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Articles 1 - 30 of 352
Full-Text Articles in Databases and Information Systems
Investigating The Spatial Complexity Of Various Pke-Peks Schematics, Jacob Patterson
Investigating The Spatial Complexity Of Various Pke-Peks Schematics, Jacob Patterson
Rose-Hulman Undergraduate Research Publications
With the advent of cloud storage, people upload all sorts of information to third party servers. However, uploading plaintext does not seem like a good idea for users who wish to keep their data private. Current solutions to this problem in literature involves integrating Public Key Encryption and Public key encryption with keyword search techniques. The intent of this paper is to analyze the spatial complexities of various PKE-PEKS schemes at various levels of security and discuss potential avenues for improvement.
Handling Relationships In A Wiki System, Yashi Kamboj
Handling Relationships In A Wiki System, Yashi Kamboj
Master's Projects
Wiki software enables users to manage content on the web, and create or edit web pages freely. Most wiki systems support the creation of hyperlinks on pages and have a simple text syntax for page formatting. A common, more advanced feature is to allow pages to be grouped together as categories. Currently, wiki systems support categorization of pages in a very traditional way by specifying whether a wiki page belongs to a category or not. Categorization represents unary relationship and is not sufficient to represent n-ary relationships, those involving links between multiple wiki pages.
In this project, we extend Yioop, …
Predicting User's Future Requests Using Frequent Patterns, Marc Nipuna Dominic Savio
Predicting User's Future Requests Using Frequent Patterns, Marc Nipuna Dominic Savio
Master's Projects
In this research, we predict User's Future Request using Data Mining Algorithm. Usage of the World Wide Web has resulted in a huge amount of data and handling of this data is getting hard day by day. All this data is stored as Web Logs and each web log is stored in a different format with different Field names like search string, URL with its corresponding timestamp, User ID’s that helps for session identification, Status code, etc. Whenever a user requests for a URL there is a delay in getting the page requested and sometimes the request is denied. Our …
Deep Data Analysis On The Web, Xuanyu Liu
Deep Data Analysis On The Web, Xuanyu Liu
Master's Projects
Search engines are well known to people all over the world. People prefer to use keywords searching to open websites or retrieve information rather than type typical URLs. Therefore, collecting finite sequences of keywords that represent important concepts within a set of authors is important, in other words, we need knowledge mining. We use a simplicial concept method to speed up concept mining. Previous CS 298 project has studied this approach under Dr. Lin. This method is very fast, for example, to mine the concept, FP-growth takes 876 seconds from a database with 1257 columns 65k rows, simplicial complex only …
Spatial Data Mining Analytical Environment For Large Scale Geospatial Data, Zhao Yang
Spatial Data Mining Analytical Environment For Large Scale Geospatial Data, Zhao Yang
LSU New Orleans Theses and Dissertations
Nowadays, many applications are continuously generating large-scale geospatial data. Vehicle GPS tracking data, aerial surveillance drones, LiDAR (Light Detection and Ranging), world-wide spatial networks, and high resolution optical or Synthetic Aperture Radar imagery data all generate a huge amount of geospatial data. However, as data collection increases our ability to process this large-scale geospatial data in a flexible fashion is still limited. We propose a framework for processing and analyzing large-scale geospatial and environmental data using a “Big Data” infrastructure. Existing Big Data solutions do not include a specific mechanism to analyze large-scale geospatial data. In this work, we extend …
Web-Based Integrated Development Environment, Hien T. Vu
Web-Based Integrated Development Environment, Hien T. Vu
Master's Projects
As tablets become more powerful and more economical, students are attracted to them and are moving away from desktops and laptops. Their compact size and easy to use Graphical User Interface (GUI) reduce the learning and adoption barriers for new users. This also changes the environment in which undergraduate Computer Science students learn how to program. Popular Integrated Development Environments (IDE) such as Eclipse and NetBeans require disk space for local installations as well as an external compiler. These requirements cannot be met by current tablets and thus drive the need for a web-based IDE. There are also many other …
