Skip to main content

ASU Electronic Theses and Dissertations


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.


Contributor
Date Range
2010 2019


Recent efforts in data cleaning have focused mostly on problems like data deduplication, record matching, and data standardization; few of these focus on fixing incorrect attribute values in tuples. Correcting values in tuples is typically performed by a minimum cost repair of tuples that violate static constraints like CFDs (which have to be provided by domain experts, or learned from a clean sample of the database). In this thesis, I provide a method for correcting individual attribute values in a structured database using a Bayesian generative model and a statistical error model learned from the noisy database directly. I thus …

Contributors
De, Sushovan, Kambhampati, Subbarao, Chen, Yi, et al.
Created Date
2014

Most data cleaning systems aim to go from a given deterministic dirty database to another deterministic but clean database. Such an enterprise pre–supposes that it is in fact possible for the cleaning process to uniquely recover the clean versions of each dirty data tuple. This is not possible in many cases, where the most a cleaning system can do is to generate a (hopefully small) set of clean candidates for each dirty tuple. When the cleaning system is required to output a deterministic database, it is forced to pick one clean candidate (say the "most likely" candidate) per tuple. Such …

Contributors
Rihan, Preet Inder Singh, Kambhampati, Subbarao, Liu, Huan, et al.
Created Date
2013

Traditionally, visualization is one of the most important and commonly used methods of generating insight into large scale data. Particularly for spatiotemporal data, the translation of such data into a visual form allows users to quickly see patterns, explore summaries and relate domain knowledge about underlying geographical phenomena that would not be apparent in tabular form. However, several critical challenges arise when visualizing and exploring these large spatiotemporal datasets. While, the underlying geographical component of the data lends itself well to univariate visualization in the form of traditional cartographic representations (e.g., choropleth, isopleth, dasymetric maps), as the data becomes multivariate, …

Contributors
Zhang, Yifan, Maciejewski, Ross, Mack, Elizabeth, et al.
Created Date
2016

Internet and social media devices created a new public space for debate on political and social topics (Papacharissi 2002; Himelboim 2010). Hotly debated issues span all spheres of human activity; from liberal vs. conservative politics, to radical vs. counter-radical religious debate, to climate change debate in scientific community, to globalization debate in economics, and to nuclear disarmament debate in security. Many prominent ’camps’ have emerged within Internet debate rhetoric and practice (Dahlberg, n.d.). In this research I utilized feature extraction and model fitting techniques to process the rhetoric found in the web sites of 23 Indonesian Islamic religious organizations, later …

Contributors
Tikves, Sukru, Davulcu, Hasan, Sen, Arunabha, et al.
Created Date
2016

Strong communities are important for society. One of the most important community builders, making friends, is poorly supported online. Dating sites support it but in romantic contexts. Other major social networks seem not to encourage it because either their purpose isn't compatible with introducing strangers or the prevalent methods of introduction aren't effective enough to merit use over real word alternatives. This paper presents a novel digital social network emphasizing creating friendships. Research has shown video chat communication can reach in-person levels of trust; coupled with a game environment to ease the discomfort people often have interacting with strangers and …

Contributors
Sorensen, Asael H., Vanlehn, Kurt, Liu, Huan, et al.
Created Date
2011