Databases and Information Systems Commons^™

Enterprise Search Technology Using Solr And Cloud, Padmavathy Ravikumar

All Capstone Projects

Solr is the popular, blazing fast open source enterprise search platform from the Apache Lucene project. Its major features include powerful full-text search, hit highlighting, faceted search, near real-time indexing, dynamic clustering, database integration, rich document (e.g., Word, PDF) handling, and geospatial search. Solr is highly reliable, scalable and fault tolerant, providing distributed indexing, replication and load-balanced querying, automated failover and recovery, centralized configuration and more. Solr powers the search and navigation features of many of the world's largest internet sites.

Databases and Solr have complementary strengths and weaknesses. SQL supports very simple wildcard-based text search with some simple normalization …

Fast Nearest Neighbor Search With Keywords, Ramu Anthati, Santosh Aditya Kokku, Tejaswini Vodapally

All Capstone Projects

Conventional spatial queries, such as range search and nearest neighbor retrieval, involve only conditions on objects’ geometric properties. Today, many modern applications call for novel forms of queries that aim to find objects satisfying both a spatial predicate, and a predicate on their associated texts. For example, instead of considering all the restaurants, a nearest neighbor query would instead ask for the restaurant that is the closest among those whose menus contain “steak, spaghetti, brandy” all at the same time. Currently the best solution to such queries is based on the IR2-tree, which, as shown in this paper, has a …

E-Exam Engine, Obaid Ahmed, Muthyalamma Gangula, Rakesh Margam

All Capstone Projects

E-Exam Engine is a web application by which is designed for Educational Institutes like Grad Schools, Colleges, and Private Institutes to conduct logic tests of their students on a regular basis. Design to facilitate administrator and user friendly interface complete and secure information is provided to user scope.

The E-Exam Engine is the process of conducting exam online. This project Provide accurate and flexible manner of conducting exam online. This Project provides more accurate and efficient way to take exam. It also provides flexibility to the user as one can give the exam at home. This is a one of …

Instamapp, Andrew Dicosmo, Preethi Reddy, Venkat Nischey

All Capstone Projects

InstaMapp is a web application we started building in fall 2014. This application is intended for anyone who wants to locate a product from a department store. Anyone who would like to print or view a shopping list with aisle or department locations. Currently there isn’t a reliable application out that that exist in the technology space. InstaMapp currently integrates with Walmart’s API and supports a responsive design for mobile devices.

During fall 2014, we built a proof of concept on Microsoft Windows Azure websites integrating with Intel Mashery Services for the API. We used the following Languages: PHP, JQuery, …

Understanding The Test Automation Culture Of App Developers, Pavneet Singh Kochhar, Ferdian. Thung, Nachiappan Nagappan, Thomas Zimmermann, David Lo

Research Collection School Of Computing and Information Systems

Smartphone applications (apps) have gained popularity recently. Millions of smartphone applications (apps) are available on different app stores which gives users plethora of options to choose from, however, it also raises concern if these apps are adequately tested before they are released for public use. In this study, we want to understand the test automation culture prevalent among app developers. Specifically, we want to examine the current state of testing of apps, the tools that are commonly used by app developers, and the problems faced by them. To get an insight on the test automation culture, we conduct two different …

Intensity And Resolution Enhancement Of Local Regions For Object Detection And Tracking In Wide Area Surveillance, Evan Krieger, Vijayan K. Asari, Saibabu Arigela, Theus H. Aspiras

Electrical and Computer Engineering Faculty Publications

Object tracking in wide area motion imagery is a complex problem that consists of object detection and target tracking over time. This challenge can be solved by human analysts who naturally have the ability to keep track of an object in a scene. A computer vision solution for object tracking has the potential to be a much faster and efficient solution. However, a computer vision solution faces certain challenges that do not affect a human analyst. To overcome these challenges, a tracking process is proposed that is inspired by the known advantages of a human analyst.

