Digital Commons Network^™

Human-Like Summaries From Heterogeneous And Time-Windowed Software Development Artefacts, Mahfouth Alghamdi, Christoph Treude, Markus Wagner

Research Collection School Of Computing and Information Systems

Automatic text summarisation has drawn considerable interest in the area of software engineering. It is challenging to summarise the activities related to a software project, (1) because of the volume and heterogeneity of involved software artefacts, and (2) because it is unclear what information a developer seeks in such a multi-document summary. We present the first framework for summarising multi-document software artefacts containing heterogeneous data within a given time frame. To produce human-like summaries, we employ a range of iterative heuristics to minimise the cosine-similarity between texts and high-dimensional feature vectors. A first study shows that users find the automatically …

Enrichment Of Ontologies Using Machine Learning And Summarization, Hao Liu

Dissertations

Biomedical ontologies are structured knowledge systems in biomedicine. They play a major role in enabling precise communications in support of healthcare applications, e.g., Electronic Healthcare Records (EHR) systems. Biomedical ontologies are used in many different contexts to facilitate information and knowledge management. The most widely used clinical ontology is the SNOMED CT. Placing a new concept into its proper position in an ontology is a fundamental task in its lifecycle of curation and enrichment.

A large biomedical ontology, which typically consists of many tens of thousands of concepts and relationships, can be viewed as a complex network with concepts as …

An Automated Feedback System To Support Student Learning Of Conceptual Knowledge In Writing-To-Learn Activities, Ye Xiong

Dissertations

As a pedagogical strategy, Writing-to-Learn (WTL) intends to use writing to improve students’ understanding of course content. However, most of the existing feedback systems for writing are mainly focused on improving students’ writing skills rather than their conceptual development. In this dissertation, an automatic approach is proposed to generate timely, actionable, and individualized feedback based on comparing knowledge representations extracted from lecture slides and individual students’ writing assignments. The novelty of the proposed approach lies in the feedback generation: to help students assimilate new knowledge into their existing knowledge better, their current knowledge is modeled as a set of matching …

Analyzing And Assisting Patient Decision-Making In Online Health Communities, Mingda Li

Dissertations

In recent years, many users have joined online health communities (OHC) to seek information, suggestions and social support. However, little has been studied about the roles of OHCs in patients' decision-making processes. The aim of this research is to analyze OHC data to better understand patient decision-making processes, and to provide assistance to OHC users in their decision-making.

In order to analyze or assist patients in their decision-making, a novel classification model is designed to identify discussion threads in OHC that are related to decision making. This is achieved by building a two-step combined deep learning model. Empirical evaluation shows …

Accurate Patient Health Condition Identification And Risk Prediction From Health Data, Jinhe Shi

Dissertations

Online Health communities (OHCs), Electronic Health Records (EHRs) and Claims data contain rich patient information. Accurate identification of patient's health conditions is critical for providing effective and safe health care service and for trustable knowledge discovery. This dissertation proposes several deep-learning based techniques on identifying patient health conditions and predicting adverse drug event (ADE) risks using various health data.

First, this dissertation presents a novel patient experience mining model to differentiate the data expressing user experiences from the one describing hearsays. Indeed, OHCs contain information with varying degrees of quality. Identifying information that describes patient health experience from OHCs is …

Cryptography, Passwords, Privacy, And The Fifth Amendment, Gary C. Kessler, Ann M. Phillips

Journal of Digital Forensics, Security and Law

Military-grade cryptography has been widely available at no cost for personal and commercial use since the early 1990s. Since the introduction of Pretty Good Privacy (PGP), more and more people encrypt files and devices, and we are now at the point where our smartphones are encrypted by default. While this ostensibly provides users with a high degree of privacy, compelling a user to provide a password has been interpreted by some courts as a violation of our Fifth Amendment protections, becoming an often insurmountable hurdle to law enforcement lawfully executing a search warrant. This paper will explore some of the …

