Digital Commons Network^™

Bridge Text And Knowledge By Learning Multi-Prototype Entity Mention Embedding, Yixin Cao, Lifu Huang, Heng Ji, Xu Chen, Juanzi Li

Research Collection School Of Computing and Information Systems

Integrating text and knowledge into a unified semantic space has attracted significant research interests recently. However, the ambiguity in the common space remains a challenge, namely that the same mention phrase usually refers to various entities. In this paper, to deal with the ambiguity of entity mentions, we propose a novel Multi-Prototype Mention Embedding model, which learns multiple sense embeddings for each mention by jointly modeling words from textual contexts and entities derived from a knowledge base. In addition, we further design an efficient language model based approach to disambiguate each mention to a specific sense. In experiments, both qualitative …

Tool Support For Capturing The Essence Of A Concern In Source Code, Chuntao Fu

Student Work

Software evolves constantly to adapt to changing user needs. As it evolves, it becomes progressively harder to understand due to accumulation of code changes, increasing code size, and the introduction of complex code dependencies. As a result, it becomes harder to maintain, exposing the software to potential bugs and degradation of code quality. High maintenance costs and diminished opportunities for software reusability and portability lead to reduced return on investment, increasing the likelihood of the software product being discarded or replaced. Nevertheless, we believe that there is value in legacy software due to the amount of intellectual efforts that have …

Can Syntax Help? Improving An Lstm-Based Sentence Compression Model For New Domains, Liangguo Wang, Jing Jiang, Hai Leong Chieu, Chen Hui Ong, Dandan Song, Lejian Liao

Research Collection School Of Computing and Information Systems

In this paper, we study how to improve thedomain adaptability of a deletion-basedLong Short-Term Memory (LSTM) neuralnetwork model for sentence compression.We hypothesize that syntactic informationhelps in making such modelsmore robust across domains. We proposetwo major changes to the model: usingexplicit syntactic features and introducingsyntactic constraints through Integer LinearProgramming (ILP). Our evaluationshows that the proposed model works betterthan the original model as well as a traditionalnon-neural-network-based modelin a cross-domain setting.

Embedding-Based Representation Of Categorical Data By Hierarchical Value Coupling Learning, Songlei Jian, Longbing Cao, Guansong Pang, Kai Lu, Hang Gao

Research Collection School Of Computing and Information Systems

Learning the representation of categorical data with hierarchical value coupling relationships is very challenging but critical for the effective analysis and learning of such data. This paper proposes a novel coupled unsupervised categorical data representation (CURE) framework and its instantiation, i.e., a coupled data embedding (CDE) method, for representing categorical data by hierarchical value-to-value cluster coupling learning. Unlike existing embedding- and similarity-based representation methods which can capture only a part or none of these complex couplings, CDE explicitly incorporates the hierarchical couplings into its embedding representation. CDE first learns two complementary feature value couplings which are then used to cluster …

A Research Stream On Sentiment Analysis, B. Yuan, Keng Siau

Research Collection School Of Computing and Information Systems

Sentiment analysis (SA) is a powerful mining technique to study online reviews and comments (Lee & Siau, 2001; Adeborna & Siau, 2014; Zhao & Siau, 2017). It is an advanced text mining technique and the goal of SA is to recognize and extract meaningful information from data using natural language processing (NLP) and computational linguistics.SA has been applied to areas such as marketing, online social media, customer service, education, and even energy fields (Yuan & Siau, 2017). For example, SA can be used to identify the attitude of customers according to polarity of the reviews and comments that they left …

How To Enhance Interdisciplinary Competence—Interdisciplinary Problem-Based Learning Versus Interdisciplinary Project-Based Learning, Mirjam Brassler, Jan Dettmers

Interdisciplinary Journal of Problem-Based Learning

Interdisciplinary competence is important in academia for both employability and sustainable development. However, to date, there are no specific interdisciplinary education models and, naturally, no empirical studies to assess them. Since problem-based learning (PBL) and project-based learning (PjBL) are learning approaches that emphasize students’ collaboration, both pedagogies seem suitable to enhance students’ interdisciplinary competence. Based on the principle of constructive alignment and four instructional principles on interdisciplinary learning, this paper proposes that students profit more from interdisciplinary PBL (iPBL) than interdisciplinary PjBL (iPjBL). A pre-post study was conducted with a sample of 95 students participating in iPBL and 183 students …

