Computational Linguistics Commons^™

Enhancing The Performance Of Ir-Based Traceability Recovery Of Requirement Artifacts Using Noun Phrases, Dafaalla Abdelrahman Mashahi Khalafalla

Student Works (2020-2029)

Requirement traceability can be considered as a measure of software quality to help achieve validation, verification, and reusability. Neglecting traceability leads to less maintainable software. Creating traceability links after-the-fact, known as traceability recovery, is a tedious and time-consuming process when it is done manually. Therefore, information retrieval (IR) methods have been used to automatically identify traceability links between the artifacts. However, as a result of limitations of the software engineer and the IR techniques, the performance of the IR methods is negatively affected. There is no IR method that is able to recover traceability links between artifacts with high precision …

Empirical Analysis Of Cbow And Skip Gram Nlp Models, Tejas Menon

University Honors Theses

CBOW and Skip Gram are two NLP techniques to produce word embedding models that are accurate and performant. They were invented in the seminal paper by T. Mikolov et al. and have since observed optimizations such as negative sampling and subsampling. This paper implements a fully-optimized version of these models using Py-Torch and runs them through a toy sentiment/subject analysis. It is weakly observed that different corpus types affect the skew of word embeddings such that fictional corpus are better suited for sentiment analysis and non-fictional for subject analysis.

Automatic Keyphrase Extraction From Russian-Language Scholarly Papers In Computational Linguistics, Yves Wienecke

University Honors Theses

The automatic extraction of keyphrases from scholarly papers is a necessary step for many Natural Language Processing (NLP) tasks, including text retrieval, machine translation, and text summarization. However, due to the different grammatical and semantic intricacies of languages, this is a highly language-dependent task. Many free and open source implementations of state-of-the-art keyphrase extraction techniques exist, but they are not adapted for processing Russian text. Furthermore, the multi-linguistic character of scholarly papers in the field of Russian computational linguistics and NLP introduces additional complexity to keyphrase extraction. This paper describes a free and open source program as a proof of …

Doing Away With Defaults: Motivation For A Gradient Parameter Space, Katherine Howitt

Dissertations, Theses, and Capstone Projects

In this thesis, I propose a reconceptualization of the traditional syntactic parameter space of the principles and parameters framework (Chomsky, 1981). In lieu of binary parameter settings, parameter values exist on a gradient plane where a learner’s knowledge of their language is encoded in their confidence that a particular parametric target value, and thus grammatical construction of an encountered sentence, is likely to be licensed by their target grammar. First, I discuss other learnability models in the classic parameter space which lack either psychological plausibility, theoretical consistency, or some combination of the two. Then, I argue for the Gradient Parameter …

Inferring Research Fields In Administrative Records Using Text Data, Ekaterina Levitskaya

Dissertations, Theses, and Capstone Projects

The UMETRICS database (Universities: Measuring the Effects of Research on Innovation, Competitiveness, and Science) contains rich information on grants from sponsored federal and non-federal research for 32 universities over a 15-year period. It is hosted at IRIS (Institute for Research on Innovation and Science, University of Michigan) and serves as a rich source of university administrative data; however, it does not contain information on research fields. Categorizing grants data by research field can help to measure results of investment in research and science and provide evidence for the data-driven policy-making; yet administrative data often lacks this type of categorization. In …

Genderlects In Social Media, Alina Korovatskaya

Dissertations, Theses, and Capstone Projects

Many studies have found significant differences in ways men and women use language; some argue that these differences occur as a result of culture differences, and others suggest that they are influenced by differences in social status and power between the genders. However, some of the major studies were concluded decades ago and do not reflect changes in gender relations in recent years. In this study, we analyze modern conversations using two social media platforms, Twitter and Reddit, to determine whether substantial differences between men and women’s use of language were preserved between the genders.

