Physical Sciences and Mathematics Commons^™

Classifying Fiction And Non-Fiction Works Using Machine Learning, Rachna Gupta '21

Student Publications & Research

The objective of this project was to create a program that can determine whether an unknown text is a work of fiction or non-fiction using machine learning. Various datasets of speeches, ebooks, poems, scientific papers, and texts from Project Gutenberg and the Wolfram Example Data were utilized to train and test a Markov Chain machine learning model. A microsite was deployed with the final product that returns a probability of fictionality based on input from the user with 95% accuracy.

Automatic Inference Of Causal Reasoning Chains From Student Essays, Simon Mark Hughes

College of Computing and Digital Media Dissertations

While there has been an increasing focus on higher-level thinking skills arising from the Common Core Standards, many high-school and middle-school students struggle to combine and integrate information from multiple sources when writing essays. Writing is an important learning skill, and there is increasing evidence that writing about a topic develops a deeper understanding in the student. However, grading essays is time consuming for teachers, resulting in an increasing focus on shallower forms of assessment that are easier to automate, such as multiple-choice tests. Existing essay grading software has attempted to ease this burden but relies on shallow lexico-syntactic features …

Adapting Bert For Target-Oriented Multimodal Sentiment Classification, Jianfei Yu, Jing Jiang

Research Collection School Of Computing and Information Systems

As an important task in Sentiment Analysis, Target-oriented Sentiment Classification (TSC) aims to identify sentiment polarities over each opinion target in a sentence. However, existing approaches to this task primarily rely on the textual content, but ignoring the other increasingly popular multimodal data sources (e.g., images), which can enhance the robustness of these text-based models. Motivated by this observation and inspired by the recently proposed BERT architecture, we study Target-oriented Multimodal Sentiment Classification (TMSC) and propose a multimodal BERT architecture. To model intra-modality dynamics, we first apply BERT to obtain target-sensitive textual representations. We then borrow the idea from self-attention …

Knowledge Base Question Answering With Topic Units, Yunshi Lan, Shuohang Wang, Jing Jiang

Research Collection School Of Computing and Information Systems

Knowledge base question answering (KBQA) is an important task in natural language processing. Existing methods for KBQA usually start with entity linking, which considers mostly named entities found in a question as the starting points in the KB to search for answers to the question. However, relying only on entity linking to look for answer candidates may not be sufficient. In this paper, we propose to perform topic unit linking where topic units cover a wider range of units of a KB. We use a generation-and-scoring approach to gradually refine the set of topic units. Furthermore, we use reinforcement learning …

Cs04all: Natural Language Processing Project, Hunter R. Johnson

Open Educational Resources

In this archive there are two activities/assignments suitable for use in a CS0 or Intro course which uses Python.

In the first activity, students are asked to "fill in the code" in a series of short programs that compute a similarity metric (cosine similarity) for text documents. This involves string tokenization, and frequency counting using Python string methods and datatypes.

https://cocalc.com/share/bde99afd-76c8-493d-9608-db9019bcd346/171/Proj1?viewer=share/

In the second activity (taken directly from Think Python 2e) students use a pronunciation dictionary to solve a riddle involving homophones.

https://cocalc.com/share/bde99afd-76c8-493d-9608-db9019bcd346/171/Dicts2?viewer=share/

This OER material was produced as a result of the CS04ALL CUNY OER project

Culture Clubs: Processing Speech By Deriving And Exploiting Linguistic Subcultures, David Guy Brizan

Dissertations, Theses, and Capstone Projects

Spoken language understanding systems are error-prone for several reasons, including individual speech variability. This is manifested in many ways, among which are differences in pronunciation, lexical inventory, grammar and disfluencies. There is, however, a lot of evidence pointing to stable language usage within subgroups of a language population. We call these subgroups linguistic subcultures.

The two broad problems are defined and a survey of the work in this space is performed. The two broad problems are: linguistic subculture detection, commonly performed via Language Identification, Accent Identification or Dialect Identification approaches; and speech and language processing tasks taken which may see …

An Evaluation Of Learning Employing Natural Language Processing And Cognitive Load Assessment, Mrunal Tipari

Dissertations

One of the key goals of Pedagogy is to assess learning. Various paradigms exist and one of this is Cognitivism. It essentially sees a human learner as an information processor and the mind as a black box with limited capacity that should be understood and studied. With respect to this, an approach is to employ the construct of cognitive load to assess a learner's experience and in turn design instructions better aligned to the human mind. However, cognitive load assessment is not an easy activity, especially in a traditional classroom setting. This research proposes a novel method for evaluating learning …