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ASU Electronic Theses and Dissertations


Contributor
Date Range
2010 2018

Online social networks are the hubs of social activity in cyberspace, and using them to exchange knowledge, experiences, and opinions is common. In this work, an advanced topic modeling framework is designed to analyse complex longitudinal health information from social media with minimal human annotation, and Adverse Drug Events and Reaction (ADR) information is extracted and automatically processed by using a biased topic modeling method. This framework improves and extends existing topic modelling algorithms that incorporate background knowledge. Using this approach, background knowledge such as ADR terms and other biomedical knowledge can be incorporated during the text mining process, with ...

Contributors
Yang, Jian, Gonzalez, Graciela, Davulcu, Hasan, et al.
Created Date
2017

Continuous Delivery, as one of the youngest and most popular member of agile model family, has become a popular concept and method in software development industry recently. Instead of the traditional software development method, which requirements and solutions must be fixed before starting software developing, it promotes adaptive planning, evolutionary development and delivery, and encourages rapid and flexible response to change. However, several problems prevent Continuous Delivery to be introduced into education world. Taking into the consideration of the barriers, we propose a new Cloud based Continuous Delivery Software Developing System. This system is designed to fully utilize the whole ...

Contributors
Deng, Yuli, Huang, Dijiang, Davulcu, Hasan, et al.
Created Date
2013

Computational visual aesthetics has recently become an active research area. Existing state-of-art methods formulate this as a binary classification task where a given image is predicted to be beautiful or not. In many applications such as image retrieval and enhancement, it is more important to rank images based on their aesthetic quality instead of binary-categorizing them. Furthermore, in such applications, it may be possible that all images belong to the same category. Hence determining the aesthetic ranking of the images is more appropriate. To this end, a novel problem of ranking images with respect to their aesthetic quality is formulated ...

Contributors
Gattupalli, Jaya Vijetha R., Li, Baoxin, Davulcu, Hasan, et al.
Created Date
2016

Text classification, in the artificial intelligence domain, is an activity in which text documents are automatically classified into predefined categories using machine learning techniques. An example of this is classifying uncategorized news articles into different predefined categories such as "Business", "Politics", "Education", "Technology" , etc. In this thesis, supervised machine learning approach is followed, in which a module is first trained with pre-classified training data and then class of test data is predicted. Good feature extraction is an important step in the machine learning approach and hence the main component of this text classifier is semantic triplet based features in ...

Contributors
Karad, Ravi Chandravadan, Davulcu, Hasan, Corman, Steven, et al.
Created Date
2013

Proliferation of social media websites and discussion forums in the last decade has resulted in social media mining emerging as an effective mechanism to extract consumer patterns. Most research on social media and pharmacovigilance have concentrated on Adverse Drug Reaction (ADR) identification. Such methods employ a step of drug search followed by classification of the associated text as consisting an ADR or not. Although this method works efficiently for ADR classifications, if ADR evidence is present in users posts over time, drug mentions fail to capture such ADRs. It also fails to record additional user information which may provide an ...

Contributors
Chandrashekar, Pramod Bharadwaj Chandrashekar, Davulcu, Hasan, Gonzalez, Graciela, et al.
Created Date
2016

The overall contribution of the Minerva Initiative at ASU is to map social organizations in a multidimensional space that provides a measure of their radical or counter radical influence over the demographics of a nation. This tool serves as a simple content management system to store and track project resources like documents, images, videos and web links. It provides centralized and secure access to email conversations among project team members. Conversations are categorized into one of the seven pre-defined categories. Each category is associated with a certain set of keywords and we follow a frequency based approach for matching email ...

Contributors
Nair, Apurva, Davulcu, Hasan, Sen, Arunabha, et al.
Created Date
2012

Muslim radicalism is recognized as one of the greatest security threats for the United States and the rest of the world. Use of force to eliminate specific radical entities is ineffective in containing radicalism as a whole. There is a need to understand the origin, ideologies and behavior of Radical and Counter-Radical organizations and how they shape up over a period of time. Recognizing and supporting counter-radical organizations is one of the most important steps towards impeding radical organizations. A lot of research has already been done to categorize and recognize organizations, to understand their behavior, their interactions with other ...