English Wordnet Taxonomic Random Walk Pseudo-Corpora, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher

Conference papers

This is a resource description paper that describes the creation and properties of a set of pseudo-corpora generated artificially from a random walk over the English WordNet taxonomy. Our WordNet taxonomic random walk implementation allows the exploration of different random walk hyperparameters and the generation of a variety of different pseudo-corpora. We find that different combinations of the walk’s hyperparameters result in varying statistical properties of the generated pseudo-corpora. We have published a total of 81 pseudo-corpora that we have used in our previous research, but have not exhausted all possible combinations of hyperparameters, which is why we have also …

Chaprates, Brinly Xavier, Micole Amanda Marietta, Nidhi Vedantam

Student Scholar Symposium Abstracts and Posters

On the Chapman campus, through taking and choosing various classes, there is a significant need for communication and feedback between students and peers, professors, tutors, and study groups. With this, we wanted to create an application that enables users from various majors to not only easily and effectively communicate with various people in their field, but one that also enables them to give and receive feedback on various classes through a rating system. We believe that the application will aid students in a myriad of specific ways, including being involved in study groups and getting tutoring help, determining which classes …

Phonologically-Informed Speech Coding For Automatic Speech Recognition-Based Foreign Language Pronunciation Training, Anthony J. Vicario

Dissertations, Theses, and Capstone Projects

Automatic speech recognition (ASR) and computer-assisted pronunciation training (CAPT) systems used in foreign-language educational contexts are often not developed with the specific task of second-language acquisition in mind. Systems that are built for this task are often excessively targeted to one native language (L1) or a single phonemic contrast and are therefore burdensome to train. Current algorithms have been shown to provide erroneous feedback to learners and show inconsistencies between human and computer perception. These discrepancies have thus far hindered more extensive application of ASR in educational systems.

This thesis reviews the computational models of the human perception of American …

Computational Approaches To The Syntax–Prosody Interface: Using Prosody To Improve Parsing, Hussein M. Ghaly

Dissertations, Theses, and Capstone Projects

Prosody has strong ties with syntax, since prosody can be used to resolve some syntactic ambiguities. Syntactic ambiguities have been shown to negatively impact automatic syntactic parsing, hence there is reason to believe that prosodic information can help improve parsing. This dissertation considers a number of approaches that aim to computationally examine the relationship between prosody and syntax of natural languages, while also addressing the role of syntactic phrase length, with the ultimate goal of using prosody to improve parsing.

Chapter 2 examines the effect of syntactic phrase length on prosody in double center embedded sentences in French. Data collected …

Ghost Peppers: Using Ensemble Models To Detect Professor Attractiveness Commentary On Ratemyprofessors.Com, Angie Waller

Dissertations, Theses, and Capstone Projects

In June 2018, RateMyProfessors.com (RMP), a popular website for students to leave professor reviews, removed a controversial feature known as the “chili pepper” which allowed students to rate their professors as “hot” or “not hot.” Though past research has rigorously analyzed the correlation of the chili pepper with higher ratings in other categories (Felton, Mitchell, and Stinson, 2004; Felton et al., 2008), none has measured the effect of the removal of the chili pepper on the text content submitted by students. While it is a positive step that the chili pepper has been removed, text commentary on teacher attractiveness persists …

You Don’T Say... Linguistic Features In Sarcasm Detection, Martina Ducret, Lauren Kruse, Carlos Martinez, Anna Feldman, Jing Peng

Department of Computer Science Faculty Scholarship and Creative Works

We explore linguistic features that contribute to sarcasm detection. The linguistic features that we investigate are a combination of text and word complexity, stylistic and psychological features. We experiment with sarcastic tweets with and without context. The results of our experiments indicate that contextual information is crucial for sarcasm prediction. One important observation is that sarcastic tweets are typically incongruent with their context in terms of sentiment or emotional load.

Pmkns For Pie: Parsed Morphological Katr Networks Of Sanskrit For Proto-Indo-European, Ryan Mark Mcdonald

Theses and Dissertations--Linguistics

In this thesis, I construct two computational networks for Sanskrit to test theories of nominal accentuation as a way of examining the simplicity of each theory. I will be examining the Paradigmatic Approach and the Compositional Approach to nominal accentuation. For the Paradigmatic Approach, nominals are categorized into mobile and static categories based on how the accent appears in the paradigm (Fortson 2010). For the Compositional Approach, accent mobility is a result of the combination of morphemes and their inherent accent states (Kirparsky 2010). To construct these networks, I use the KATR extension to the DATR language for lexical knowledge …

The Stained Glass Of Knowledge: On Understanding Novice Mental Models Of Computing, Briana Christina Bettin

Dissertations, Master's Theses and Master's Reports

Learning to program can be a novel experience. The rigidity of programming can be at odds with beginning programmer's existing perceptions, and the concepts can feel entirely unfamiliar. These observations motivated this research, which explores two major questions: What factors influence how novices learn programming? and How can analogy by more appropriately leveraged in programming education?