Evaluation Of Standard And Semantically-Augmented Distance Metrics For Neurology Patients, Daniel B. Hier, Jonathan Kopel, Steven U. Brint, Donald C. Wunsch, Gayla R. Olbricht, Sima Azizi, Blaine Allen

Electrical and Computer Engineering Faculty Research & Creative Works

Background: Patient distances can be calculated based on signs and symptoms derived from an ontological hierarchy. There is controversy as to whether patient distance metrics that consider the semantic similarity between concepts can outperform standard patient distance metrics that are agnostic to concept similarity. The choice of distance metric can dominate the performance of classification or clustering algorithms. Our objective was to determine if semantically augmented distance metrics would outperform standard metrics on machine learning tasks.

Methods: We converted the neurological findings from 382 published neurology cases into sets of concepts with corresponding machine-readable codes. We calculated patient distances by …

Misogyny Detection In Social Media On The Twitter Platform, Elena Shushkevich

Doctoral

The thesis is devoted to the problem of misogyny detection in social media. In the work we analyse the difference between all offensive language and misogyny language in social media, and review the best existing approaches to detect offensive and misogynistic language, which are based on classical machine learning and neural networks. We also review recent shared tasks aimed to detect misogyny in social media, several of which we have participated in. We propose an approach to the detection and classification of misogyny in texts, based on the construction of an ensemble of models of classical machine learning: Logistic Regression, …

Assessing The Role Of Social Media Platforms In The Propagation Of Toxicity, Adewale Muyiwa Obadimu

Theses and Dissertations

The increased global salience of social media has fueled the propagation of various forms of toxicity. As digital technologies and interactive websites proliferate, Online Social Networks (OSNs), once regarded as safe havens for sharing information and providing mutual support among groups of people, have now become breeding grounds for spreading toxic behaviors, political propaganda and radicalizing content. Numerous platforms are trying to combat this phenomenon by training computational methods that are capable of automatically recognizing these toxic contents and removing them from the user-generated text on their platforms. However, given the immensity and speed of content posted on online platforms, …

Credibility Assessment Of Fault Injection Simulation Based On Feature Selective Validation, Li Sheng, Yuxiao Li

Journal of System Simulation

Abstract: Aiming at the complexity and large number feature details of the data of fault injection simulation which lead to the difficulty for the single indicators or expert visual assessment methods to obtain the accurate assessment results, and the evaluation expert giving the interval complementary judgment matrix on the basis of AHP method which lead to the difficulty for the weights of credibility indicators to be determined, a multi-indicator comprehensive credibility assessment model based on Feature Selection Verification (FSV) is proposed. It can calculate the quantitative credibility values and the qualitative credibility values of the credibility indicators. In order …

Group Decision Making Model For Weapon Selection Using Extended Vikor Method Under Intuitionistic Fuzzy Environment, Shanliang Yang, Wang Peng, Li Ge, Kedi Huang

Journal of System Simulation

Abstract: With respect to weapon system selection problem, in which attribute weights are completely unknown and attribute values are expressed with linguistic information, a multi-attribute group decision-making method based on extended VIKOR was proposed. The intuitionistic fuzzy weighted averaging (IFWA) operator was introduced to aggregate all the individual decision-making information in order to obtain the intuitionistic fuzzy decision matrix. The intuitionistic fuzzy entropy method was utilized to obtain the objective weights of evaluation criteria. The alternative weapon systems were ranked according to the basic concept of extended VIKOR method. A case study of air-to-ground guided missile selection problem for UCAV …

A Study Of Information Bots And Knowledge Bots, Amartya Hatua

Dissertations

In this dissertation, a study of different aspects of information bots and knowledge bots is done. The research contributes to a better understanding of the various characteristics of information bots as well as the different patterns and factors responsible for the information diffusion in a social network. This research also shows how these factors can be used to predict information diffusion for a particular topic in a social network. The second part of the research is focused on strategies for improving the knowledge base of knowledge bots, where two different approaches are studied. In the first approach, knowledge is transferred …

Detecting Undisclosed Paid Editing In Wikipedia, Nikesh Joshi

Boise State University Theses and Dissertations

Wikipedia is a free and open-collaboration based online encyclopedia. The website has millions of pages that are maintained by thousands of volunteer editors. It is part of Wikipedia’s fundamental principles that pages are written with a neutral point of view and are maintained by volunteer editors for free with well-defined guidelines in order to avoid or disclose any conflict of interest. However, there have been several known incidents where editors intentionally violate such guidelines in order to get paid (or even extort money) for maintaining promotional spam articles without disclosing such information.

