Physical Sciences and Mathematics Commons^™

Computing Inconsistency Measure Based On Paraconsistent Semantics, Pascal Hitzler, Yue Ma, Guilin Qi

Computer Science and Engineering Faculty Publications

Measuring inconsistency in knowledge bases has been recognized as an important problem in several research areas. Many methods have been proposed to solve this problem and a main class of them is based on some kind of paraconsistent semantics. However, existing methods suffer from two limitations: (i) they are mostly restricted to propositional knowledge bases; (ii) very few of them discuss computational aspects of computing inconsistency measures. In this article, we try to solve these two limitations by exploring algorithms for computing an inconsistency measure of first-order knowledge bases. After introducing a four-valued semantics for first-order logic, we define an …

Overview Of Contrast Data Mining As A Field And Preview Of An Upcoming Book, Guozhu Dong, James Bailey

Kno.e.sis Publications

This report provides an overview of the field of contrast data mining and its applications, and offers a preview of an upcoming book on the topic. The importance of contrasting is discussed and a brief survey is given covering the following topics: general definitions and terminology for contrast patterns, representative contrast pattern mining algorithms, applications of contrast mining for fundamental data mining tasks such as classification and clustering, applications of contrast mining in bioinformatics, medicine, blog analysis, image analysis and subgroup mining, results on contrast based dataset similarity measure, and on analyzing item interaction in contrast patterns, and open research …

An Effective Approach For Topicspecific Opinion Summarization, Binyang Li, Lanjun Zhou, Wei Gao, Kam-Fai Wong, Zhongyu Wei

Research Collection School Of Computing and Information Systems

Topic-specific opinion summarization (TOS) plays an important role in helping users digest online opinions, which targets to extract a summary of opinion expressions specified by a query, i.e. topic-specific opinionated information (TOI). A fundamental problem in TOS is how to effectively represent the TOI of an opinion so that salient opinions can be summarized to meet user’s preference. Existing approaches for TOS are either limited by the mismatch between topic-specific information and its corresponding opinionated information or lack of ability to measure opinionated information associated with different topics, which in turn affect the performance seriously. In this paper, we represent …

Four-Jet Final State Production In E+E- Collisions At Centre-Of-Mass Energies Of 130 And 136 Gev, D. Buskulic, M. Thulasidas

Research Collection School Of Computing and Information Systems

The four-jet final state is analyzed to search for hadronic decays of pair-produced heavy particles. The analysis uses the ALEPH data collected at LEP in November 1995 at centre-of-mass energies of 130 and 136 GeV, corresponding to a total integrated luminosity of 5.7 pb1 . An excess of four-jet events is observed with respect to the standard model predictions. In addition, these events exhibit an enhancement in the sum of the two di-jet masses around 105 GeV/c 2 . The properties of these events are studied and compared to the expectations from standard processes and to pair production hypotheses

Context-Based Friend Suggestion In Online Photo-Sharing Community, Ting Yao, Chong-Wah Ngo, Tao Mei

Research Collection School Of Computing and Information Systems

With the popularity of social media, web users tend to spend more time than before for sharing their experience and interest in online photo-sharing sites. The wide variety of sharing behaviors generate different metadata which pose new opportunities for the discovery of communities. We propose a new approach, named context-based friend suggestion, to leverage the diverse form of contextual cues for more effective friend suggestion in the social media community. Different from existing approaches, we consider both visual and geographical cues, and develop two user-based similarity measurements, i.e., visual similarity and geo similarity for characterizing user relationship. The problem of …

Consolidated Study On Query Expansion, Abhishek Biruduraju

UNLV Theses, Dissertations, Professional Papers, and Capstones

A typical day of million web users all over the world starts with a simple query. The quest for information on a particular topic drives them to search for it, and in the pursuit of their info the terms they supply for queries varies from person to person depending on the knowledge they have. With a vast collection of documents available on the web universe it is the onus of the retrieval system to return only those documents that are relevant and satisfy the user’s search requirements. The document mismatch problem is resolved by appending extra query terms to the …

Study Of Feature Selection Algorithms For Text-Categorization, Kandarp Dave

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis will discuss feature selection algorithms for text-categorization. Feature selection algorithms are very important, as they can make-or-break a categorization engine. The feature selection algorithms that will be discussed in this thesis are Document Frequency, Information Gain, Chi Squared, Mutual Information, NGL (Ng-Goh-Low) coefficient, and GSS (Galavotti-Sebastiani-Simi) coefficient . The general idea of any feature selection algorithm is to determine importance of words using some measure that can keep informative words, and remove non-informative words, which can then help the text-categorization engine categorize a document, D , into some category, C . These feature selection methods are explained, implemented, …

Parallel Machines Scheduling With Applications To Internet Ad-Slot Placement, Shaista Lubna

UNLV Theses, Dissertations, Professional Papers, and Capstones

We consider a class of problems of scheduling independent jobs on identical, uniform and unrelated parallel machines with an objective of achieving an optimal schedule. The primary focus is on the minimization of the maximum completion time of the jobs, commonly referred to as Makespan (C _max ). We survey and present examples of uniform machines and its applications to the single slot and multiple slots based on bids and budgets.