Contributors
Nair, Shreejay, Davulcu, Hasan, Dasgpta, Partha, et al.
Created Date
2012

Cyber systems, including IoT (Internet of Things), are increasingly being used ubiquitously to vastly improve the efficiency and reduce the cost of critical application areas, such as finance, transportation, defense, and healthcare. Over the past two decades, computing efficiency and hardware cost have dramatically been improved. These improvements have made cyber systems omnipotent, and control many aspects of human lives. Emerging trends in successful cyber system breaches have shown increasing sophistication in attacks and that attackers are no longer limited by resources, including human and computing power. Most existing cyber defense systems for IoT systems have two major issues: (1) ...

Contributors
Buduru, Arun Balaji, Yau, Sik-Sang, Ahn, Gail-Joon, et al.
Created Date
2016

With the recent expansion in the use of wearable technology, a large number of users access personal data with these smart devices. The consumer market of wearables includes smartwatches, health and fitness bands, and gesture control armbands. These smart devices enable users to communicate with each other, control other devices, relax and work out more effectively. As part of their functionality, these devices store, transmit, and/or process sensitive user personal data, perhaps biological and location data, making them an abundant source of confidential user information. Thus, prevention of unauthorized access to wearables is necessary. In fact, it is important to ...

Contributors
Mukherjee, Tamalika, Yau, Sik-Sang, Ahn, Gail-Joon, et al.
Created Date
2017

Predicting when an individual will adopt a new behavior is an important problem in application domains such as marketing and public health. This thesis examines the performance of a wide variety of social network based measurements proposed in the literature - which have not been previously compared directly. This research studies the probability of an individual becoming influenced based on measurements derived from neighborhood (i.e. number of influencers, personal network exposure), structural diversity, locality, temporal measures, cascade measures, and metadata. It also examines the ability to predict influence based on choice of the classifier and how the ratio of positive ...

Contributors
Nanda Kumar, Nikhil, Shakarian, Paulo, Sen, Arunabha, et al.
Created Date
2016

There has been a lot of research in the field of artificial intelligence about thinking machines. Alan Turing proposed a test to observe a machine's intelligent behaviour with respect to natural language conversation. The Winograd schema challenge is suggested as an alternative, to the Turing test. It needs inferencing capabilities, reasoning abilities and background knowledge to get the answer right. It involves a coreference resolution task in which a machine is given a sentence containing a situation which involves two entities, one pronoun and some more information about the situation and the machine has to come up with the right ...

Contributors
Budukh, Tejas Ulhas, Baral, Chitta, Vanlehn, Kurt, et al.
Created Date
2013

With the advent of social media (like Twitter, Facebook etc.,) people are easily sharing their opinions, sentiments and enforcing their ideologies on others like never before. Even people who are otherwise socially inactive would like to share their thoughts on current affairs by tweeting and sharing news feeds with their friends and acquaintances. In this thesis study, we chose Twitter as our main data platform to analyze shifts and movements of 27 political organizations in Indonesia. So far, we have collected over 30 million tweets and 150,000 news articles from RSS feeds of the corresponding organizations for our analysis. For ...

Contributors
Poornachandran, Sathishkumar, Davulcu, Hasan, Sen, Arunabha, et al.
Created Date
2013

The purpose of this research is to efficiently analyze certain data provided and to see if a useful trend can be observed as a result. This trend can be used to analyze certain probabilities. There are three main pieces of data which are being analyzed in this research: The value for δ of the call and put option, the %B value of the stock, and the amount of time until expiration of the stock option. The %B value is the most important. The purpose of analyzing the data is to see the relationship between the variables and, given certain values, ...

