Databases and Information Systems Commons^™

Assessing Learning Outcomes And Social Capital Formation Resulting From The Use And Sharing Of Internet Knowledge Resources, Regina S. Collins

Dissertations

Today’s “digital natives” use the Internet to address most, if not all, their learning-related knowledge needs. This research evaluates the outcomes of formal learning activities requiring students to use, manage, share, and consolidate Internet knowledge resources (such as websites, videos, and blogs) to achieve both individual and group learning. This research takes an integrative approach to learning, capturing learner cognitive, interpersonal, and intrapersonal characteristics as well as the impact of the digital environment by evaluating the technological affordances of two different systems supporting such learning activities. This research also examines pedagogical modifications that would best integrate course assignments utilizing Internet …

Entity Recommendations Using Hierarchical Knowledge Bases, Siva Kumar Cheekula, Pavan Kapanipathi, Derek Doran, Prateek Jain, Amit P. Sheth

Kno.e.sis Publications

Recent developments in recommendation algorithms have focused on integrating Linked Open Data to augment traditional algorithms with background knowledge. These developments recognize that the integration of Linked Open Data may or better performance, particularly in cold start cases. In this paper, we explore if and how a specific type of Linked Open Data, namely hierarchical knowledge, may be utilized for recommendation systems. We propose a content-based recommendation approaches that adapts a spreading activation algorithm over the DBpedia category structure to identify entities of interest to the user. Evaluation of the algorithm over the Movielens dataset demonstrates that our method yields …

Mining Concept In Big Data, Jingjing Yang

Master's Projects

To fruitful using big data, data mining is necessary. There are two well-known methods, one is based on apriori principle, and the other one is based on FP-tree. In this project we explore a new approach that is based on simplicial complex, which is a combinatorial form of polyhedron used in algebraic topology. Our approach, similar to FP-tree, is top down, at the same time, it is based on apriori principle in geometric form, called closed condition in simplicial complex. Our method is almost 300 times faster than FP-growth on a real world database using a SJSU laptop. The database …

Index Strategies For Efficient And Effective Entity Search, Huy T. Vu

Master's Projects

The volume of structured data has rapidly grown in recent years, when data-entity emerged as an abstraction that captures almost every data pieces. As a result, searching for a desired piece of information on the web could be a challenge in term of time and relevancy because the number of matching entities could be very large for a given query. This project concerns with the efficiency and effectiveness of such entity queries. The work contains two major parts: implement inverted indexing strategies so that queries can be searched in minimal time, and rank results based on features that are independent …

An Open Source Advertisement Server, Pushkar Umaranikar

Master's Projects

This report describes a new online advertisement system and its implementation for the Yioop open source search engine. This system was implemented for my CS298 project. It supports both selling advertisements and displaying them within search results. The selling of advertisement is done using a novel auction system, which we describe in this paper. With this auction system, it is possible to create an advertisement, attach keywords to it, and add it to the advertisement inventory. An advertisement is displayed on a search results page if the search keyword matches the keywords attached to the advertisement. Display of advertisements is …

Context-Based Autosuggest On Graph Data, Hai Nguyen

Master's Projects

Autosuggest is an important feature in any search applications. Currently, most applications only suggest a single term based on how frequent that term appears in the indexed documents or how often it is searched upon. These approaches might not provide the most relevant suggestions because users often enter a series of related query terms to answer a question they have in mind. In this project, we implemented the Smart Solr Suggester plugin using a context-based approach that takes into account the relationships among search keywords. In particular, we used the keywords that the user has chosen so far in the …

A Scalable Search Engine Aggregator, Pooja Mishra

Master's Projects

The ability to display different media sources in an appropriate way is an integral part of search engines such as Google, Yahoo, and Bing, as well as social networking sites like Facebook, etc. This project explores and implements various media-updating features of the open source search engine Yioop [1]. These include news aggregation, video conversion and email distribution. An older, preexisting news update feature of Yioop was modified and scaled so that it can work on many machines. We redesigned and modified the user interface associated with a distributed news updater feature in Yioop. This project also introduced a video …