A Pattern Approach To Examine The Design Space Of Spatiotemporal Visualization, Chen Guo

Department of Computer Graphics Technology Degree Theses

Pattern language has been widely used in the development of visualization systems. This dissertation applies a pattern language approach to explore the design space of spatiotemporal visualization. The study provides a framework for both designers and novices to communicate, develop, evaluate, and share spatiotemporal visualization design on an abstract level. The touchstone of the work is a pattern language consisting of fifteen design patterns and four categories. In order to validate the design patterns, the researcher created two visualization systems with this framework in mind. The first system displayed the daily routine of human beings via a polygon-based visualization. The …

Explaining Trained Neural Networks With Semantic Web Technologies: First Steps, Md Kamruzzaman Sarker, Ning Xie, Derek Doran, Michael L. Raymer, Pascal Hitzler

Computer Science and Engineering Faculty Publications

The ever increasing prevalence of publicly available struc-tured data on the World Wide Web enables new applications in a varietyof domains. In this paper, we provide a conceptual approach that lever-ages such data in order to explain the input-output behavior of trainedartificial neural networks. We apply existing Semantic Web technologiesin order to provide an experimental proof of concept.

Multifaceted Mathematicians, Juan M. Sepulcre

Journal of Humanistic Mathematics

This report attempts to provide an overview of some of the mathematicians who have combined their mathematical knowledge with other academic and non-academic specialities. The various examples given, many of them included in the well-known MacTutor History of Mathematics archive, corroborate the fact that although the idea of the typical polymath has receded with the passage of time, until the end of the Renaissance, most well-known mathematicians were also well-versed in a number of different sciences such as philosophy, astronomy, and physics. We also highlight other, less common combinations of knowledge, in famous mathematicians who were experts in other disciplines …

On Commensurability And Symmetry, David Pierce

Journal of Humanistic Mathematics

Commensurability and symmetry have diverged from a common Greek origin. We review the history of this divergence. In mathematics, symmetry is now a kind of measure that is different from size, though analogous to it. Size being given by numbers, the concept of numbers and their equality comes into play. For Euclid, two magnitudes were symmetric when they had a common measure; also, numbers were magnitudes, commonly represented as bounded straight lines, for which equality was congruence. When Billingsley translated Euclid into English in the sixteenth century, he used the word "commensurable" for Euclid's symmetric magnitudes; but the word had …

Perchance To Dream: Art, Mathematics, And Shakespeare, Randall E. Cone

Journal of Humanistic Mathematics

Visual representation of textual works has often aided in the understanding of sophisticated concepts. In the Digital Age this is particularly true, given the advent of natural language processing, the ubiquity of general programming languages, and the maturation of digital visualization. In this article, we eschew the traditional disciplinary boundaries to view and analyze Shakespeare’s works in various ways. Our point of departure is Hamlet, where we first examine the play as a unity — both graphically and analytically. We then focus on Act III, Scene 1, where we analyze one of the most famous passages in English Literature: …

Detecting User Demographics In Twitter To Inform Health Trends In Social Media, Christopher R. Markson

Dissertations

The widespread and popular use of social media and social networking applications offer a promising opportunity for gaining knowledge and insights regarding population health conditions thanks to the diversity and abundance of online user-generated information (UGHI) relating to healthcare and well-being. However, users on social media and social networking sites often do not supply their complete demographic information, which greatly undermines the value of the aforementioned information for health 2.0 research, e.g., for discerning disparities across population groups in certain health conditions. To recover the missing user demographic information, existing methods observe a limited scope of user behaviors, such as …

Discovering Explanatory Models To Identify Relevant Tweets On Zika, Roopteja Muppalla, Michele Miller, Tanvi Banerjee, William L. Romine