The Internet is an important advertising medium attracting large number of advertisers and users. When a user searches for a query, a search engine returns a set of results …

Wsm 2011: Third Acm Workshop On Social Media, Steven C. H. Hoi, Michal Jacovi, Ioannis Kompatsiaris, Jiebo Luo, Konstantinos Tserpes

Research Collection School Of Computing and Information Systems

The Third Workshop on Social Media (WSM2011) continues the series of Workshops on Social Media in 2009 and 2010 and has been established as a platform for the presentation and discussion of the latest, key research issues in social media analysis, exploration, search, mining, and emerging new social media applications. It is held in conjunction with the ACM International Multimedia Conference (MM'11) at Scottsdale, Arizona, USA, 2011 and has attracted contributions on various aspects of social media including data mining from social media, content organization, geo-localization, personalization, recommendation systems, user experience, machine learning and social media approaches and architectures for …

Determination Of Sin2Θeff W Using Jet Charge Measurements In Hadronic Z Decays, D. Buskulic, M. Thulasidas

Research Collection School Of Computing and Information Systems

The electroweak mixing angle is determined with high precision from measurements of the mean dierence between forward and backward hemisphere charges in hadronic decays of the Z. A data sample of 2:5 million hadronic Z decays recorded over the period 1990 to 1994 in the ALEPH detector at LEP is used. The mean charge separation between event hemispheres containing the original quark and antiquark is measured for b b and cc events in subsamples selected by their long lifetimes or using fast D 's. The corresponding average charge separation for light quarks is measured in an inclusive sample from the …

Modeling 3d Articulated Motions With Conformal Geometry Videos (Cgvs), Dao T. P. Quynh, Ying He, Xiaoming Chen, Jiazhi Xia, Qian Sun, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

3D articulated motions are widely used in entertainment, sports, military, and medical applications. Among various techniques for modeling 3D motions, geometry videos (GVs) are a compact representation in that each frame is parameterized to a 2D domain, which captures the 3D geometry (x, y, z) to a pixel (r, g, b) in the image domain. As a result, the widely studied image/video processing techniques can be directly borrowed for 3D motion. This paper presents conformal geometry videos (CGVs), a novel extension of the traditional geometry videos by taking into the consideration of the isometric nature of 3D articulated motions. We …

Understanding And Protecting Privacy: Formal Semantics And Principled Audit Mechanisms, Anupam Datta, Jeremiah Blocki, Nicolas Christin, Henry Deyoung, Deepak Garg, Limin Jia, Dilsun Kaynar, Arunesh Sinha

Research Collection School Of Computing and Information Systems

Privacy has become a significant concern in modern society as personal information about individuals is increasingly collected, used, and shared, often using digital technologies, by a wide range of organizations. Certain information handling practices of organizations that monitor individuals’ activities on the Web, data aggregation companies that compile massive databases of personal information, cell phone companies that collect and use location data about individuals, online social networks and search engines—while enabling useful services—have aroused much indignation and protest in the name of privacy. Similarly, as healthcare organizations are embracing electronic health record systems and patient portals to enable patients, employees, …

Vireo@Trecvid 2011: Instance Search, Semantic Indexing, Multimedia Event Detection And Known-Item Search, Chong-Wah Ngo, Shi-Ai Zhu, Wei Zhang, Chun-Chet Tan, Ting Yao, Lei Pang, Hung-Khoon Tan

Research Collection School Of Computing and Information Systems

The vireo group participated in four tasks: instance search, semantic indexing, multimedia event detection and known-item search. In this paper,we will present our approaches and discuss the evaluation results.

