomy of schema matching approaches, classifying them as being based on a combination schema matching technique and the type of data used by those techniques. Schema matching techniques are categorized as being based on rules, learning, or ontology, and the type of data used is categorized as being based …

Evolutionary Combinatorial Optimization For Recursive Supervised Learning With Clustering, Kiruthika Ramanathan, Sheng Uei Guan

Research Collection School Of Computing and Information Systems

The idea of using a team of weak learners to learn a dataset is a successful one in literature. In this paper, we explore a recursive incremental approach to ensemble learning. In this paper, patterns are clustered according to the output space of the problem, i.e., natural clusters are formed based on patterns belonging to each class. A combinatorial optimization problem is therefore formed, which is solved using evolutionary algorithms. The evolutionary algorithms identify the "easy" and the "difficult" clusters in the system. The removal of the easy patterns then gives way to the focused learning of the more complicated …

The Future Of Information Systems Engineering, Keng Siau

Research Collection School Of Computing and Information Systems

No abstract provided.

Overview Of The Imageclef 2007 Object Retrieval Task, Thomas Deselaers, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

We describe the object retrieval task of ImageCLEF 2007, give an overview of the methods of the participating groups, and present and discuss the results. The task was based on the widely used PASCAL object recognition data to train object recognition methods and on the IAPR TC-12 benchmark dataset from which images of objects of the ten different classes bicycles, buses, cars, motorbikes, cats, cows, dogs, horses, sheep, and persons had to be retrieved. Seven international groups participated using a wide variety of methods. The results of the evaluation show that the task was very challenging and that different methods …

Cross-Language And Cross-Media Image Retrieval: An Empirical Study At Imageclef2007, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

This paper summarizes our empirical study of cross-language and cross-media image retrieval at the CLEF image retrieval track (ImageCLEF2007). In this year, we participated in the ImageCLEF photo retrieval task, in which the goal of the retrieval task is to search natural photos by some query with both textual and visual information. In this paper, we study the empirical evaluations of our solutions for the image retrieval tasks in three aspects. First of all, we study the application of language models and smoothing strategies for text-based image retrieval, particularly addressing the short text query issue. Secondly, we study the cross-media …

Column Heterogeneity As A Measure Of Data Quality, Bing Tian Dai, Nick Koudas, Beng Chin Ooi, Divesh Srivastava, Suresh Venkatasubramanian

Research Collection School Of Computing and Information Systems

Data quality is a serious concern in every data management application, and a variety of quality measures have been proposed, including accuracy, freshness and completeness, to capture the common sources of data quality degradation. We identify and focus attention on a novel measure, column heterogeneity, that seeks to quantify the data quality problems that can arise when merging data from different sources. We identify desiderata that a column heterogeneity measure should intuitively satisfy, and discuss a promising direction of research to quantify database column heterogeneity based on using a novel combination of cluster entropy and soft clustering. Finally, we present …

Ntu: Solution For The Object Retrieval Task Of The Imageclef2007, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Object retrieval is an interdisciplinary research problem between object recognition and content-based image retrieval (CBIR). It is commonly expected that object retrieval can be solved more effectively with the joint maximization of CBIR and object recognition techniques. We study a typical CBIR solution with application to the object retrieval tasks [26,27]. We expect that the empirical study in this work will serve as a baseline for future research when using CBIR techniques for object recognition.

Who’S Creating?, M. Thulasidas

Research Collection School Of Computing and Information Systems

We don’t read to retain information or knowledge any more. We search, scan, locate keywords, browse and bookmark. The Internet is doing to our reading habits what the calculator did to our arithmetic abilities. Knowledge is not cheap, although our easy access to it through the Internet may indicate otherwise. When we all become users of information, our knowledge will stop at its current level because nobody will be creating it any more.

Mobile Information Communication Technology For Crisis Management : Understanding User Behavior, Response And Training, Elizabeth Avery Gomez

Dissertations

SMS text-messaging is an interoperable communication vehicle known to be dependable for mass media alert notifications in crisis management. SMS text-messaging also offers potential as one viable two-way communication alternative for field responders in crisis response. Both continuously changing mobile information communication technologies and the importance of precise information exchange constitute a need for communication protocol training and practice. This study introduces a technology-mediated training technique based on speech act and communicative action theories. These theories are used to inform the design of a baseline measure for task performance improvement and to suggest a model to predict communication readiness. Because …

Designing Multimodal Interaction For The Visually Impaired, Xiaoyu Chen

Dissertations

Although multimodal computer input is believed to have advantages over unimodal input, little has been done to understand how to design a multimodal input mechanism to facilitate visually impaired users' information access.

This research investigates sighted and visually impaired users' multimodal interaction choices when given an interaction grammar that supports speech and touch input modalities. It investigates whether task type, working memory load, or prevalence of errors in a given modality impact a user's choice. Theories in human memory and attention are used to explain the users' speech and touch input coordination.

Among the abundant findings from this research, the …

Sensor Data Management, Cory Andrew Henson

Kno.e.sis Publications

No abstract provided.

Research On Multi-Agent-Based Shipping Information System, Kai Wang

World Maritime University Dissertations

No abstract provided.

Csi Revisited: The Science Of Forensic Dna Analysis, Michael L. Raymer

Kno.e.sis Publications

No abstract provided.

Trailblazing, Complex Hypothesis Evaluation, Abductive Reasoning And Semantic Web - Exploring Possible Synergy, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Relationship Web: Spinning The Semantic Web From Trailblazing To Complex Hypothesis Evaluation, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.