Kno.e.sis Publications

Zika virus has caught the worlds attention, and has led people to share their opinions and concerns on social media like Twitter. Using text-based features, extracted with the help of Parts of Speech (POS) taggers and N-gram, a classifier was built to detect Zika related tweets from Twitter. With a simple logistic classifier, the system was successful in detecting Zika related tweets from Twitter with a 92% accuracy. Moreover, key features were identified that provide deeper insights on the content of tweets relevant to Zika. This system can be leveraged by domain experts to perform sentiment analysis, and understand the …

Truly Multi-Modal Youtube-8m Video Classification With Video, Audio, And Text, Zhe Wang, Kingsley Kuan, Mathieu Ravant, Gaurav Manek, Sibo Song, Yuan Fang, Et Al

Research Collection School Of Computing and Information Systems

The YouTube-8M video classification challenge requires teams to classify 0.7 million videos into one or more of 4,716 classes. In this Kaggle competition, we placed in the top 3% out of 650 participants using released video and audio features. Beyond that, we extend the original competition by including text information in the classification, making this a truly multi-modal approach with vision, audio and text. The newly introduced text data is termed as YouTube-8M-Text. We present a classification framework for the joint use of text, visual and audio features, and conduct an extensive set of experiments to quantify the benefit that …

A Domain Based Approach To Social Relation Recognition, Qianru Sun, Bernt Schiele, Mario Fritz

Research Collection School Of Computing and Information Systems

Social relations are the foundation of human daily life. Developing techniques to analyze such relations from visual data bears great potential to build machines that better understand us and are capable of interacting with us at a social level. Previous investigations have remained partial due to the overwhelming diversity and complexity of the topic and consequently have only focused on a handful of social relations. In this paper, we argue that the domain-based theory from social psychology is a great starting point to systematically approach this problem. The theory provides coverage of all aspects of social relations and equally is …

Demographics Of News Sharing In The U.S. Twittersphere, Julio C.S. Reis, Haewoon Kwak, Jisun An, Johnnatan Messias, Benevenuto Fabrıcio.

Research Collection School Of Computing and Information Systems

The widespread adoption and dissemination of online news through social media systems have been revolutionizing many segments of our society and ultimately our daily lives. In these systems, users can play a central role as they share content to their friends. Despite that, little is known about news spreaders in social media. In this paper, we provide the first of its kind in-depth characterization of news spreaders in social media. In particular, we investigate their demographics, what kind of content they share, and the audience they reach. Among our main findings, we show that males and white users tend to …

A Critical Path Problem Using Triangular Neutrosophic Number, Florentin Smarandache, Mai Mohamed, Yongquan Zhou, Mohamed Abdel-Baset

Branch Mathematics and Statistics Faculty and Staff Publications

The Critical Path Method (CPM) is one of several related techniques for planning and managing of complicated projects in real world applications. In many situations, the data obtained for decision makers are only approximate, which gives rise of neutrosophic critical path problem. In this paper, the proposed method has been made to find the critical path in network diagram, whose activity time uncertain. The vague parameters in the network are represented by triangular neutrosophic numbers, instead of crisp numbers. At the end of paper, two illustrative examples are provided to validate the proposed approach.

Towards A More Representative Definition Of Cyber Security, Daniel Schatz, Rabih Bashroush, Julie Wall

Journal of Digital Forensics, Security and Law

In recent years, ‘Cyber Security’ has emerged as a widely-used term with increased adoption by practitioners and politicians alike. However, as with many fashionable jargon, there seems to be very little understanding of what the term really entails. Although this is may not be an issue when the term is used in an informal context, it can potentially cause considerable problems in context of organizational strategy, business objectives, or international agreements. In this work, we study the existing literature to identify the main definitions provided for the term ‘Cyber Security’ by authoritative sources. We then conduct various lexical and semantic …

The Rhetoric Of Scientific Authority: A Rhetorical Examination Of _An Inconvenient Truth_, Alexander W. Morales