Aiddata Gis International Fellowship: Ghana West-Africa, Jason N. Ready
Aiddata Gis International Fellowship: Ghana West-Africa, Jason N. Ready
Sustainability and Social Justice
My internship, or fellowship as it was commonly referred to, was funded by a non-profit organization out of Williamsburg Virginia called AidData. This fellowship took place in in the country of Ghana, West-Africa beginning in May of 2016 and continued for 14 weeks with 40 hours each week. The objective of this internship was to provide in-depth training on the use of geographic Information Systems to Private and Public sectors within the country to allow for increased efficiency, and transparency through data visualization. In accordance with the requirement of Clark Universities GISDE master’s program this paper will delve into the …
A System For Detecting Malicious Insider Data Theft In Iaas Cloud Environments, Jason Nikolai, Yong Wang
A System For Detecting Malicious Insider Data Theft In Iaas Cloud Environments, Jason Nikolai, Yong Wang
Research & Publications
The Cloud Security Alliance lists data theft and insider attacks as critical threats to cloud security. Our work puts forth an approach using a train, monitor, detect pattern which leverages a stateful rule based k-nearest neighbors anomaly detection technique and system state data to detect inside attacker data theft on Infrastructure as a Service (IaaS) nodes. We posit, instantiate, and demonstrate our approach using the Eucalyptus cloud computing infrastructure where we observe a 100 percent detection rate for abnormal login events and data copies to outside systems.
Implementation And Testing Of A Book Lookup System For The Robert E. Kennedy Library, Casey C. Sheehan
Implementation And Testing Of A Book Lookup System For The Robert E. Kennedy Library, Casey C. Sheehan
Computer Science and Software Engineering
The goal of this senior project centered around improving the quality of student and teacher experiences when visiting the library. The task of finding a book amongst the shelves is an arduous one, which I felt could be improved upon through implementation and testing of a Book Lookup system for the Cal Poly Robert E. Kennedy Library. Development for this project was done using a Python framework. Testing and earlier designs were also created using JavaScript and PHP. Repeated tests were conducted on the accuracy of the software and its ability to decrease user search-time when compared to conventional methods.
Designing A Datawarehousing And Business Analytics Course Using Experiential Learning Pedagogy, Gottipati Swapna, Venky Shankararaman
Designing A Datawarehousing And Business Analytics Course Using Experiential Learning Pedagogy, Gottipati Swapna, Venky Shankararaman
Research Collection School Of Computing and Information Systems
Experiential learning refers to learning from experience or learning by doing. Universities have explored various forms for implementing experiential learning such as apprenticeships, internships, cooperative education, practicums, service learning, job shadowing, fellowships and community activities. However, very little has been done in systematically trying to integrate experiential learning to the main stream academic curriculum. Over the last two years, at the authors’ university, a new program titled UNI-X was launched to achieve this. Combining academic curriculum with experiential learning pedagogy, provides a challenging environment for students to use their disciplinary knowledge and skills to tackle real world problems and issues …
Applying Ahp And Clustering Approaches For Public Transportation Decisionmaking: A Case Study Of Isfahan City, Alireza Salavati, Hossein Haghshenas, Bahador Ghadirifaraz, Jamshid Laghaei, Ghodrat Eftekhari
Applying Ahp And Clustering Approaches For Public Transportation Decisionmaking: A Case Study Of Isfahan City, Alireza Salavati, Hossein Haghshenas, Bahador Ghadirifaraz, Jamshid Laghaei, Ghodrat Eftekhari
Journal of Public Transportation
The main purpose of this paper is to define appropriate criteria for the systematic approach to evaluate and prioritize multiple candidate corridors for public transport investment simultaneously to serve travel demand, regarding supply of current public transportation system and road network conditions of Isfahan, Iran. To optimize resource allocation, policymakers need to identify proper corridors to implement a public transportation system. In fact, the main question is to adopt the best public transportation system for each main corridor of Isfahan. In this regard, 137 questionnaires were completed by experts, directors, and policymakers of Isfahan to identify goals and objectives in …