First, the focus of …

Affect And Online Privacy Concerns, David Charles Castano

CCAC Theses and Dissertations

The purpose of this study was to investigate the influence of affect on privacy concerns and privacy behaviors. A considerable amount of research in the information systems field argues that privacy concerns, usually conceptualized as an evaluation of privacy risks, influence privacy behaviors. However, recent theoretical work shows that affect, a pre-cognitive evaluation, has a significant effect on preferences and choices in risky situations. Affect is contrasted with cognitive issues in privacy decision making and the role of affective versus cognitive-consequentialist factors is reviewed in privacy context.

A causal model was developed to address how affect influences privacy concerns and …

Social Services Management Solution, Kurt A. Karner, James L. Potulny

All Capstone Projects

The modern privately run social services agency exists within a complex regulatory framework that requires detailed recordkeeping. In such an environment, paperwork tracking is best managed by a centralized enterprise data management system. While commercial applications that perform this function exist, they are frequently bundled with software for other business functions. Such additional software can be helpful, but it frequently duplicates the functionality of other enterprise software for these businesses, which is financially inefficient. This project developed a similar system using the ASP.NET 4.5 framework that is designed to provide a standalone solution to recordkeeping requirements. It followed a typical …

Hadoop "The Emerging Tool In The Present Scenario For Accessing The Large Sets Of Data", Chandra Kiran Movva, Tejaswi Sura, Ranjith Reddy Thipparthi

All Capstone Projects

Hadoop is one of the tools designed to handle big data. Hadoop and other software products work to interpret or parse the results of big data searches through specific proprietary algorithms and methods. Hadoop is an open-source program under the Apache license that is maintained by a global community of users. It includes various main components, including a MapReduce set of functions and a Hadoop distributed file system (HDFS). The idea behind MapReduce is that Hadoop can first map a large data set, and then perform a reduction on that content for specific results. A reduce function can be thought …

Context-Driven Automatic Subgraph Creation For Literature-Based Discovery, Delroy H. Cameron, Ramakanth Kavuluru, Thomas Rindflesch, Amit P. Sheth, Krishnaprasad Thirunarayan, Olivier Bodenreider

Kno.e.sis Publications

Background: Literature-based discovery (LBD) is characterized by uncovering hidden associations in non-interacting scientific literature. Prior approaches to LBD include use of: 1) domain expertise and structured background knowledge to manually filter and explore the literature, 2) distributional statistics and graph-theoretic measures to rank interesting connections and 3) heuristics to help eliminate spurious connections. However, manual approaches to LBD are not scalable and purely distributional approaches may not be sufficient to obtain insights into the meaning of poorly understood associations. While several graph-based approaches have the potential to elucidate associations, their effectiveness has not been fully demonstrated. A considerable degree of …

Big Data Analytics By Using Hadoop, Chaitanya Arava, Sudharshan Bandaru, Saradhi Bhargava Reddy Tiyyagura

All Capstone Projects

Data is large and vast, with more data coming into the system every day. Summarization analytics are all about grouping similar data together and then performing an operation such as calculating a statistic, building an index, or just simply counting.

Filtering is more about understanding a smaller piece of your data, such as all records generated from a particular user, or the top ten most used verbs in a corpus of text. In short, filtering allows you to apply a microscope to your data. It can also be considered a form of search.

Hadoop allows us to modify the way …

Sensorem – An Efficient Mobile Platform For Wireless Sensor Network Visualization, Jin Ming Koh, Marcus Sak, Hwee Xian Tan, Huiguang Liang, Fachmin Folianto, Tony Quek

Research Collection School Of Computing and Information Systems

No abstract provided.

Best Upgrade Plans For Single And Multiple Source-Destination Pairs, Yimin Lin, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

In this paper, we study Resource Constrained Best Upgrade Plan (BUP) computation in road network databases. Consider a transportation network (weighted graph) G where a subset of the edges are upgradable, i.e., for each such edge there is a cost, which if spent, the weight of the edge can be reduced to a specific new value. In the single-pair version of BUP, the input includes a source and a destination in G, and a budget B (resource constraint). The goal is to identify which upgradable edges should be upgraded so that the shortest path distance between source and …

