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Rethinking Global-Regulation: World’S Law Meets Artificial Intelligence, Nachshon Sean Goltz, Addison Cameron-Huff, Giulia Dondoli
Rethinking Global-Regulation: World’S Law Meets Artificial Intelligence, Nachshon Sean Goltz, Addison Cameron-Huff, Giulia Dondoli
Research outputs 2014 to 2021
This article takes a critical look at Machine Translation of legal text, especially global legislation, through the discussion of Global-Regulation, a state of the art online search engine of the world’s legislation in English. Part 2 explains the rationale for an online platform such as Global-Regulation. Part 3 provides a brief account of the history of the development of machine translation, and it describes some of the limits of the use of statistical machine translation for translating legal texts. Part 4 describes Neural Machine Translation (NMT), which is a new generation of machine translation systems. Finally, Parts 5 and 6 …
Towards Misleading Connection Mining, Md Main Uddin Rony
Towards Misleading Connection Mining, Md Main Uddin Rony
Electronic Theses and Dissertations
This study introduces a new Natural Language Generation (NLG) task – Unit Claim Identification. The task aims to extract every piece of verifiable information from a headline. The Unit Claim identification has applications in other domains; such as fact-checking where the identification of each verifiable information from a check-worthy statement can lead to an effective fact-check. Moreover, the extracting of the unit claims from headlines can identify a misleading news article, by mapping evidence from contents. For addressing the unit claim identification problem, we outlined a set of guidelines for data annotation, arranged in-house training for the annotators and obtained …
Summer Research Fellowship Project Descriptions 2019, Clark Science Center's Summer Research Fellows Program
Summer Research Fellowship Project Descriptions 2019, Clark Science Center's Summer Research Fellows Program
SURF Abstracts (Women in Science)
A summary of research done by Smith College’s 2019 Summer Research Fellowship (SURF) Program participants. Ever since its 1967 start, SURF has been a cornerstone of Smith’s science education. Supervised by faculty mentor-advisors drawn from the Clark Science Center and connected to its eighteen science, mathematics, and engineering departments and programs and associated centers and units. At summer’s end, SURF participants were asked to summarize their research experiences for this publication.
Successful Strategies For Retaining Profitability In An Education-Sector It Project, Cassandra Romae Middleton
Successful Strategies For Retaining Profitability In An Education-Sector It Project, Cassandra Romae Middleton
Walden Dissertations and Doctoral Studies
Many information technology (IT) project managers (PMs) and other business leaders lack effective strategies for enhancing communication among their project team members, thereby reducing profitability and organizational cohesion. The purpose of this multiple case study was to explore communication strategies that IT PMs used to successfully complete IT mobile device projects. The conceptual framework for this study was McQuail's mass communication, Craig's communication, and Deming's profound knowledge theory. Purposive sampling method was used to identify 6 successful IT PMs and leaders who worked at 2 leading educations settings located in southeastern South Carolina. Data gathered from the semistructured interviews and …
Potential Solar Consumers' Understanding Of Energy Policy Development In HawaiâI, Kristin Li Mcgill
Potential Solar Consumers' Understanding Of Energy Policy Development In HawaiâI, Kristin Li Mcgill
Walden Dissertations and Doctoral Studies
Hawaiâi has implemented renewable energy goals that assume continued investments by solar consumers who seem unaware of their role in the policy's success. Without the renewable resource generation that will come from these investments, the state will be unable to achieve its energy mandate. Using Sabatier and Jenkins-Smith's advocacy coalition framework and Ajzen's theory of planned behavior as the foundation, the purpose of this study was to better understand the perspectives of potential solar consumers on the Island of Oâahu regarding the state's renewable portfolio standards, their level of knowledge regarding consumer impact on this policy, and their perceptions of …