USF Tampa Graduate Theses and Dissertations

This thesis project examines how scientific authority is produced through rhetorical practices instead of the “information deficit” model of science communication. By conducting a rhetorical analysis of the science documentary An Inconvenient Truth, this project demonstrates how the documentary format itself and the film’s leading agent, former United States Vice President Al Gore, attempt to persuade audiences through building degrees of scientific authority by employing multiple rhetorics or narrative themes of science to bolster the scientific facts supporting anthropogenic climate change. Additionally, I demonstrate how these narrative themes parallel three scholarly themes within the rhetoric of science literature: science …

Question Type Recognition Using Natural Language Input, Aishwarya Soni

Master's Projects

Recently, numerous specialists are concentrating on the utilization of Natural Language Processing (NLP) systems in various domains, for example, data extraction and content mining. One of the difficulties with these innovations is building up a precise Question and Answering (QA) System. Question type recognition is the most significant task in a QA system, for example, chat bots. Organization such as National Institute of Standards (NIST) hosts a conference series called as Text REtrieval Conference (TREC) series which keeps a competition every year to encourage and improve the technique of information retrieval from a large corpus of text. When a user …

Back To The Future: Logic And Machine Learning, Simon Dobnik, John D. Kelleher

Conference papers

In this paper we argue that since the beginning of the natural language processing or computational linguistics there has been a strong connection between logic and machine learning. First of all, there is something logical about language or linguistic about logic. Secondly, we argue that rather than distinguishing between logic and machine learning, a more useful distinction is between top-down approaches and data-driven approaches. Examining some recent approaches in deep learning we argue that they incorporate both properties and this is the reason for their very successful adoption to solve several problems within language technology.

Axioms: Mathematical And Spiritual: What Says The Parable?, Melvin Royer

ACMS Conference Proceedings 2017

Relational structure A is compact provided for any structure Jffi of the same signature, if every finite substructure of Jffi has a homomorphism to A then so does Jffi. The Constraint Satisfaction Problem (CSP) for A is the computational problem of determining whether finite structures have homomorphisms into A. We explore a connection between the hierarchy of logical axioms and the complexity hierarchy of CSPs: It appears that the complexity of CSP for A corresponds to the strength of the axiom "A is compact". At the top, the statement "K3 is compacts" is logically equivalent to the compactness theorem. Thus …

The R Journal (June 2017) 9(1): Complete Issue, The R Foundation

The R Journal

Editorial, Roger Bivand

Contributed Research Articles

iotools: High-Performance I/O Tools for R, Taylor Arnold, Michael J. Kane, and Simon Urbanek

IsoGeneGUI: Multiple Approaches for Dose-Response Analysis of Microarray Data Using R, Martin Otava, Rudradev Sengupta, Ziv Shkedy, Dan Lin, Setia Pramana, Tobias Verbeke, Philippe Haldermans, Ludwig A. Hothorn, Daniel Gerhard, Rebecca M. Kuiper, Florian Klinglmueller, and Adetayo Kasim

Network Visualization with ggplot2, Sam Tyner, François Briatte, and Heike Hofmann

OrthoPanels: An R Package for Estimating a Dynamic Panel Model with Fixed Effects Using the Orthogonal Reparameterization Approach, Mark Pickup, Paul Gustafson, Davor Cubranic, and Geoffrey Evans

The mosaic Package: Helping …

Multilabel Classification With R Package Mlr, Philipp Probst, Quay Au, Giuseppe Casalicchio, Clemens Stachl, Bernd Bischl

The R Journal

We implemented several multilabel classification algorithms in the machine learning package mlr. The implemented methods are binary relevance, classifier chains, nested stacking, dependent binary relevance and stacking, which can be used with any base learner that is accessible in mlr. Moreover, there is access to the multilabel classification versions of random ForestSRC and rFerns. All these methods can be easily compared by different implemented multilabel performance measures and resampling methods in the standardized mlr framework. In a benchmark experiment with several multilabel datasets, the performance of the different methods is evaluated.