Keeping Pace With Criminals: Designing Patrol Allocation Against Adaptive Opportunistic Criminals, Chao Zhang, Arunesh Sinha, Milind Tambe

Research Collection School Of Computing and Information Systems

Police patrols are used ubiquitously to deter crimes in urban areas. A distinctive feature of urban crimes is that criminals react opportunistically to patrol officers' assignments. Compared to strategic attackers (such as terrorists) with a well-laid out plan, opportunistic criminals are less strategic in planning attacks and more flexible in executing them. In this paper, our goal is to recommend optimal police patrolling strategy against such opportunistic criminals. We first build a game-theoretic model that captures the interaction between officers and opportunistic criminals. However, while different models of adversary behavior have been proposed, their exact form remains uncertain. Rather than …

Domain Specific Document Retrieval Framework On Near Real-Time Social Health Data, Swapnil Soni

Kno.e.sis Publications

With the advent of web search and microblogging, the percentage of Online Health Information Seekers (OHIS) using these services to share and seek health information in real-time has increased exponentially. Recently, Twitter has emerged as one of the primary mediums for sharing and seeking of the latest information related to a variety of topics, including health information. Although Twitter is an excellent information source, the identification of useful information from the deluge of tweets is one of the major challenges. Twitter search is limited to keyword-based techniques to retrieve information for a given query and sometimes the results do not …

Analyzing The Social Media Footprint Of Street Gangs, Sanjaya Wijeratne, Derek Doran, Amit P. Sheth, Jack Dustin

Kno.e.sis Publications

Gangs utilize social media as a way to maintain threatening virtual presences, to communicate about their activities, and to intimidate others. Such usage has gained the attention of many justice service agencies that wish to create better crime prevention and judicial services. However, these agencies use analysis methods that are labor intensive and only lead to basic, qualitative data interpretations. This paper presents the architecture of a modern platform to discover the structure, function, and operation of gangs through the lens of social media. Preliminary analysis of social media posts shared in the greater Chicago, IL region demonstrate the platform’s …

Self-Organizing Neural Networks Integrating Domain Knowledge And Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Jacek M. Zurada

Research Collection School Of Computing and Information Systems

The use of domain knowledge in learning systems is expected to improve learning efficiency and reduce model complexity. However, due to the incompatibility with knowledge structure of the learning systems and real-time exploratory nature of reinforcement learning (RL), domain knowledge cannot be inserted directly. In this paper, we show how self-organizing neural networks designed for online and incremental adaptation can integrate domain knowledge and RL. Specifically, symbol-based domain knowledge is translated into numeric patterns before inserting into the self-organizing neural networks. To ensure effective use of domain knowledge, we present an analysis of how the inserted knowledge is used by …

Pediapp Finder: Creating A Pediatric Application Database, Sara Pro, Adrianne Leblanc, April Wasjutin, Robert Williams

Dissertations, Masters Theses, Capstones, and Culminating Projects

It is estimated that of the 85% of Americans that own cell phones, over half of these cell phone owners use apps on their phone (Fox & Duggan, 2012; Purcell, 2011). According to the U.S. Food and Drug Administration (2013), by 2015, 500 million mobile device users will be using mobile health, or “m-Health” apps. Healthcare professionals are increasingly adopting mobile technology as an innovative, cost-efficient, and timesaving tool that may promote patient wellness and disease prevention (Kumar, 2013; mHealth Bible, 2013). Although mobile technology is a natural fit to the field of occupational therapy, research demonstrates that few resources …

Compression Of Video Tracking And Bandwidth Balancing Routing In Wireless Multimedia Sensor Networks, Yin Wang, Jianjun Yang, Ju Shen, Bryson Payne, Juan Guo, Kun Hua

Computer Science Faculty Publications

There has been a tremendous growth in multimedia applications over wireless networks. Wireless Multimedia Sensor Networks(WMSNs) have become the premier choice in many research communities and industry. Many state-of-art applications, such as surveillance, traffic monitoring, and remote heath care are essentially video tracking and transmission in WMSNs. The transmission speed is constrained by the big file size of video data and fixed bandwidth allocation in constant routing paths. In this paper, we present a CamShift based algorithm to compress the tracking of videos. Then we propose a bandwidth balancing strategy in which each sensor node is able to dynamically select …