Preliminary Investigation Of Walking Motion Using A Combination Of Image And Signal Processing, Bradley Schneider, Tanvi Banerjee
Preliminary Investigation Of Walking Motion Using A Combination Of Image And Signal Processing, Bradley Schneider, Tanvi Banerjee
Kno.e.sis Publications
We present the results of analyzing gait motion in first-person video taken from a commercially available wearable camera embedded in a pair of glasses. The video is analyzed with three different computer vision methods to extract motion vectors from different gait sequences from four individuals for comparison against a manually annotated ground truth dataset. Using a combination of signal processing and computer vision techniques, gait features are extracted to identify the walking pace of the individual wearing the camera as well as validated using the ground truth dataset. Our preliminary results indicate that the extraction of activity from the video …
Towards Building A Review Recommendation System That Trains Novices By Leveraging The Actions Of Experts, Shilpa Khanal
Towards Building A Review Recommendation System That Trains Novices By Leveraging The Actions Of Experts, Shilpa Khanal
School of Computing: Dissertations, Theses, and Student Research
Online reviews increase consumer visits, increase the time spent on the website, and create a sense of community among the frequent shoppers. Because of the importance of online reviews, online retailers such as Amazon.com and eOpinions provide detailed guidelines for writing reviews. However, though these guidelines provide instructions on how to write reviews, reviewers are not provided instructions for writing product-specific reviews. As a result, poorly-written reviews are abound and a customer may need to scroll through a large number of reviews, which could be up to 6000 pixels down from the top of the page, in order to find …
The Development Of An Automated Testing Framework For Data-Driven Testing Utilizing The Uml Testing Profile, James Edward Hearn
The Development Of An Automated Testing Framework For Data-Driven Testing Utilizing The Uml Testing Profile, James Edward Hearn
Masters Theses & Doctoral Dissertations
The development of increasingly-complex Web 2.0 applications, along with a rise in end-user expectations, have not only made the testing and quality assurance processes of web application development an increasingly-important part of the SDLC, but have also made these processes more complex and resource-intensive. One way to effectively test these applications is by implementing an automated testing solution along with manual testing, as automation solutions have been shown to increase the total amount of testing that can be performed, and help testing team achieve consistency in their testing efforts. The difficulty, though, lies in how to best go about developing …
Ios Application For Inventory In Small Retail Stores, Andrea Savage
Ios Application For Inventory In Small Retail Stores, Andrea Savage
Computer Science and Software Engineering
Currently, small retail stores with low technology budgets such as those right here in San Luis Obispo are struggling to integrate new technologies into their companies. This mobile application built for iOS with a Firebase backend is seeking to remove their barriers to entry. I built this application to give small retail stores a customizable application that allows them to display products electronically to customers and maintain accurate inventory both in one place. The construction of this application hinged around three major design decisions: UI design of the color management views, organization of the database, and accessing the database with …
Cryptographic Reverse Firewall Via Malleable Smooth Projective Hash Functions, Rongmao Chen, Guomin Yang, Guomin Yang, Willy Susilo, Fuchun Guo, Mingwu Zhang
Cryptographic Reverse Firewall Via Malleable Smooth Projective Hash Functions, Rongmao Chen, Guomin Yang, Guomin Yang, Willy Susilo, Fuchun Guo, Mingwu Zhang
Research Collection School Of Computing and Information Systems