Comparing Grounded Theory And Topic Modeling: Extreme Divergence Or Unlikely Convergence?, Eric P.S. Baumer, David Mimno, Shion Guha, Emily Quan, Geri K. Gay

Mathematics, Statistics and Computer Science Faculty Research and Publications

Researchers in information science and related areas have developed various methods for analyzing textual data, such as survey responses. This article describes the application of analysis methods from two distinct fields, one method from interpretive social science and one method from statistical machine learning, to the same survey data. The results show that the two analyses produce some similar and some complementary insights about the phenomenon of interest, in this case, nonuse of social media. We compare both the processes of conducting these analyses and the results they produce to derive insights about each method's unique advantages and drawbacks, as …

Bug Characteristics In Blockchain Systems: A Large-Scale Empirical Study, Zhiyuan Wan, David Lo, Xin Xia, Liang Cai

Research Collection School Of Computing and Information Systems

Bugs severely hurt blockchain system dependability. A thorough understanding of blockchain bug characteristics is required to design effective tools for preventing, detecting and mitigating bugs. We perform an empirical study on bug characteristics in eight representative open source blockchain systems. First, we manually examine 1,108 bug reports to understand the nature of the reported bugs. Second, we leverage card sorting to label the bug reports, and obtain ten bug categories in blockchain systems. We further investigate the frequency distribution of bug categories across projects and programming languages. Finally, we study the relationship between bug categories and bug fixing time. The …

Aliner: An R Package For Optimizing Feature-Weighted Alignments And Linguistic Distances, Sean S. Downey, Guowei Sun, Peter Norquest

The R Journal

Linguistic distance measurements are commonly used in anthropology and biology when quantitative and statistical comparisons between words are needed. This is common, for example, when analyzing linguistic and genetic data. Such comparisons can provide insight into historical population patterns and evolutionary processes. However, the most commonly used linguistic distances are derived from edit distances, which do not weight phonetic features that may, for example, represent smaller-scale patterns in linguistic evolution. Thus, computational methods for calculating feature-weighted linguistic distances are needed for linguistic, biological, and evolutionary applications; additionally, the linguistic distances presented here are generic and may have broader applications in …

Neutrosophy, A Sentiment Analysis Model, Florentin Smarandache, Mirela Teodorescu, Daniela Gifu

Branch Mathematics and Statistics Faculty and Staff Publications

This paper describes the importance of Neutrosophy Theory in order to find a method that could solve the uncertainties arising on discursive analysis. The aim of this pilot study is to find a procedure to diminish the uncertainties from public discourse induced, especially, by humans (politicians, journalists, etc.). We consider that Neutrosophy Theory is a sentiment analysis specific case regarding processing of the three states: positive, negative, and neutral. The study is intended to identify a method to answer to uncertainties solving in order to support politician's staff, NLP specialists, artificial intelligence researchers and generally the electors.

An Exploratory Study Of Functionality And Learning Resources Of Web Apis On Programmableweb, Yuan Tian, Pavneet Singh Kochhar, David Lo

Research Collection School Of Computing and Information Systems

Web APIs provide various functionalities that can be leveraged by developers in building their applications. ProgrammableWeb, which is the largest and most active web API and mashup collection, provides a record of thousands of web APIs and mashups. However, important properties about these large number of web APIs, such as their functionality and support/resources for learning, have never been studied by the existing research work. In this study, we perform an exploratory analysis on functionality and learning resources of 9,883 web APIs and 4,315 mashups listed on ProgrammableWeb, and find that: (1) web APIs provide a wide range of functionalities …

Employing Smartwatch For Enhanced Password Authentication, Bing Chang, Ximing Liu, Yingjiu Li, Pingjian Wang, Wen-Tao Zhu, Zhan Wang

Research Collection School Of Computing and Information Systems

This paper presents an enhanced password authentication scheme by systematically exploiting the motion sensors in a smartwatch. We extract unique features from the sensor data when a smartwatch bearer types his/her password (or PIN), and train certain machine learning classifiers using these features. We then implement smartwatch-aided password authentication using the classifiers. Our scheme is user-friendly since it does not require users to perform any additional actions when typing passwords or PINs other than wearing smartwatches. We conduct a user study involving 51 participants on the developed prototype so as to evaluate its feasibility and performance. Experimental results show that …