This thesis addresses for the first time the …

Rethinking Pruning For Accelerating Deep Inference At The Edge, Dawei Gao, Xiaoxi He, Zimu Zhou, Yongxin Tong, Ke Xu, Lothar Thiele

Research Collection School Of Computing and Information Systems

There is a growing trend to deploy deep neural networks at the edge for high-accuracy, real-time data mining and user interaction. Applications such as speech recognition and language understanding often apply a deep neural network to encode an input sequence and then use a decoder to generate the output sequence. A promising technique to accelerate these applications on resource-constrained devices is network pruning, which compresses the size of the deep neural network without severe drop in inference accuracy. However, we observe that although existing network pruning algorithms prove effective to speed up the prior deep neural network, they lead to …

Refactoring From 9 To 5? What And When Employees And Volunteers Contribute To Oss, Luiz Felipe Dias, Caio Barbosa, Gustavo Pinto, Igor Steinmacher, Baldoino Fonseca, Márcio Ribeiro, Christoph Treude, Daniel Alencar Da Costa

Research Collection School Of Computing and Information Systems

In this paper we characterize the contributions made by employees (developers that work for GitHub, the company) and volunteers (developers that use GitHub, the platform) to OSS projects maintained by GitHub (the company) on GitHub (the platform). By mining activities performed in five well-known company-owned OSS projects, we investigate what they do and when they do it. We found that the majority of the volunteers' contributions are related to reengineering (e.g., refactoring), while employees focus more on management (e.g., documentation). When it comes to the working hours, we found that contributions are made mostly from 9am-5pm, even for the volunteers.

Hierarchical Syntactic Models For Human Activity Recognition Through Mobility Traces, Enrico Casella, Marco Ortolani, Simone Silvestri, Sajal K. Das

Computer Science Faculty Research & Creative Works

Recognizing users’ daily life activities without disrupting their lifestyle is a key functionality to enable a broad variety of advanced services for a Smart City, from energy-efficient management of urban spaces to mobility optimization. In this paper, we propose a novel method for human activity recognition from a collection of outdoor mobility traces acquired through wearable devices. Our method exploits the regularities naturally present in human mobility patterns to construct syntactic models in the form of finite state automata, thanks to an approach known as grammatical inference. We also introduce a measure of similarity that accounts for the intrinsic hierarchical …

Diffusion Of Falsehoods On Social Media, Kelvin Kizito King

Theses and Dissertations

Misinformation has captured the interest of academia in recent years with several studies looking at the topic broadly. However, these studies mostly focused on rumors which are social in nature and can be either classified as false or real. In this research, we attempt to bridge the gap in the literature by examining the impacts of user characteristics and feature contents on the diffusion of (mis)information using verified true and false information. We apply a topic allocation model augmented by both supervised and unsupervised machine learning algorithms to identify tweets on novel topics. We find that retweet count is higher …

An Attention-Based Rumor Detection Model With Tree-Structured Recursive Neural Networks, Jing Ma, Wei Gao, Shafiq Joty, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Rumor spread in social media severely jeopardizes the credibility of online content. Thus, automatic debunking of rumors is of great importance to keep social media a healthy environment. While facing a dubious claim, people often dispute its truthfulness sporadically in their posts containing various cues, which can form useful evidence with long-distance dependencies. In this work, we propose to learn discriminative features from microblog posts by following their non-sequential propagation structure and generate more powerful representations for identifying rumors. For modeling non-sequential structure, we first represent the diffusion of microblog posts with propagation trees, which provide valuable clues on how …