Teachers' Perceptions About Instructing Underachieving K-5 Students On Mathematical Word Problem-Solving, Crystal Yvette Baldwindouglas
Teachers' Perceptions About Instructing Underachieving K-5 Students On Mathematical Word Problem-Solving, Crystal Yvette Baldwindouglas
Walden Dissertations and Doctoral Studies
The state of Maryland has implemented the Common Core State Standards for Mathematics (CCSSM) operations & algebraic thinking and number & operations-fractions with emphasis on students in Grades K-5 acquiring the ability to solve word problems for state and curriculum math assessments. However, since the implementation of CCSSM, 30% of elementary students in a Maryland school district have demonstrated underachievement (basic or below basic level) on problem-solving sections of the state and school standardized tests. This qualitative case study, guided by Polya's model of the four phases of mathematical problem-solving, was conducted to address this problem. The research questions addressed …
Collaboration Pattern Model For Student Participation In Problem-Solving Typed Chat, Duy Quang Bui
Collaboration Pattern Model For Student Participation In Problem-Solving Typed Chat, Duy Quang Bui
Theses
This project measures different collaborative dialogue acts between students who are working together to solve problems in a computer programming class. In COMPS (Computer-Mediated Problem Solving) exercises students work together via online typed-chat. Transcripts of these conversations were annotated with four categories of collaborative utterance: sharing ideas, negotiating ideas, regulating problem-solving, and maintaining communication. The annotated transcripts were then applied to answer four different research questions. A) Among the several students in a conversation, there are measurable quantitative differences in dialogue behavior that correlate with the relative preparedness for solving the problem. The most prepared student not only talks more …
The New Legal Landscape For Text Mining And Machine Learning, Matthew Sag
The New Legal Landscape For Text Mining And Machine Learning, Matthew Sag
Faculty Articles
Now that the dust has settled on the Authors Guild cases, this Article takes stock of the legal context for TDM research in the United States. This reappraisal begins in Part I with an assessment of exactly what the Authors Guild cases did and did not establish with respect to the fair use status of text mining. Those cases held unambiguously that reproducing copyrighted works as one step in the process of knowledge discovery through text data mining was transformative, and thus ultimately a fair use of those works. Part I explains why those rulings followed inexorably from copyright's most …
วิธีการสำหรับการสร้างหุ่นยนต์สนทนาไทยโดยใช้หน่วยความจำระยะสั้นแบบยาวแบบสยามและการแต่งเติมข้อมูลเชิงข้อความ, ธนัญญา พีรพัฒนาการ
วิธีการสำหรับการสร้างหุ่นยนต์สนทนาไทยโดยใช้หน่วยความจำระยะสั้นแบบยาวแบบสยามและการแต่งเติมข้อมูลเชิงข้อความ, ธนัญญา พีรพัฒนาการ
Chulalongkorn University Theses and Dissertations (Chula ETD)
แนวคิดการนำหุ่นยนต์สนทนามาช่วยในการตอบคำถามปัญหาที่พบบ่อยให้กับผู้รับบริการ เช่น การสอบถามข้อมูลทั่วไปเกี่ยวกับผู้ให้บริการ เป็นต้น เริ่มเป็นที่นิยมมากขึ้นในยุคปัจจุบัน อีกทั้งในการเรียนรู้ของเครื่องสำหรับสร้างหุ่นยนต์สนทนานั้น ชุดข้อมูลที่ใช้สำหรับการเรียนรู้ของแบบจำลอง ถือเป็นอีกหนึ่งสิ่งสำคัญที่จะช่วยให้แบบจำลองให้สามารถทำงานได้อย่างมีประสิทธิภาพ ในงานวิจัยนี้ได้รับการสนับสนุนข้อมูลจากการไฟฟ้านครหลวงแห่งประเทศไทยที่ได้รวบรวมข้อมูลการให้บริการการตอบปัญหาลูกค้าผ่านช่องทางสื่อสังคมออนไลน์ โดยจำนวนของชุดคำถามที่ได้นั้นมีปริมาณน้อยกว่า 1,500 คำถาม ทำให้จำนวนและความหลากหลายของข้อมูลที่มีนั้นส่งผลกับการเรียนรู้ของเครื่องโดยตรง งานวิจัยนี้จึงนำเสนอแนวคิดในการแต่งเติมข้อมูลด้วยวิธีการแทนที่คำด้วยคำที่มีความหมายคล้ายกันด้วยการวัดระยะห่างระหว่างเวกเตอร์น้อยที่สุดเมื่อเทียบกับคำที่ต้องการจะนำไปแทนที่ในประโยคเดิม เพื่อเพิ่มจำนวนและความหลากหลายของข้อมูล จากนั้นจึงนำชุดข้อมูลที่ได้ไปประยุกต์ใช้กับแบบจำลองหน่วยความจำระยะสั้นแบบยาว (Long Short-Term Memory: LSTM) ที่ใช้ร่วมกับการหาระยะทางร่วมกับการทดลองหาระยะทางของเวกเตอร์ทั้ง 3 แบบ ได้แก่ การหาระยะทางแบบยุคลิด (Euclidean Distance) การหาระยะทางแบบแมนฮัตตัน (Manhattan Distance) และ การหาค่าความคล้ายโคไซน์ (Cosine Similarity) เพื่อนำไปใช้ในการค้นคืนคำตอบของคำถามที่ได้รับมาจากผู้ใช้งาน ซึ่งผลการทดลองแสดงให้เห็นว่าชุดข้อมูลที่ปรับปรุงด้วยวิธีการแต่งเติมข้อมูลเชิงข้อความที่นำเสนอนั้นสามารถเพิ่มประสิทธิภาพของแบบจำลองได้ดีกว่าชุดข้อมูลตั้งต้น