Retrieval-Based Face Annotation By Weak Label Regularized Local Coordinate Coding, Dayong Wang, Steven C. H. Hoi, Ying He, Jianke Zhu

Research Collection School Of Computing and Information Systems

Retrieval-based face annotation is a promising paradigm in mining massive web facial images for automated face annotation. Such an annotation paradigm usually encounters two key challenges. The first challenge is how to efficiently retrieve a short list of most similar facial images from facial image databases, and the second challenge is how to effectively perform annotation by exploiting these similar facial images and their weak labels which are often noisy and incomplete. In this paper, we mainly focus on tackling the second challenge of the retrieval-based face annotation paradigm. In particular, we propose an effective Weak Label Regularized Local Coordinate …

Processj: A Process-Oriented Programming Language, Matthew Sowders

UNLV Theses, Dissertations, Professional Papers, and Capstones

Java is a general purpose object-oriented programming language that has been widely adopted. Because of its high adoption rate and its lineage as a C-style language, its syntax is familiar to many programmers. The downside is that Java is not natively concurrent. Volumes have been written about concurrent programming in Java; however, concurrent programming is difficult to reason about within an object-oriented paradigm and so is difficult to get right.

occam -π is a general purpose process-oriented programming language. Concurrency is part of the theoretical underpinnings of the language. Concurrency is simple to reason about within an occam -π application …

Modeling Social Strength In Social Media Community Via Kernel-Based Learning, Jinfeng Zhuang, Tao Mei, Steven C. H. Hoi, Xian-Sheng Hua, Shipeng Li

Research Collection School Of Computing and Information Systems

Modeling continuous social strength rather than conventional binary social ties in the social network can lead to a more precise and informative description of social relationship among people. In this paper, we study the problem of social strength modeling (SSM) for the users in a social media community, who are typically associated with diverse form of data. In particular, we take Flickr---the most popular online photo sharing community---as an example, in which users are sharing their experiences through substantial amounts of multimodal contents (e.g., photos, tags, geo-locations, friend lists) and social behaviors (e.g., commenting and joining interest groups). Such heterogeneous …

The Valuation Of User-Generated Content: A Structural, Stylistic And Semantic Analysis Of Online Reviews, Noi Sian Koh

Dissertations and Theses Collection (Open Access)

The ability and ease for users to create and publish content has provided vast amount of online product reviews. However, the amount of data is overwhelmingly large and unstructured, making information difficult to quantify. This creates challenge in understanding how online reviews affect consumers’ purchase decisions. In my dissertation, I explore the structural, stylistic and semantic content of online reviews. Firstly, I present a measurement that quantifies sentiments with respect to a multi-point scale and conduct a systematic study on the impact of online reviews on product sales. Using the sentiment metrics generated, I estimate the weight that customers place …

Quantifying Computer Network Security, Ian Burchett

Masters Theses & Specialist Projects

Simplifying network security data to the point that it is readily accessible and usable by a wider audience is increasingly becoming important, as networks become larger and security conditions and threats become more dynamic and complex, requiring a broader and more varied security staff makeup. With the need for a simple metric to quantify the security level on a network, this thesis proposes: simplify a network’s security risk level into a simple metric. Methods for this simplification of an entire network’s security level are conducted on several characteristic networks. Identification of computer network port vulnerabilities from NIST’s Network Vulnerability Database …

Sire: A Social Image Retrieval Engine, Steven C. H. Hoi, Pengcheng Wu

Research Collection School Of Computing and Information Systems

With the explosive growth of social media applications on the internet, billions of social images have been made available in many social media web sites nowadays. This has presented an open challenge of web-scale social image search. Unlike existing commercial web search engines that often adopt text based retrieval, in this demo, we present a novel web-based multimodal paradigm for large-scale social image retrieval, termed "Social Image Retrieval Engine" (SIRE), which effectively exploits both textual and visual contents to narrow down the semantic gap between high-level concepts and low-level visual features. A relevance feedback mechanism is also equipped to learn …

Tag-Based Social Image Search With Visual-Text Joint Hypergraph Learning, Yue Gao, Meng Wang, Huanboo Luan, Jialie Shen, Shuicheng Yan, Dacheng Tao

Research Collection School Of Computing and Information Systems

Tag-based social image search has attracted great interest and how to order the search results based on relevance level is a research problem. Visual content of images and tags have both been investigated. However, existing methods usually employ tags and visual content separately or sequentially to learn the image relevance. This paper proposes a tag-based image search with visual-text joint hypergraph learning. We simultaneously investigate the bag-of-words and bag-of-visual-words representations of images and accomplish the relevance estimation with a hypergraph learning approach. Each textual or visual word generates a hyperedge in the constructed hypergraph. We conduct experiments with a real-world …

Efficient Mining Of Iterative Patterns For Software Specification Discovery, David Lo, Siau-Cheng Khoo, Chao Liu

David LO

Studies have shown that program comprehension takes up to 45% of software development costs. Such high costs are caused by the lack-of documented specification and further aggravated by the phenomenon of software evolution. There is a need for automated tools to extract specifications to aid program comprehension. In this paper, a novel technique to efficiently mine common software temporal patterns from traces is proposed. These patterns shed light on program behaviors, and are termed iterative patterns. They capture unique characteristic of software traces, typically not found in arbitrary sequences. Specifically, due to loops, interesting iterative patterns can occur multiple times …