Motivated by the revelations of Edward Snowden, postSnowden cryptography has become a prominent research direction in recent years. In Eurocrypt 2015, Mironov and Stephens-Davidowitz proposed a novel concept named cryptographic reverse firewall (CRF) which can resist exfiltration of secret information from an arbitrarily compromised machine. In this work, we continue this line of research and present generic CRF constructions for several widely used cryptographic protocols based on a new notion named malleable smooth projective hash function. Our contributions can be summarized as follows. – We introduce the notion of malleable smooth projective hash function, which is an extension of the …
Validating Social Media Data For Automatic Persona Generation, Jisun An, Haewoon Kwak, Bernard J Jansen
Validating Social Media Data For Automatic Persona Generation, Jisun An, Haewoon Kwak, Bernard J Jansen
Research Collection School Of Computing and Information Systems
Using personas during interactive design has considerable potential for product and content development. Unfortunately, personas have typically been a fairly static technique. In this research, we validate an approach for creating personas in real time, based on analysis of actual social media data in an effort to automate the generation of personas. We validate that social media data can be implemented as an approach for automating generating personas in real time using actual YouTube social media data from a global media corporation that produces online digital content. Using the organization's YouTube channel, we collect demographic data, customer interactions, and topical …
Zero++: Harnessing The Power Of Zero Appearances To Detect Anomalies In Large-Scale Data Sets, Guansong Pang, Kai Ming Ting, David Albrecht, Huidong Jin
Zero++: Harnessing The Power Of Zero Appearances To Detect Anomalies In Large-Scale Data Sets, Guansong Pang, Kai Ming Ting, David Albrecht, Huidong Jin
Research Collection School Of Computing and Information Systems
This paper introduces a new unsupervised anomaly detector called ZERO++ which employs the number of zero appearances in subspaces to detect anomalies in categorical data. It is unique in that it works in regions of subspaces that are not occupied by data; whereas existing methods work in regions occupied by data. ZERO++ examines only a small number of low dimensional subspaces to successfully identify anomalies. Unlike existing frequencybased algorithms, ZERO++ does not involve subspace pattern searching. We show that ZERO++ is better than or comparable with the state-of-the-art anomaly detection methods over a wide range of real-world categorical and numeric …
Impact Of Isp, Bpr, And Customization On Erp Performance In Manufacturing Smes Of Korea, Soon-Goo Hong, Keng Siau, Jong-Weon Kim
Impact Of Isp, Bpr, And Customization On Erp Performance In Manufacturing Smes Of Korea, Soon-Goo Hong, Keng Siau, Jong-Weon Kim
Research Collection School Of Computing and Information Systems
Purpose: This paper aims to assess how enterprise resource planning (ERP) performance of Korean small and medium enterprises in manufacturing differs according to different levels of business process reengineering (BPR), information strategic planning (ISP) and ERP customization. Design/methodology/approach: A questionnaire survey was carried out in this research. Responses from 96 small and medium manufacturing companies that have adopted ERP systems were analyzed. Findings: The results of this study suggest that ISP and BPR implementation are positively correlated to ERP performance. Originality/value: While consulting and customization costs have positive impacts on ERP performance, the level of customization does not influence performance. …
Answering Why-Not And Why Questions On Reverse Top-K Queries, Qing Liu, Yunjun Gao, Gang Chen, Baihua Zheng, Linlin Zhou
Answering Why-Not And Why Questions On Reverse Top-K Queries, Qing Liu, Yunjun Gao, Gang Chen, Baihua Zheng, Linlin Zhou
Research Collection School Of Computing and Information Systems
Why-not and why questions can be posed by database users to seek clarifications on unexpected query results. Specifically, why-not questions aim to explain why certain expected tuples are absent from the query results, while why questions try to clarify why certain unexpected tuples are present in the query results. This paper systematically explores the why-not and why questions on reverse top-k queries, owing to its importance in multi-criteria decision making. We first formalize why-not questions on reverse top-k queries, which try to include the missing objects in the reverse top-k query results, and then, we propose a unified framework called …