Cloud Resource Prediction Using Explainable And Cooperative Artificial Neural Networks, Nathan R. Nelson

Graduate Theses/Dissertations

This work proposes a system for predicting cloud resource utilization by using runtime assembled cooperative artificial neural networks (RACANN). RACANN breaks up the problem into smaller contexts, each represented by a small-scale artificial neural network (ANN). The relevant ANNs are joined together at runtime when the context is present in the data for training and predictions. By analyzing the structure of a complete ANN, the influence of inputs is calculated and used to create linguistic descriptions (LD) of model behavior, so RACANN becomes explainable (eRACANN). The predictive results of eRACANN are compared against its prototype and a single deep ANN …

Virtual Temari: Artistically Inspired Mathematics, Carl Giuffre, Lee Stemkoski

Journal of Humanistic Mathematics

Technology can be a significant aide in understanding and appreciating geometry, beyond theoretical considerations. Both fiber art and technology have been employed as a significant aide and an inspiring vessel in education to explore geometry. The Japanese craft known as temari, or "hand-balls", combines important artistic, spiritual, and familial values, and provides one such approach to exploring geometry. Mathematically, the artwork of temari may be classified based on whether they are inspired by polyhedra and discrete patterns or by periodic functional curves. The resulting designs of these categories provide an ancient vantage for displaying spherical patterns. We illustrate a …

Effect Of Text Processing Steps On Twitter Sentiment Classification Using Word Embedding, Manar D. Samad, Nalin D. Khounviengxay, Megan A. Witherow

Computer Science Faculty Research

Processing of raw text is the crucial first step in text classification and sentiment analysis. However, text processing steps are often performed using off-the-shelf routines and pre-built word dictionaries without optimizing for domain, application, and context. This paper investigates the effect of seven text processing scenarios on a particular text domain (Twitter) and application (sentiment classification). Skip gram-based word embeddings are developed to include Twitter colloquial words, emojis, and hashtag keywords that are often removed for being unavailable in conventional literature corpora. Our experiments reveal negative effects on sentiment classification of two common text processing steps: 1) stop word removal …

A Computer Science Academic Vocabulary List, David Roesler

Dissertations and Theses

This thesis documents the development of the Computer Science Academic Vocabulary List (CSAVL), a pedagogical tool intended for use by English-for-specific-purpose educators and material developers. A 3.5-million-word corpus of academic computer science textbooks and journal articles was developed in order to produce the CSAVL. This study draws on the improved methodologies used in the creation of recent lemma-based word lists such as the Academic Vocabulary List (AVL) and the Medical Academic Vocabulary List (MAVL), which take into account the discipline-specific meanings of academic vocabulary. The CSAVL provides specific information for each entry, including part of speech and CS-specific meanings in …

Lulling Waters: A Poetry Reading For Real-Time Music Generation Through Emotion Mapping, Ashley Muniz, Toshihisa Tsuruoka

Electronic Literature Organization Conference 2020

Through a poetic narrative, “Lulling Waters” tells the story of a whale overcoming the loss of his mother, who passed away from ingesting plastic, as he attempts to escape from the polluted oceanic world. The live performance of this poem utilizes a software system called Soundwriter, which was developed with the goal of enriching the oral storytelling experience through music. This video demonstrates how Soundwriter’s real-time hybrid system was able to analyze “Lulling Waters” through its lexical and auditory features. Emotionally salient words were given ratings based on arousal, valence, and dominance while the emotionally charged prosodic features of the …

Poetry For Seers Or The Peruvian Visual Poetic Tradition In Front Of New Media, Michael Hurtado, Pamela Medina, Enrique García, Michael Prado

Electronic Literature Organization Conference 2020

Since the first decades of the twentieth century, Peruvian poetic tradition has been characterized by experimental uses of language. Among these possibilities, some records tensioned this medium from the link with the plastic arts, as in the case of the poetry of José María Eguren, while others opted for the playing with the spatiality and visuality of the blank sheet, such as in the case of the work of Carlos Oquendo de Amat. However, it is not until the appearance of the poetry of César Vallejo, specifically with a poems like Trilce in 1922, that these breakages force us to …

