ASU Electronic Theses and Dissertations

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The amount of time series data generated is increasing due to the integration of sensor technologies with everyday applications, such as gesture recognition, energy optimization, health care, video surveillance. The use of multiple sensors simultaneously for capturing different aspects of the real world attributes has also led to an increase in dimensionality from uni-variate to multi-variate time series. This has facilitated richer data representation but also has necessitated algorithms determining similarity between two multi-variate time series for search and analysis. Various algorithms have been extended from uni-variate to multi-variate case, such as multi-variate versions of Euclidean distance, edit distance, dynamic ...

Contributors
Garg, Yash, Candan, Kasim Selcuk, Chowell-Punete, Gerardo, et al.
Created Date
2015

Measuring node centrality is a critical common denominator behind many important graph mining tasks. While the existing literature offers a wealth of different node centrality measures, it remains a daunting task on how to intervene the node centrality in a desired way. In this thesis, we study the problem of minimizing the centrality of one or more target nodes by edge operation. The heart of the proposed method is an accurate and efficient algorithm to estimate the impact of edge deletion on the spectrum of the underlying network, based on the observation that the edge deletion is essentially a local, ...

Contributors
Peng, Ruiyue, Tong, Hanghang, He, Jingrui, et al.
Created Date
2016

Micro-blogging platforms like Twitter have become some of the most popular sites for people to share and express their views and opinions about public events like debates, sports events or other news articles. These social updates by people complement the written news articles or transcripts of events in giving the popular public opinion about these events. So it would be useful to annotate the transcript with tweets. The technical challenge is to align the tweets with the correct segment of the transcript. ET-LDA by Hu et al [9] addresses this issue by modeling the whole process with an LDA-based graphical ...

Contributors
Acharya, Anirudh, Kambhampati, Subbarao, Davulcu, Hasan, et al.
Created Date
2015

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

Stock market news and investing tips are popular topics in Twitter. In this dissertation, first I utilize a 5-year financial news corpus comprising over 50,000 articles collected from the NASDAQ website matching the 30 stock symbols in Dow Jones Index (DJI) to train a directional stock price prediction system based on news content. Next, I proceed to show that information in articles indicated by breaking Tweet volumes leads to a statistically significant boost in the hourly directional prediction accuracies for the DJI stock prices mentioned in these articles. Secondly, I show that using document-level sentiment extraction does not yield a ...

Contributors
Alostad, Hana, Davulcu, Hasan, Corman, Steven, et al.
Created Date
2016

The increasing usage of smart-phones and mobile devices in work environment and IT industry has brought about unique set of challenges and opportunities. ARM architecture in particular has evolved to a point where it supports implementations across wide spectrum of performance points and ARM based tablets and smart-phones are in demand. The enhancements to basic ARM RISC architecture allow ARM to have high performance, small code size, low power consumption and small silicon area. Users want their devices to perform many tasks such as read email, play games, and run other online applications and organizations no longer desire to provision ...

Contributors
Chowdhary, Ankur, Huang, Dijiang, Tong, Hanghang, et al.
Created Date
2015

Node proximity measures are commonly used for quantifying how nearby or otherwise related to two or more nodes in a graph are. Node significance measures are mainly used to find how much nodes are important in a graph. The measures of node proximity/significance have been highly effective in many predictions and applications. Despite their effectiveness, however, there are various shortcomings. One such shortcoming is a scalability problem due to their high computation costs on large size graphs and another problem on the measures is low accuracy when the significance of node and its degree in the graph are not related. ...

Contributors
Kim, Jung Hyun, Candan, K. Selcuk, Davulcu, Hasan, et al.
Created Date
2017

The game held by National Basketball Association (NBA) is the most popular basketball event on earth. Each year, tons of statistical data are generated from this industry. Meanwhile, managing teams, sports media, and scientists are digging deep into the data ocean. Recent research literature is reviewed with respect to whether NBA teams could be analyzed as connected networks. However, it becomes very time-consuming, if not impossible, for human labor to capture every detail of game events on court of large amount. In this study, an alternative method is proposed to parse public resources from NBA related websites to build degenerated ...

Contributors
Zhang, Xiaoyu, Tong, Hanghang, He, Jingrui, et al.
Created Date
2017

Visual Question Answering (VQA) is a new research area involving technologies ranging from computer vision, natural language processing, to other sub-fields of artificial intelligence such as knowledge representation. The fundamental task is to take as input one image and one question (in text) related to the given image, and to generate a textual answer to the input question. There are two key research problems in VQA: image understanding and the question answering. My research mainly focuses on developing solutions to support solving these two problems. In image understanding, one important research area is semantic segmentation, which takes images as input ...

Contributors
Tian, Qiongjie, Li, Baoxin, Tong, Hanghang, et al.
Created Date
2017

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.