Pairwise Relation Classification With Mirror Instances And A Combined Convolutional Neural Network, Jianfei Yu, Jing Jiang
Pairwise Relation Classification With Mirror Instances And A Combined Convolutional Neural Network, Jianfei Yu, Jing Jiang
Research Collection School Of Computing and Information Systems
Relation classification is the task of classifying the semantic relations between entity pairs in text. Observing that existing work has not fully explored using different representations for relation instances, especially in order to better handle the asymmetry of relation types, in this paper, we propose a neural network based method for relation classification that combines the raw sequence and the shortest dependency path representations of relation instances and uses mirror instances to perform pairwise relation classification. We evaluate our proposed models on two widely used datasets: SemEval-2010 Task 8 and ACE-2005. The empirical results show that our combined model together …
Efficient Online Summarization Of Large-Scale Dynamic Networks, Qiang Qu, Siyuan Liu, Feida Zhu, Christian S. Jensen
Efficient Online Summarization Of Large-Scale Dynamic Networks, Qiang Qu, Siyuan Liu, Feida Zhu, Christian S. Jensen
Research Collection School Of Computing and Information Systems
Information diffusion in social networks is often characterized by huge participating communities and viral cascades of high dynamicity. To observe, summarize, and understand the evolution of dynamic diffusion processes in an informative and insightful way is a challenge of high practical value. However, few existing studies aim to summarize networks for interesting dynamic patterns. Dynamic networks raise new challenges not found in static settings, including time sensitivity, online interestingness evaluation, and summary traceability, which render existing techniques inadequate. We propose dynamic network summarization to summarize dynamic networks with millions of nodes by only capturing the few most interesting nodes or …
From Footprint To Evidence: An Exploratory Study Of Mining Social Data For Credit Scoring, Guangming Guo, Feida Zhu, Enhong Chen, Qi Liu, Le Wu, Chu Guan
From Footprint To Evidence: An Exploratory Study Of Mining Social Data For Credit Scoring, Guangming Guo, Feida Zhu, Enhong Chen, Qi Liu, Le Wu, Chu Guan
Research Collection School Of Computing and Information Systems
With the booming popularity of online social networks like Twitter and Weibo, online user footprints are accumulating rapidly on the social web. Simultaneously, the question of how to leverage the large-scale user-generated social media data for personal credit scoring comes into the sight of both researchers and practitioners. It has also become a topic of great importance and growing interest in the P2P lending industry. However, compared with traditional financial data, heterogeneous social data presents both opportunities and challenges for personal credit scoring. In this article, we seek a deep understanding of how to learn users’ credit labels from social …
Cast2face: Assigning Character Names Onto Faces In Movie With Actor-Character Correspondence, Guangyu Gao, Mengdi Xu, Jialie Shen, Huangdong Ma, Shuicheng Yan
Cast2face: Assigning Character Names Onto Faces In Movie With Actor-Character Correspondence, Guangyu Gao, Mengdi Xu, Jialie Shen, Huangdong Ma, Shuicheng Yan
Research Collection School Of Computing and Information Systems
Automatically identifying characters in movies has attracted researchers' interest and led to several significant and interesting applications. However, due to the vast variation in character appearance as well as the weakness and ambiguity of available annotation, it is still a challenging problem. In this paper, we investigate this problem with the supervision of actor-character name correspondence provided by the movie cast. Our proposed framework, namely, Cast2Face, is featured by: 1) we restrict the assigned names within the set of character names in the cast; 2) for each character, by using the corresponding actor and movie name as keywords, we retrieve …
Careermapper: An Automated Resume Evaluation Tool, Vivian Lai, Kyong Jin Shim, Richard J. Oentaryo, Philips K. Prasetyo, Casey Vu, Ee-Peng Lim, David Lo
Careermapper: An Automated Resume Evaluation Tool, Vivian Lai, Kyong Jin Shim, Richard J. Oentaryo, Philips K. Prasetyo, Casey Vu, Ee-Peng Lim, David Lo
Research Collection School Of Computing and Information Systems