From Ai With Love: Reading Big Data Poetry Through Gilbert Simondon’S Theory Of Transduction, Andrew Klobucar

Electronic Literature Organization Conference 2020

Computation initiated a far-reaching re-imagination of language, not just as an information tool, but as a social, bio-physical activity in general. Modern lexicology provides an important overview of the ongoing development of textual documentation and its applications in relation to language and linguistics. At the same time, the evolution of lexical tools from the first dictionaries and graphs to algorithmically generated scatter plots of live online interaction patterns has been surprisingly swift. Modern communication and information studies from Norbert Weiner to the present-day support direct parallels between coding and linguistic systems. However, most theories of computation as a model of …

Autopia And The Truelist: Language Combined In Two Computer-Generated Books, Nick Montfort

Electronic Literature Organization Conference 2020

Autopia (Troll Thread, 2016) and The Truelist (Counterpath, 2017) are computer-generated literary books. I reported at ELO 2014 on two of my text-generating “novel machines” (Montfort 2014). The two projects discussed in this paper are about novel-size, but are different sorts of projects. Autopia’s text consists of headline-style sentences made entirely of the singular and plural names of cars. This project manifests not only as a print-on-demand book from a post-digital publisher, but also as a web project and a gallery installation. The Truelist’s 140 pages of verse are available in offset printed book form and also as a …

Rrsds: Towards A Robot-Ready Spoken Dialogue System, Casey Kennington, Daniele Moro, Lucas Marchand, Jake Carns, David Mcneill

Computer Science Faculty Publications and Presentations

Spoken interaction with a physical robot requires a dialogue system that is modular, multimodal, distributive, incremental and temporally aligned. In this demo paper, we make significant contributions towards fulfilling these requirements by expanding upon the ReTiCo incremental framework. We outline the incremental and multimodal modules and how their computation can be distributed. We demonstrate the power and flexibility of our robot-ready spoken dialogue system to be integrated with almost any robot.

Semantics With Feeling: Emotions For Abstract Embedding, Affect For Concrete Grounding, Daniele Moro, Gerardo Caracas, David Mcneill, Casey Kennington

Computer Science Faculty Publications and Presentations

An important yet underexplored aspect of meaning in both distributional and grounded models of semantics is emotion. In this paper, we explore how emotion can be predicted from descriptions of robot behaviors represented with embeddings. We then compare this approach with a grounded model that maps corresponding robot behaviors represented as internal states to the same emotion labels and discover comparable results. We then take the predictions from the second model and use them as a proxy for concrete affect (as opposed to abstract emotion) and use this derived affect to ground a semantic classifier in a retrieval task and …

Learning Word Groundings From Humans Facilitated By Robot Emotional Displays, David Mcneill, Casey Kennington

Computer Science Faculty Publications and Presentations

In working towards accomplishing a human-level acquisition and understanding of language, a robot must meet two requirements: the ability to learn words from interactions with its physical environment, and the ability to learn language from people in settings for language use, such as spoken dialogue. In a live interactive study, we test the hypothesis that emotional displays are a viable solution to the cold-start problem of how to communicate without relying on language the robot does not–indeed, cannot–yet know. We explain our modular system that can autonomously learn word groundings through interaction and show through a user study with 21 …

Optimising The Fit Of Stack Overflow Code Snippets Into Existing Code, Brittany Reid, Christoph Treude, Markus Wagner

Research Collection School Of Computing and Information Systems

Software developers often reuse code from online sources such as Stack Overflow within their projects. However, the process of searching for code snippets and integrating them within existing source code can be tedious. In order to improve efficiency and reduce time spent on code reuse, we present an automated code reuse tool for the Eclipse IDE (Integrated Developer Environment), NLP2TestableCode. NLP2TestableCode can not only search for Java code snippets using natural language tasks, but also evaluate code snippets based on a user’s existing code, modify snippets to improve fit and correct errors, before presenting the user with the best snippet, …