Databases and Information Systems Commons^™

Maximum A Posteriori Estimation For Information Source Detection, Biao Chang, Enhong Chen, Feida Zhu, Qi Liu, Tong Xu

Research Collection School Of Computing and Information Systems

Information source detection is to identify nodes initiating the diffusion process in a network, which has a wide range of applications including epidemic outbreak prevention, Internet virus source identification, and rumor source tracing in social networks. Although it has attracted ever-increasing attention from research community in recent years, existing solutions still suffer from high time complexity and inadequate effectiveness, due to high dynamics of information diffusion and observing just a snapshot of the whole process. To this end, we present a comprehensive study for single information source detection in weighted graphs. Specifically, we first propose a maximum a posteriori (MAP) …

An Investigation Into The Optimal Use Of Frequency-Based Weights To Improve The Performance Of Entity Resolution, Bingyi Zhong

Theses and Dissertations

Using a weight-based match score has been studied as a way to improve the accuracy of record linking (entity resolution) since Fellegi and Sunter first described the idea of probabilistic agreement and disagreement weights in their seminal work “A Theory of Record Linking.” However, the original work only described weight associated with an entity attribute. Later researchers such as Herzog et al suggested the weighting scheme could be extended to apply to frequently-occurring attribute values (frequency-based weights) instead of just the attribute as in the Fellegi-Sunter scheme. However, there has been little definitive research as to how frequency-based weights should …

Improved Chinese Language Processing For An Open Source Search Engine, Xianghong Sun

Master's Projects

Natural Language Processing (NLP) is the process of computers analyzing on human languages. There are also many areas in NLP. Some of the areas include speech recognition, natural language understanding, and natural language generation.

Information retrieval and natural language processing for Asians languages has its own unique set of challenges not present for Indo-European languages. Some of these are text segmentation, named entity recognition in unsegmented text, and part of speech tagging. In this report, we describe our implementation of and experiments with improving the Chinese language processing sub-component of an open source search engine, Yioop. In particular, we rewrote …

An Inventory Of Existing Neuroprivacy Controls, Dustin Steinhagen, Houssain Kettani

Research & Publications

Brain-Computer Interfaces (BCIs) facilitate communication between brains and computers. As these devices become increasingly popular outside of the medical context, research interest in brain privacy risks and countermeasures has bloomed. Several neuroprivacy threats have been identified in the literature, including brain malware, personal data being contained in collected brainwaves and the inadequacy of legal regimes with regards to neural data protection. Dozens of controls have been proposed or implemented for protecting neuroprivacy, although it has not been immediately apparent what the landscape of neuroprivacy controls consists of. This paper inventories the implemented and proposed neuroprivacy risk mitigation techniques from open …

Benchmarking Mongodb Multi-Document Transactions In A Sharded Cluster, Tushar Panpaliya

Master's Projects

Relational databases like Oracle, MySQL, and Microsoft SQL Server offer trans- action processing as an integral part of their design. These databases have been a primary choice among developers for business-critical workloads that need the highest form of consistency. On the other hand, the distributed nature of NoSQL databases makes them suitable for scenarios needing scalability, faster data access, and flexible schema design. Recent developments in the NoSQL database community show that NoSQL databases have started to incorporate transactions in their drivers to let users work on business-critical scenarios without compromising the power of distributed NoSQL features [1].

MongoDB is …

Server Score, Zachary Buresh

Student Academic Conference

This presentation is in regards to the Android mobile application that I developed in the Kotlin programming language named "Server Score". The app helps waiters/waitresses calculate, track, and predict performance related statistics on the job.

Predictive Modeling Of Asynchronous Event Sequence Data, Jin Shang

LSU Doctoral Dissertations

Large volumes of temporal event data, such as online check-ins and electronic records of hospital admissions, are becoming increasingly available in a wide variety of applications including healthcare analytics, smart cities, and social network analysis. Those temporal events are often asynchronous, interdependent, and exhibiting self-exciting properties. For example, in the patient's diagnosis events, the elevated risk exists for a patient that has been recently at risk. Machine learning that leverages event sequence data can improve the prediction accuracy of future events and provide valuable services. For example, in e-commerce and network traffic diagnosis, the analysis of user activities can be …

Building A Library Search Infrastructure With Elasticsearch, Kim Pham, Fernando Reyes, Jeff Rynhart

University Libraries: Faculty Scholarship

This article discusses our implementation of an Elastic cluster to address our search, search administration and indexing needs, how it integrates in our technology infrastructure, and finally takes a close look at the way that we built a reusable, dynamic search engine that powers our digital repository search. We cover the lessons learned with our early implementations and how to address them to lay the groundwork for a scalable, networked search environment that can also be applied to alternative search engines such as Solr.