The advent of the Web brought about major changes in the way people search for jobs and companies look for suitable candidates. As more employers and recruitment firms turn to the Web for job candidate search, an increasing number of people turn to the Web for uploading and creating their online resumes. Resumes are often the first source of information about candidates and also the first item of evaluation in candidate selection. Thus, it is imperative that resumes are complete, free of errors and well-organized. We present an automated resume evaluation tool called 'CareerMapper'. Our tool is designed to conduct …
Unsupervised Feature Selection For Outlier Detection By Modelling Hierarchical Value-Feature Couplings, Guansong Pang, Longbing Cao, Ling Chen, Huan Liu
Unsupervised Feature Selection For Outlier Detection By Modelling Hierarchical Value-Feature Couplings, Guansong Pang, Longbing Cao, Ling Chen, Huan Liu
Research Collection School Of Computing and Information Systems
Proper feature selection for unsupervised outlier detection can improve detection performance but is very challenging due to complex feature interactions, the mixture of relevant features with noisy/redundant features in imbalanced data, and the unavailability of class labels. Little work has been done on this challenge. This paper proposes a novel Coupled Unsupervised Feature Selection framework (CUFS for short) to filter out noisy or redundant features for subsequent outlier detection in categorical data. CUFS quantifies the outlierness (or relevance) of features by learning and integrating both the feature value couplings and feature couplings. Such value-to-feature couplings capture intrinsic data characteristics and …
Iterated Random Oracle: A Universal Approach For Finding Loss In Security Reduction, Fuchun Guo, Willy Susilo, Yi Mu, Rongmao Chen, Jianchang Lai, Guomin Yang
Iterated Random Oracle: A Universal Approach For Finding Loss In Security Reduction, Fuchun Guo, Willy Susilo, Yi Mu, Rongmao Chen, Jianchang Lai, Guomin Yang
Research Collection School Of Computing and Information Systems
The indistinguishability security of a public-key cryptosystem can be reduced to a computational hard assumption in the random oracle model, where the solution to a computational hard problem is hidden in one of the adversary’s queries to the random oracle. Usually, there is a finding loss in finding the correct solution from the query set, especially when the decisional variant of the computational problem is also hard. The problem of finding loss must be addressed towards tight(er) reductions under this type. In EUROCRYPT 2008, Cash, Kiltz and Shoup proposed a novel approach using a trapdoor test that can solve the …
Coherence, Richness And Cognitive Absorption In Website Design, L. Visinescu, Fiona Fui-Hoon Nah
Coherence, Richness And Cognitive Absorption In Website Design, L. Visinescu, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
Kaplan’s theory on environmental preferences can offer a holistic perspective on cognitive absorption in ecommerce website design. Drawing on Kaplan’s theory, this paper proposes that coherence and richness of a website can enhance cognitive absorption of users. The findings from our study not only support the hypotheses, but also suggest that coherence and richness can reach an optimal proportion in website design, after which they are inversely correlated.
An Interview With The Scorpion: Walter O’Brien, Walter O'Brien
An Interview With The Scorpion: Walter O’Brien, Walter O'Brien
The Transdisciplinary STEAM+ Journal
An interview with Walter O'Brien (hacker handle: "Scorpion"), known as a businessman, information technologist, executive producer, and media personality who is the founder and CEO of Scorpion Computer Services, Inc. O'Brien is also the inspiration for and executive producer of the CBS television series, Scorpion.
Inferred Error Rates For Entity Resolution, Melody Lynn Penning
Inferred Error Rates For Entity Resolution, Melody Lynn Penning
Theses and Dissertations
This dissertation is focused on the methodology of determining the quality of the results of entity resolution. Entity resolution methodologies results in different success rates. Until now these success rates have been measured by counting all of the correctly and incorrectly matched results. This is quickly becoming an intractable task as datasets grow in size. In order to address this problem this research tests and describes the results of count based measures as compared with inferred measures borrowed from the information retrieval community. The key contribution of this research is a proof of concept in a controlled environment that demonstrates …