Mining Business Competitiveness From User Visitation Data, Doan Thanh Nam, Freddy Chong Tat Chua, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Ranking businesses by competitiveness is useful in many applications including business (e.g., restaurant) recommendation, and estimation of intrinsic value of businesses for mergers and acquisitions. Our literature reveals that previous methods of business ranking have ignored the competing relationship among businesses within their geographical areas. To account for competition, we propose the use of PageRank model and its variant to derive the Competitive Rankof businesses. We use the check-ins of users from Foursquare, a location-based social network, to model the winners of competitions among stores. The results of our experiments show that Competitive Rank works well when evaluated against ground …

Measuring User Influence, Susceptibility And Cynicalness In Sentiment Diffusion, Roy Ka-Wei Lee, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Diffusion in social networks is an important research topic lately due to massive amount of information shared on social media and Web. As information diffuses, users express sentiments which can affect the sentiments of others. In this paper, we analyze how users reinforce or modify sentiment of one another based on a set of inter-dependent latent user factors as they are engaged in diffusion of event information. We introduce these sentiment-based latent user factors, namely influence, susceptibility and cynicalness. We also propose the ISC model to relate the three factors together and develop an iterative computation approach to …

A Study Of Access Control For Electronic Health Records, Sergio Vincent Senese

All Student Theses and Dissertations

The expansion between Information Technology and Healthcare has created many new options for both disciplines, as well as challenges. One of these topics is the Electronic Health Record (EHR) and the push for a universal record. A challenge for this topic is access control: how to keep patient’s personal health information secure, but at the same time accessible to all fields of healthcare and accomplish this within the federal privacy laws made by our government. This study focuses on the idea of a single EHR containing all the different medical information for all the areas of healthcare for a patient. …

Review Selection Using Micro-Reviews, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas

Research Collection School Of Computing and Information Systems

Given the proliferation of review content, and the fact that reviews are highly diverse and often unnecessarily verbose, users frequently face the problem of selecting the appropriate reviews to consume. Micro-reviews are emerging as a new type of online review content in the social media. Micro-reviews are posted by users of check-in services such as Foursquare. They are concise (up to 200 characters long) and highly focused, in contrast to the comprehensive and verbose reviews. In this paper, we propose a novel mining problem, which brings together these two disparate sources of review content. Specifically, we use coverage of micro-reviews …

Multi-Roles Affiliation Model For General User Profiling, Lizi Liao, Heyan Huang, Yashen Wang

Research Collection School Of Computing and Information Systems

Online social networks release user attributes, which is important for many applications. Due to the sparsity of such user attributes online, many works focus on profiling user attributes automatically. However, in order to profile a specific user attribute, an unique model is built and such model usually does not fit other profiling tasks. In our work, we design a novel, flexible general user profiling model which naturally models users’ friendships with user attributes. Experiments show that our method simultaneously profile multiple attributes with better performance.

Exploring Discriminative Features For Anomaly Detection In Public Spaces, Shriguru Nayak, Archan Misra, Kasthuri Jeyarajah, Philips Kokoh Prasetyo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Context data, collected either from mobile devices or from user-generated social media content, can help identify abnormal behavioural patterns in public spaces (e.g., shopping malls, college campuses or downtown city areas). Spatiotemporal analysis of such data streams provides a compelling new approach towards automatically creating real-time urban situational awareness, especially about events that are unanticipated or that evolve very rapidly. In this work, we use real-life datasets collected via SMU's LiveLabs testbed or via SMU's Palanteer software, to explore various discriminative features (both spatial and temporal - e.g., occupancy volumes, rate of change in topic{specific tweets or probabilistic distribution of …

Memory Dynamics In Attractor Networks, Guoqi Li, Kiruthika Ramanathan, Ning Ning, Luping Shi, Changyun Wen

Research Collection School Of Computing and Information Systems

As can be represented by neurons and their synaptic connections, attractor networks are widely believed to underlie biological memory systems and have been used extensively in recent years to model the storage and retrieval process of memory. In this paper, we propose a new energy function, which is nonnegative and attains zero values only at the desired memory patterns. An attractor network is designed based on the proposed energy function. It is shown that the desired memory patterns are stored as the stable equilibrium points of the attractor network. To retrieve a memory pattern, an initial stimulus input is presented …