Improved User News Feed Customization For An Open Source Search Engine, Timothy Chow

Master's Projects

Yioop is an open source search engine project hosted on the site of the same name.It offers several features outside of searching, with one such feature being a news feed. The current news feed system aggregates articles from a curated list of news sites determined by the owner. However in its current state, the feed list is limited in size, constrained by the hardware that the aggregator is run on. The goal of my project was to overcome this limit by improving the current storage method used. The solution was derived by making use of IndexArchiveBundles and IndexShards, both of …

Developing A Mongodb Monitoring System Using Nosql Databases For Monitored Data Management, Anjitha Karattu Thodi

Master's Projects

MongoDB is a NoSQL database, specifically used to efficiently store and access a large quantity of unstructured data over a distributed cluster of nodes. As the number of nodes in the cluster increases, it becomes difficult to manually monitor different components of the database. This poses an interesting problem of monitoring the MongoDB database to view the state of the system at any point. Although a few proprietary monitoring tools exist to monitor MongoDB clusters, they are not freely available for use in academia. Therefore, the focus of this project is to create a monitoring system that is completely built …

The Use Of Digital Millenium Copyright Act To Stifle Speech Through Non-Copyright Related Takedowns, Miller Freeman

Seattle Journal of Technology, Environmental, & Innovation Law

In 1998, Congress passed the Digital Millennium Copyright Act. This law provided new methods of protecting copyright in online media. These protections shift the normal judicial process that would stop the publication of infringing materials to private actors: the online platforms. As a result, online platforms receive notices of infringement and issue takedowns of allegedly copyrighted works without the judicial process which normally considers the purpose of the original notice of infringement. In at least one case, discussed in detail below, this has resulted in a notice and takedown against an individual for reasons not related to the purpose of …

Secure And Efficient Models For Retrieving Data From Encrypted Databases In Cloud, Sultan Ahmed A Almakdi

Graduate Theses and Dissertations

Recently, database users have begun to use cloud database services to outsource their databases. The reason for this is the high computation speed and the huge storage capacity that cloud owners provide at low prices. However, despite the attractiveness of the cloud computing environment to database users, privacy issues remain a cause for concern for database owners since data access is out of their control. Encryption is the only way of assuaging users’ fears surrounding data privacy, but executing Structured Query Language (SQL) queries over encrypted data is a challenging task, especially if the data are encrypted by a randomized …

A Data-Analytics Approach For Risk Evaluation In Peer-To-Peer Lending Platforms, Feng He, Yuelei Li, Tiecheng Xu, Libo Yin, Wei Zhang, Xiaotao Zhang

Research Collection School Of Accountancy

The goal of this article is to investigate the roles of individual behavior characteristics and Internet finance industry risk in the light of bank run theory for P2P. We know that risk evaluation is clearly important for peer-to-peer (P2P) lending platforms in China, as during the last two years, the industry has experienced thousands of platform crashes. Traditional approaches to evaluate enterprise risk are increasingly ineffective in this industry, due to the difficulty of assessing the real information. In addition, the Internet business model makes it possible to record new kinds of information. By applying a data-driven analytics method, we …

Improving Energy-Efficiency Through Smart Data Placement In Hadoop Clusters, Ahmed Mostafa

Theses and Dissertations

Hadoop, a pioneering open source framework, has revolutionized the big data world because of its ability to process vast amounts of unstructured and semi-structured data. This ability makes Hadoop the ‘go-to’ technology for many industries that generate big data, thus it also aids in being cost effective, unlike other legacy systems. Hadoop MapReduce is used in large scale data parallel applications to process massive amounts of data across a cluster and is used for scheduling, processing, and executing jobs. Basically, MapReduce is the right hand of Hadoop, as its library is needed to process these large data sets. In this …