หุ่นยนต์สนทนาที่มุ่งงานโดยใช้หน่วยความจำระยะสั้นแบบยาวกับกลไกจุดสนใจสำหรับภาษาไทย, รมณ รอบโลก
หุ่นยนต์สนทนาที่มุ่งงานโดยใช้หน่วยความจำระยะสั้นแบบยาวกับกลไกจุดสนใจสำหรับภาษาไทย, รมณ รอบโลก
Chulalongkorn University Theses and Dissertations (Chula ETD)
หุ่นยนต์สนทนาที่มุ่งงานสามารถช่วยบรรลุเป้าหมายที่เฉพาะเจาะจงให้กับผู้ใช้งานได้ เช่น การจองร้านอาหาร เป็นต้น การเรียนรู้ของเครื่องด้วยวิธีกำหนดกฎสำหรับสถานการณ์ต่าง ๆ ทำให้บทสนทนาระหว่างผู้ใช้งานกับหุ่นยนต์ขาดความยืดหยุ่นและมีต้นทุนสูงเมื่อต้องการปรับเปลี่ยนกฎ ที่ผ่านมาหุ่นยนต์สนทนาที่ใช้เทคนิคกำหนดกฎนั้น ไม่สามารถติดตามความต้องการหรือความตั้งใจที่แท้จริงของผู้ใช้งานได้ จึงเริ่มใช้วิธีการทางปัญญาประดิษฐ์ซึ่งทำให้สามารถติดตามความต้องการหรือความตั้งใจที่แท้จริงของผู้ใช้งานได้ นอกจากนี้วิธีการนี้ยังช่วยให้ผู้ใช้งานสามารถสนทนากับหุ่นยนต์ได้ยืดหยุ่นมากขึ้น ซึ่งหุ่นยนต์สนทนาที่ถูกพัฒนาด้วยวิธีนี้ส่วนมากจะใช้คำฝังตัวเป็นตัวแทนข้อความซึ่งถูกพัฒนาโดย Mikolov และคณะ [10] นอกจากนี้มีหลายงานวิจัยที่พยายามสร้างหุ่นยนต์สนทนาที่มุ่งเน้นงานแบบครบวงจรซึ่งสามารถเพิ่มประสิทธิภาพให้กับหุ่นยนต์ได้ ตัวอย่างสถาปัตยกรรมแบบครบวงจร ได้แก่ แบบจำลอง Hybrid Code Networks (HCNs) [8] ซึ่งใช้หน่วยความจำระยะสั้นแบบยาว [23] โดยใช้ชุดข้อมูลบทสนทนาการจองร้านอาหารเพื่อวัดประสิทธิภาพของแบบจำลองในการติดตามสถานะบทสนทนาสนทนาและทำนายการตอบโต้ของหุ่นยนต์ ในวิทยานิพนธ์ฉบับนี้ได้เสนอแบบจำลองที่ใช้หน่วยความจำระยะสั้นแบบยาวโดยเพิ่มกลไกจุดสนใจสำหรับการจองร้านอาหาร อย่างไรก็ตามเพื่อให้บทสนทนาจองร้านอาหารมีความซับซ้อนและสมจริงมากขึ้น จึงได้สร้างชุดข้อมูลการจองร้านอาหารที่สอดคล้องกับวัฒนธรรมไทยเพื่อทดลองว่าแบบจำลองจะทำงานอย่างไรในสภาพแวดล้อมที่สมจริงยิ่งขึ้น ซึ่งผลการทดลองแสดงให้เห็นว่าแบบจำลองที่นำเสนอนั้นมีประสิทธิภาพในการบรรลุเป้าหมายที่ต้องการ
Classification As Catachresis: Double Binds Of Representing Difference With Semiotic Infrastructure, Lindsay Poirier
Classification As Catachresis: Double Binds Of Representing Difference With Semiotic Infrastructure, Lindsay Poirier
Statistical and Data Sciences: Faculty Publications
Background; This article explores the results of a three-year ethnographic study of how semiotic infrastructures-or digital standards and frameworks such as taxonomies, schemas, and ontologies that encode the meaning of data-are designed. Analysis: It examines debates over best practices in semiotic infrastructure design, such as how much complexity adopted languages should characterize versus how restrictive they should be. It also discusses political and pragmatic considerations that impact what and how information is represented in an information system. Conclusion and implications: This article suggests that all databased representations are forms of data power, and that examining semiotic infrastructure design provides insight …
Building An Automated Q-A System Using Online Forums As Knowledge Bases, Kyle Moore
Building An Automated Q-A System Using Online Forums As Knowledge Bases, Kyle Moore
Electronic Theses and Dissertations
Question-Answer systems traditionally use expensive and difficult to produce structured knowledge bases. Recent systems have used unstructured natural language sources as their datasets, but most of those sources have been overly broad or difficult to extend. Online forums are a largely untapped source of information that can provide both depth and breadth when limited to a specific domain, as well as being adaptive to the introduction of new information. In this paper, I conjecture that online forums can be similarly and effectively used as an unstructured knowledge base for Question-Answer systems. I use a relatively simple summarization-based approach to analyze …
A Tacticians Guide To Conflict, Vol. 1: Advancing Explanations & Predictions Of Intrastate Conflict, Khaled Eid
A Tacticians Guide To Conflict, Vol. 1: Advancing Explanations & Predictions Of Intrastate Conflict, Khaled Eid
CGU Theses & Dissertations
Intrastate conflict is an ever-evolving problem – causes, explanation, and predictions are increasingly murky as traditional methods of analysis focus on structural issues as precursors of conflict. Often times these theories do not consider the underlying meso and micro dynamics that can provide vital insights into the phenomena. Tactical decision-makers are left using models that rely on highly aggregated, country level data to create proper courses of actions (COAs) to address or predict conflict. The shortcoming is that conflicts morph quite rapidly and structural variables can struggle capture such dynamic changes. To address this some tacticians are using big data …