Smartic: Specification Mining Architecture With Trace Filtering And Clustering, David Lo, Siau-Cheng Khoo

David LO

Improper management of software evolution, compounded by imprecise, and changing requirements, along with the "short time to market" requirement, commonly leads to a lack of up-to-date specifications. This can result in software that is characterized by bugs, anomalies and even security threats. Software specification mining is a new technique to address this concern by inferring specifications automatically. In this paper, we propose a novel API specification mining architecture called SMArTIC Specification Mining Architecture with Trace fIltering and Clustering) to improve the accuracy, robustness and scalability of specification miners. This architecture is constructed based on two hypotheses: (1) Erroneous traces should …

Mining Software Specifications, David Lo, Siau-Cheng Khoo

David LO

No abstract provided.

Matching Dependence-Related Queries In The System Dependence Graph., Xiaoyin Wang, David Lo, Jiefeng Cheng, Lu Zhang, Hong Mei, Jeffrey Xu Yu

David LO

In software maintenance and evolution, it is common that developers want to apply a change to a number of similar places. Due to the size and complexity of the code base, it is challenging for developers to locate all the places that need the change. A main challenge in locating the places that need the change is that, these places share certain common dependence conditions but existing code searching techniques can hardly handle dependence relations satisfactorily. In this paper, we propose a technique that enables developers to make queries involving dependence conditions and textual conditions on the system dependence graph …

Mining Iterative Generators And Representative Rules For Software Specification Discovery, David Lo, Jinyan Li, Limsoon Wong, Siau-Cheng Khoo

David LO

Billions of dollars are spent annually on software-related cost. It is estimated that up to 45 percent of software cost is due to the difficulty in understanding existing systems when performing maintenance tasks (i.e., adding features, removing bugs, etc.). One of the root causes is that software products often come with poor, incomplete, or even without any documented specifications. In an effort to improve program understanding, Lo et al. have proposed iterative pattern mining which outputs patterns that are repeated frequently within a program trace, or across multiple traces, or both. Frequent iterative patterns reflect frequent program behaviors that likely …

Mining Past-Time Temporal Rules: A Dynamic Analysis Approach, David Lo, Siau-Cheng Khoo, Chao Liu

David LO

No abstract provided.

Mining Antagonistic Communities From Social Networks, Kuan Zhang, David Lo, Ee Peng Lim

David LO

During social interactions in a community, there are often sub-communities that behave in opposite manner. These antagonistic sub-communities could represent groups of people with opposite tastes, factions within a community distrusting one another, etc. Taking as input a set of interactions within a community, we develop a novel pattern mining approach that extracts for a set of antagonistic sub-communities. In particular, based on a set of user specified thresholds, we extract a set of pairs of sub-communities that behave in opposite ways with one another. To prevent a blow up in these set of pairs, we focus on extracting a …

Efficient Mining Of Recurrent Rules From A Sequence Database, David Lo, Siau-Cheng Khoo, Chao Liu

David LO

We study a novel problem of mining significant recurrent rules from a sequence database. Recurrent rules have the form "whenever a series of precedent events occurs, eventually a series of consequent events occurs". Recurrent rules are intuitive and characterize behaviors in many domains. An example is in the domain of software specifications, in which the rules capture a family of program properties beneficial to program verification and bug detection. Recurrent rules generalize existing work on sequential and episode rules by considering repeated occurrences of premise and consequent events within a sequence and across multiple sequences, and by removing the "window" …

Efficient Topological Olap On Information Networks, Qiang Qu, Feida Zhu, Xifeng Yan, Jiawei Han, Philip Yu, Hongyan Li

David LO

We propose a framework for efficient OLAP on information networks with a focus on the most interesting kind, the topological OLAP (called “T-OLAP”), which incurs topological changes in the underlying networks. T-OLAP operations generate new networks from the original ones by rolling up a subset of nodes chosen by certain constraint criteria. The key challenge is to efficiently compute measures for the newly generated networks and handle user queries with varied constraints. Two effective computational techniques, T-Distributiveness and T-Monotonicity are proposed to achieve efficient query processing and cube materialization. We also provide a T-OLAP query processing framework into which these …

Comprehensive Evaluation Of Association Measures For Fault Localization, Lucia Lucia, David Lo, Lingxiao Jiang, Aditya Budi

David LO

In statistics and data mining communities, there have been many measures proposed to gauge the strength of association between two variables of interest, such as odds ratio, confidence, Yule-Y, Yule-Q, Kappa, and gini index. These association measures have been used in various domains, for example, to evaluate whether a particular medical practice is associated positively to a cure of a disease or whether a particular marketing strategy is associated positively to an increase in revenue, etc. This paper models the problem of locating faults as association between the execution or non-execution of particular program elements with failures. There have been …