Contributors
Reeves, Michael Thomas, Richa, Andrea, McCarville, Daniel, et al.
Created Date
2015

This dissertation presents the Temporal Event Query Language (TEQL), a new language for querying event streams. Event Stream Processing enables online querying of streams of events to extract relevant data in a timely manner. TEQL enables querying of interval-based event streams using temporal database operators. Temporal databases and temporal query languages have been a subject of research for more than 30 years and are a natural fit for expressing queries that involve a temporal dimension. However, operators developed in this context cannot be directly applied to event streams. The research extends a preexisting relational framework for event stream processing to ...

Contributors
Shiva, Foruhar Ali, Urban, Susan D, Chen, Yi, et al.
Created Date
2012

Genes have widely different pertinences to the etiology and pathology of diseases. Thus, they can be ranked according to their disease-significance on a genomic scale, which is the subject of gene prioritization. Given a set of genes known to be related to a disease, it is reasonable to use them as a basis to determine the significance of other candidate genes, which will then be ranked based on the association they exhibit with respect to the given set of known genes. Experimental and computational data of various kinds have different reliability and relevance to a disease under study. This work ...

Contributors
Lee, Jang, Gonzalez, Graciela, Ye, Jieping, et al.
Created Date
2011

With the advent of Internet, the data being added online is increasing at enormous rate. Though search engines are using IR techniques to facilitate the search requests from users, the results are not effective towards the search query of the user. The search engine user has to go through certain webpages before getting at the webpage he/she wanted. This problem of Information Overload can be solved using Automatic Text Summarization. Summarization is a process of obtaining at abridged version of documents so that user can have a quick view to understand what exactly the document is about. Email threads from ...

Contributors
Nadella, Sravan, Davulcu, Hasan, Li, Baoxin, et al.
Created Date
2015

Online learning platforms such as massive online open courses (MOOCs) and intelligent tutoring systems (ITSs) have made learning more accessible and personalized. These systems generate unprecedented amounts of behavioral data and open the way for predicting students’ future performance based on their behavior, and for assessing their strengths and weaknesses in learning. This thesis attempts to mine students’ working patterns using a programming problem solving system, and build predictive models to estimate students’ learning. QuizIT, a programming solving system, was used to collect students’ problem-solving activities from a lower-division computer science programming course in 2016 Fall semester. Differential mining techniques ...

Contributors
Mandal, Partho Pratim, Hsiao, I-Han, Davulcu, Hasan, et al.
Created Date
2017

Continuous advancements in biomedical research have resulted in the production of vast amounts of scientific data and literature discussing them. The ultimate goal of computational biology is to translate these large amounts of data into actual knowledge of the complex biological processes and accurate life science models. The ability to rapidly and effectively survey the literature is necessary for the creation of large scale models of the relationships among biomedical entities as well as hypothesis generation to guide biomedical research. To reduce the effort and time spent in performing these activities, an intelligent search system is required. Even though many ...

Contributors
Kanwar, Pradeep, Davulcu, Hasan, Dinu, Valentin, et al.
Created Date
2010

In trading, volume is a measure of how much stock has been exchanged in a given period of time. Since every stock is distinctive and has an alternate measure of shares, volume can be contrasted with historical volume inside a stock to spot changes. It is likewise used to affirm value patterns, breakouts, and spot potential reversals. In my thesis, I hypothesize that the concept of trading volume can be extrapolated to social media (Twitter). The ubiquity of social media, especially Twitter, in financial market has been overly resonant in the past couple of years. With the growth of its ...

Contributors
Awasthi, Piyush, Davulcu, Hasan, Tong, Hanghang, et al.
Created Date
2015

In visualizing information hierarchies, icicle plots are efficient diagrams in that they provide the user a straightforward layout for different levels of data in a hierarchy and enable the user to compare items based on the item width. However, as the size of the hierarchy grows large, the items in an icicle plot end up being small and indistinguishable. In this thesis, by maintaining the positive characteristics of traditional icicle plots and incorporating new features such as dynamic diagram and active layer, we developed an interactive visualization that allows the user to selectively drill down or roll up to review ...

Contributors
Wu, Bi, Maciejewski, Ross, Runger, George, et al.
Created Date
2014

This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries.

For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.