Nidus Idearum. Scilogs, V: Joining The Dots, Florentin Smarandache
Nidus Idearum. Scilogs, V: Joining The Dots, Florentin Smarandache
Branch Mathematics and Statistics Faculty and Staff Publications
My lab[oratory] is a virtual facility with noncontrolled conditions in which I mostly perform scientific meditation and chats: a nest of ideas (nidus idearum, in Latin). I called the jottings herein scilogs (truncations of the words scientific, and gr. Λόγος – appealing rather to its original meanings "ground", "opinion", "expectation"), combining the welly of both science and informal (via internet) talks (in English, French, and Romanian). * In this fifth book of scilogs collected from my nest of ideas, one may find new and old questions and solutions, mostly referring to topics on NEUTROSOPHY – email messages to research colleagues, …
Reinforcement Learning For Optimal Control Of Network Epidemic Processes, Alec H. Kerrigan
Reinforcement Learning For Optimal Control Of Network Epidemic Processes, Alec H. Kerrigan
Honors Undergraduate Theses
Our society is increasingly interconnected, making it easy for cascades/epidemic (diseases, disinformation etc). Current epidemic control efforts are based on approximate network epidemic models, which often ignore the unique complexity and rich information embedded in the complex interconnections of real-world networks/populations.Deep reinforcement learning (RL) is a powerful tool at learning policies for these nonlinear, complex processes in high-dimension. To control an epidemic outbreak on a Susceptible-Infected-Susceptible network epidemic model, we design a RL framework with a custom reward structure using the node2vec embedding technique. Results indicate deep RL is able to determine and converge on an optimal intervention policy in …
Undergraduate Mathematics Students’ Connections Between Their Group Homomorphism And Linear Transformation Concept Images, Jeffrey Slye
Undergraduate Mathematics Students’ Connections Between Their Group Homomorphism And Linear Transformation Concept Images, Jeffrey Slye
Theses and Dissertations--Mathematics
It is well documented that undergraduate students struggle with the more formal and abstract concepts of vector space theory in a first course on linear algebra. Some of these students continue on to classes in abstract algebra, where they learn about algebraic structures such as groups. It is clear to the seasoned mathematician that vector spaces are in fact groups, and so linear transformations are group homomorphisms with extra restrictions. This study explores the question of whether or not students see this connection as well. In addition, I probe the ways in which students’ stated understandings are the same or …
Automated Essay Evaluation Using Natural Language Processing And Machine Learning, Harshanthi Ghanta
Automated Essay Evaluation Using Natural Language Processing And Machine Learning, Harshanthi Ghanta
Theses and Dissertations
The goal of automated essay evaluation is to assign grades to essays and provide feedback using computers. Automated evaluation is increasingly being used in classrooms and online exams. The aim of this project is to develop machine learning models for performing automated essay scoring and evaluate their performance. In this research, a publicly available essay data set was used to train and test the efficacy of the adopted techniques. Natural language processing techniques were used to extract features from essays in the dataset. Three different existing machine learning algorithms were used on the chosen dataset. The data was divided into …
Curtus: An Nlp Tool To Map Job Skills To Academic Courses, Daniel Rockwell
Curtus: An Nlp Tool To Map Job Skills To Academic Courses, Daniel Rockwell
Theses and Dissertations
Many businesses are burdened with the need to train students for the job instead of finding them prepared for it. Few business leaders feel that colleges prepare students for future jobs from day one. It can be a challenge for colleges to determine if their curricula meet the industry needs. Mapping industry needs to academic courses can be advantageous to both parties as it will allow colleges to be aligned with the industry needs and accordingly satisfy those needs and will allow the industry to hire better prepared graduates. In an attempt to address this, a system prototype that uses …
