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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.


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

A volunteered geographic information system, e.g., OpenStreetMap (OSM), collects data from volunteers to generate geospatial maps. To keep the map consistent, volunteers are expected to perform the tedious task of updating the underlying geospatial data at regular intervals. Such a map curation step takes time and considerable human effort. In this thesis, we propose a framework that improves the process of updating geospatial maps by automatically identifying road changes from user-generated GPS traces. Since GPS traces can be sparse and noisy, the proposed framework validates the map changes with the users before propagating them to a publishable version of the …

Contributors
Vementala, Nikhil, Papotti, Paolo, Sarwat, Mohamed, et al.
Created Date
2017

The goal of fact checking is to determine if a given claim holds. A promising ap- proach for this task is to exploit reference information in the form of knowledge graphs (KGs), a structured and formal representation of knowledge with semantic descriptions of entities and relations. KGs are successfully used in multiple appli- cations, but the information stored in a KG is inevitably incomplete. In order to address the incompleteness problem, this thesis proposes a new method built on top of recent results in logical rule discovery in KGs called RuDik and a probabilistic extension of answer set programs called …

Contributors
Pradhan, Anish, Lee, Joohyung, Baral, Chitta, et al.
Created Date
2018

Social media has become popular in the past decade. Facebook for example has 1.59 billion active users monthly. With such massive social networks generating lot of data, everyone is constantly looking for ways of leveraging the knowledge from social networks to make their systems more personalized to their end users. And with rapid increase in the usage of mobile phones and wearables, social media data is being tied to spatial networks. This research document proposes an efficient technique that answers socially k-Nearest Neighbors with Spatial Range Filter. The proposed approach performs a joint search on both the social and spatial …

Contributors
Pasumarthy, Nitin, Sarwat, Mohamed, Papotti, Paolo, et al.
Created Date
2016

Reasoning with commonsense knowledge is an integral component of human behavior. It is due to this capability that people know that a weak person may not be able to lift someone. It has been a long standing goal of the Artificial Intelligence community to simulate such commonsense reasoning abilities in machines. Over the years, many advances have been made and various challenges have been proposed to test their abilities. The Winograd Schema Challenge (WSC) is one such Natural Language Understanding (NLU) task which was also proposed as an alternative to the Turing Test. It is made up of textual question …

Contributors
Sharma, Arpit, Baral, Chitta, Lee, Joohyung, et al.
Created Date
2019