Privacy-Preserving Protocol For Atomic Swap Between Blockchains, Kiran Gurung

Boise State University Theses and Dissertations

Atomic swap facilitates fair exchange of cryptocurrencies without the need for a trusted authority. It is regarded as one of the prominent technologies for the cryptocurrency ecosystem, helping to realize the idea of a decentralized blockchain introduced by Bitcoin. However, due to the heterogeneity of the cryptocurrency systems, developing efficient and privacy-preserving atomic swap protocols has proven challenging. In this thesis, we propose a generic framework for atomic swap, called PolySwap, that enables fair ex-change of assets between two heterogeneous sets of blockchains. Our construction 1) does not require a trusted third party, 2) preserves the anonymity of the swap …

Applications Of Digital Remote Sensing To Quantify Glacier Change In Glacier And Mount Rainier National Parks, Brianna Clark

Electronic Theses and Dissertations

Digital remote sensing and geographic information systems were employed in performing area and volume calculations on glacial landscapes. Characteristics of glaciers from two geographic regions, the Intermountain Region (between the Rocky Mountain and Cascade Ranges) and the Pacific Northwest, were estimated for the years 1985, 2000, and 2015. Glacier National Park was studied for the Intermountain Region whereas Mount Rainier National Park was representative of the glaciers in the Pacific Northwest. Within the thirty year period of the study, the glaciers in Glacier National Park decreased in area by 27.5 percent while those on Mount Rainier only decreased by 5.7 …

Predicting Disease Progression Using Deep Recurrent Neural Networks And Longitudinal Electronic Health Record Data, Seunghwan Kim

McKelvey School of Engineering Graduate Student Theses & Dissertations

Electronic Health Records (EHR) are widely adopted and used throughout healthcare systems and are able to collect and store longitudinal information data that can be used to describe patient phenotypes. From the underlying data structures used in the EHR, discrete data can be extracted and analyzed to improve patient care and outcomes via tasks such as risk stratification and prospective disease management. Temporality in EHR is innately present given the nature of these data, however, and traditional classification models are limited in this context by the cross-sectional nature of training and prediction processes. Finding temporal patterns in EHR is especially …

Platform Pricing With Strategic Buyers: The Impact Of Future Production Cost, Mei Lin, Xiajun Amy Pan, Quan Zheng

Research Collection School Of Computing and Information Systems

Two-sided platforms are often coupled with exclusive hardware products that connect two sides of users, the consumers of the hardware product (i.e., buyers) and the application developers (i.e., sellers). The hardware product in the platform business model introduces three important issues that are not yet well understood in the literature of platform pricing: potentially downward-trending production cost, product quality improvements, and consumers' strategic behaviors. Using analytical modeling, our study explicitly factors in these issues in analyzing a monopoly platform owner's two-sided pricing problem. The platform sequentially introduces and prices quality-improving hardware products, for which the costliness of quality may decrease. …

Robust Graph Learning From Noisy Data, Zhao Kang, Haiqi Pan, Steven C. H. Hoi, Zenglin Xu

Research Collection School Of Computing and Information Systems

Learning graphs from data automatically have shown encouraging performance on clustering and semisupervised learning tasks. However, real data are often corrupted, which may cause the learned graph to be inexact or unreliable. In this paper, we propose a novel robust graph learning scheme to learn reliable graphs from the real-world noisy data by adaptively removing noise and errors in the raw data. We show that our proposed model can also be viewed as a robust version of manifold regularized robust principle component analysis (RPCA), where the quality of the graph plays a critical role. The proposed model is able to …

The Future Of Work Now: Cyber Threat Attribution At Fireeye, Thomas H. Davenport, Steven M. Miller

Research Collection School Of Computing and Information Systems

One of the most frequently-used phrases at business events these days is “the future of work.” It’s increasingly clear that artificial intelligence and other new technologies will bring substantial changes in work tasks and business processes. But while these changes are predicted for the future, they’re already present in many organizations for many different jobs. The job and incumbent described below is an example of this phenomenon. It’s a clear example of an existing job that’s been transformed by AI and related tools.