Contextual Word Embeddings - Trained On English Wikipedia Corpora, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher
Contextual Word Embeddings - Trained On English Wikipedia Corpora, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher
Datasets
This archive contains a collection of computational models called word embeddings. These are vectors that contain numerical representations of words. These have been trained on real language sentences collected from the English Wikipedia. As such, they contain contextual (thematic) knowledge about words (rather than taxonomic).
Taxonomic Word Embeddings - Trained On English Wordnet Random Walk Pseudo-Corpora, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher
Taxonomic Word Embeddings - Trained On English Wordnet Random Walk Pseudo-Corpora, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher
Datasets
This archive contains a collection of computational models called word embeddings. These are vectors that contain numerical representations of words. They have been trained on pseudo-sentences generated artificially from a random walk over the English WordNet taxonomy, and thus reflect taxonomic knowledge about words (rather than contextual).
Improving Word Embeddings Projection For Turkish Hypernym Extraction, Savaş Yildirim
Improving Word Embeddings Projection For Turkish Hypernym Extraction, Savaş Yildirim
Turkish Journal of Electrical Engineering and Computer Sciences
Corpus-driven approaches can automatically explore is-a relations between the word pairs from corpus. This problem is also called hypernym extraction. Formerly, lexico-syntactic patterns have been used to solve hypernym relations. The language-specific syntactic rules have been manually crafted to build the patterns. On the other hand, recent studies have applied distributional approaches to word semantics. They extracted the semantic relations relying on the idea that similar words share similar contexts. Former distributional approaches have applied one-hot bag-of-word (BOW) encoding. The dimensionality problem of BOW has been solved by various neural network approaches, which represent words in very short and dense …
Selective Word Encoding For Effective Text Representation, Savaş Özkan, Akin Özkan
Selective Word Encoding For Effective Text Representation, Savaş Özkan, Akin Özkan
Turkish Journal of Electrical Engineering and Computer Sciences
Determining the category of a text document from its semantic content is highly motivated in the literature and it has been extensively studied in various applications. Also, the compact representation of the text is a fundamental step in achieving precise results for the applications and the studies are generously concentrated to improve its performance. In particular, the studies which exploit the aggregation of word-level representations are the mainstream techniques used in the problem. In this paper, we tackle text representation to achieve high performance in different text classification tasks. Throughout the paper, three critical contributions are presented. First, to encode …
Application Of Boolean Logic To Natural Language Complexity In Political Discourse, Austin Taing
Application Of Boolean Logic To Natural Language Complexity In Political Discourse, Austin Taing
Theses and Dissertations--Computer Science
Press releases serve as a major influence on public opinion of a politician, since they are a primary means of communicating with the public and directing discussion. Thus, the public’s ability to digest them is an important factor for politicians to consider. This study employs several well-studied measures of linguistic complexity and proposes a new one to examine whether politicians change their language to become more or less difficult to parse in different situations. This study uses 27,500 press releases from the US Senate between 2004–2008 and examines election cycles and natural disasters, namely hurricanes, as situations where politicians’ language …
Word Sense Disambiguation Using Semantic Kernels With Class-Based Term Values, Ayşe Berna Altinel, Murat Can Gani̇z, Bi̇lge Şi̇pal, Eren Can Erkaya, Onur Can Yücedağ, Muhammed Ali̇ Doğan