This dissertation investigates the factors influencing novice programming through multiple methods. The CS1 classroom is observed as a "whole system", with consideration to the factors present in it that can influence the learning process. Learning's cognitive processes are elaborated to ground exploration into specifically …

Scholarly Communication And Documentary Fragmentations In The Public Space: A Functional Citation Study, Fidelia Ibekwe, Lucie Loubère

Proceedings from the Document Academy

This paper studies how academic content published in Open Edition.org, an online publication platform in the Social Sciences and Humanities is re-appropriated by members of the public. Our research is therefore concerned with the public appropriation of science and Open science. After extracting the contexts of citation of these content and mapping them, we propose a typology of citation functions as well as of citers (their origins and types). Our preliminary results indicated that academic literature is repurposed and cited by members of the public mainly as scientific warrant (support for their argumentation). We also found that academic content is …

Size Matters: The Impact Of Training Size In Taxonomically-Enriched Word Embeddings, Alfredo Maldonado, Filip Klubicka, John D. Kelleher

Articles

Word embeddings trained on natural corpora (e.g., newspaper collections, Wikipedia or the Web) excel in capturing thematic similarity (“topical relatedness”) on word pairs such as ‘coffee’ and ‘cup’ or ’bus’ and ‘road’. However, they are less successful on pairs showing taxonomic similarity, like ‘cup’ and ‘mug’ (near synonyms) or ‘bus’ and ‘train’ (types of public transport). Moreover, purely taxonomy-based embeddings (e.g. those trained on a random-walk of WordNet’s structure) outperform natural-corpus embeddings in taxonomic similarity but underperform them in thematic similarity. Previous work suggests that performance gains in both types of similarity can be achieved by enriching natural-corpus embeddings with …

Demographic Factors As Domains For Adaptation In Linguistic Preprocessing, Sara Morini

Dissertations, Theses, and Capstone Projects

Classic natural language processing resources such as the Penn Treebank (Marcus et al. 1993) have long been used both as evaluation data for many linguistic tasks and as training data for a variety of off-the-shelf language processing tools. Recent work has highlighted a gender imbalance in the authors of this text data (Garimella et al. 2019) and hypothesized that tools created with such resources will privilege users from particular demographic groups (Hovy and Søgaard 2015). Domain adaptation is typically employed as a strategy in machine learning to adjust models trained and evaluated with data from different genres. However, the present …

Do It Like A Syntactician: Using Binary Gramaticality Judgements To Train Sentence Encoders And Assess Their Sensitivity To Syntactic Structure, Pablo Gonzalez Martinez

Dissertations, Theses, and Capstone Projects

The binary nature of grammaticality judgments and their use to access the structure of syntax are a staple of modern linguistics. However, computational models of natural language rarely make use of grammaticality in their training or application. Furthermore, developments in modern neural NLP have produced a myriad of methods that push the baselines in many complex tasks, but those methods are typically not evaluated from a linguistic perspective. In this dissertation I use grammaticality judgements with artificially generated ungrammatical sentences to assess the performance of several neural encoders and propose them as a suitable training target to make models learn …

Synthetic, Yet Natural: Properties Of Wordnet Random Walk Corpora And The Impact Of Rare Words On Embedding Performance, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher

Conference papers

Creating word embeddings that reflect semantic relationships encoded in lexical knowledge resources is an open challenge. One approach is to use a random walk over a knowledge graph to generate a pseudo-corpus and use this corpus to train embeddings. However, the effect of the shape of the knowledge graph on the generated pseudo-corpora, and on the resulting word embeddings, has not been studied. To explore this, we use English WordNet, constrained to the taxonomic (tree-like) portion of the graph, as a case study. We investigate the properties of the generated pseudo-corpora, and their impact on the resulting embeddings. We find …

Beneath The Surface Of Talking About Physicians: A Statistical Model Of Language For Patient Experience Comments, Taylor Turpen, Lea Matthews Md, Senem Guney Phd, Cpxp

Patient Experience Journal

This study applies natural language processing (NLP) techniques to patient experience comments. Our goal was to examine the language describing care experiences with two groups of physicians: those with scores in the top 100 and those with scores in the bottom 100 among all physicians (n=498) who received scores from patient satisfaction surveys. Our analysis showed a statistically significant difference in the language used to describe care experiences with these two distinct groups of physicians. This analysis illustrates how to apply NLP techniques in categorizing and building a statistical model for language use in order to identify meaningful language and …