An Empirical Development Of Critical Value Factors For System Quality And Information Quality In Business Intelligence Systems Implementations, Paul Dooley

CCAC Theses and Dissertations

Business intelligence (BI) systems have been widely recognized as a leading technology for many years. However, despite the high priority and importance placed on BI, there has been a significant lack of BI system implementation (BISI) success. BI systems are not considered to be conventional information systems (IS) and often rely on the integration of a complex information infrastructure. Consequently, the degree of information quality (IQ) and system quality (SQ) have not met expectations for BISI success.

This study was designed to determine how an organization may gain benefits in the context of BISI by uncovering the antecedents and critical …

Design, Programming, And User-Experience, Kaila G. Manca

Honors Scholar Theses

This thesis is a culmination of my individualized major in Human-Computer Interaction. As such, it showcases my knowledge of design, computer engineering, user-experience research, and puts into practice my background in psychology, com- munications, and neuroscience.

I provided full-service design and development for a web application to be used by the Digital Media and Design Department and their students.This process involved several iterations of user-experience research, testing, concepting, branding and strategy, ideation, and design. It lead to two products.

The first product is full-scale development and optimization of the web appli- cation.The web application adheres to best practices. It was …

Assessing The Impacts Of Electronic Commerce Diffusion On Development, Gerard De Leoz, Sajda Qureshi, Lotfollah Najjar

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

While the concept of economic development has been widely used to understand the health and wealth of countries, it is accepted that the access to the internet for electronic commerce transactions enable generation in income and improvements in lives. However, with the rise of disparities in income within countries, electronic commerce opportunities can be limited to the few with internet access. In this paper, we investigate how e-commerce diffusion affects economic development and factors of electronic commerce diffusion that promote or impede economic development. Using data available through international data collection agencies, we analyze three ASEAN members with relatively close …

Secure And Reliable Routing Protocol For Transmission Data In Wireless Sensor Mesh Networks, Nooh Adel Bany Muhammad

Dissertations

Abstract

Sensor nodes collect data from the physical world then exchange it until it reaches the intended destination. This information can be sensitive, such as battlefield surveillance. Therefore, providing secure and continuous data transmissions among sensor nodes in wireless network environments is crucial. Wireless sensor networks (WSN) have limited resources, limited computation capabilities, and the exchange of data through the air and deployment in accessible areas makes the energy, security, and routing major concerns in WSN. In this research we are looking at security issues for the above reasons. WSN is susceptible to malicious activities such as hacking and physical …

Moving Average Reversion Strategy For On-Line Portfolio Selection, Bin Li, Steven C. H. Hoi, Doyen Sahoo, Zhi-Yong Liu

Research Collection School Of Computing and Information Systems

On-line portfolio selection, a fundamental problem in computational finance, has attracted increasing interest from artificial intelligence and machine learning communities in recent years. Empirical evidence shows that stock's high and low prices are temporary and stock prices are likely to follow the mean reversion phenomenon. While existing mean reversion strategies are shown to achieve good empirical performance on many real datasets, they often make the single-period mean reversion assumption, which is not always satisfied, leading to poor performance in certain real datasets. To overcome this limitation, this article proposes a multiple-period mean reversion, or so-called "Moving Average Reversion" (MAR), and …

Advances In Knowledge Discovery And Data Mining Part Ii, Tru Cao, Ee Peng Lim, Zhi-Hua Zhou, Tu-Bao Ho, David Wai-Lok Cheung, Hiroshi Motoda

Research Collection School Of Computing and Information Systems

No abstract provided.

Advances In Knowledge Discovery And Data Mining: 19th Pacific-Asia Conference, Pakdd 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part I, Tru Cao, Ee-Peng Lim, Zhi-Hua Zhou, Tu-Bao Ho, David Wai-Lok Cheung, Hiroshi Motoda

Research Collection School Of Computing and Information Systems

No abstract provided.