Word Sense Disambiguation Using Semantic Kernels With Class-Based Term Values, Ayşe Berna Altinel, Murat Can Gani̇z, Bi̇lge Şi̇pal, Eren Can Erkaya, Onur Can Yücedağ, Muhammed Ali̇ Doğan
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, we propose several semantic kernels for word sense disambiguation (WSD). Our approaches adapt the intuition that class-based term values help in resolving ambiguity of polysemous words in WSD. We evaluate our proposed approaches with experiments, utilizing various sizes of training sets of disambiguated corpora (SensEval). With these experiments we try to answer the following questions: 1.) Do our semantic kernel formulations yield higher classification performance than traditional linear kernel?, 2.) Under which conditions a kernel design performs better than others?, 3.) Does the addition of class labels into standard term-document matrix improve the classification accuracy?, 4.) Is …
Artificial Intelligence And Role-Reversible Judgment, Kiel Brennan-Marquez, Stephen E. Henderson
Artificial Intelligence And Role-Reversible Judgment, Kiel Brennan-Marquez, Stephen E. Henderson
Faculty Articles
As intelligent machines begin more generally outperforming human experts, why should humans remain ‘in the loop’ of decision-making? One common answer focuses on outcomes: relying on intuition and experience, humans are capable of identifying interpretive errors—sometimes disastrous errors—that elude machines. Though plausible today, this argument will wear thin as technology evolves. Here, we seek out sturdier ground: a defense of human judgment that focuses on the normative integrity of decision-making. Specifically, we propose an account of democratic equality as ‘role-reversibility.’ In a democracy, those tasked with making decisions should be susceptible, reciprocally, to the impact of decisions; there ought to …
Speech Interfaces And Pilot Performance: A Meta-Analysis, Kenneth A. Ward
Speech Interfaces And Pilot Performance: A Meta-Analysis, Kenneth A. Ward
International Journal of Aviation, Aeronautics, and Aerospace
As the aviation industry modernizes, new technology and interfaces must support growing aircraft complexity without increasing pilot workload. Natural language processing presents just such a simple and intuitive interface, yet the performance implications for use by pilots remain unknown. A meta-analysis was conducted to understand performance effects of using speech and voice interfaces in a series of pilot task analogs. The inclusion criteria selected studies that involved participants performing a demanding primary task, such as driving, while interacting with a vehicle system to enter numbers, dial radios, or enter a navigation destination. Compared to manual system interfaces, voice interfaces reduced …
A Hybrid Framework For Sentiment Analysis Using Genetic Algorithm Based Feature Reduction, Farkhund Iqbal, Jahanzeb Maqbool Hashmi, Benjamin C.M. Fung, Rabia Batool, Asad Masood Khattak, Saiqa Aleem, Patrick C.K. Hung
A Hybrid Framework For Sentiment Analysis Using Genetic Algorithm Based Feature Reduction, Farkhund Iqbal, Jahanzeb Maqbool Hashmi, Benjamin C.M. Fung, Rabia Batool, Asad Masood Khattak, Saiqa Aleem, Patrick C.K. Hung
All Works
© 2019 IEEE. Due to the rapid development of Internet technologies and social media, sentiment analysis has become an important opinion mining technique. Recent research work has described the effectiveness of different sentiment classification techniques ranging from simple rule-based and lexicon-based approaches to more complex machine learning algorithms. While lexicon-based approaches have suffered from the lack of dictionaries and labeled data, machine learning approaches have fallen short in terms of accuracy. This paper proposes an integrated framework which bridges the gap between lexicon-based and machine learning approaches to achieve better accuracy and scalability. To solve the scalability issue that arises …
Learning From The 'Alien' Language: Unraveling Linguistic Relativity In The Film Arrival, Jayla Johnson
Learning From The 'Alien' Language: Unraveling Linguistic Relativity In The Film Arrival, Jayla Johnson
The Synapse: Intercollegiate science magazine
No abstract provided.
Is There A Correlation Between Wikidata Revisions And Trending Hashtags On Twitter?, Paula Dooley
Is There A Correlation Between Wikidata Revisions And Trending Hashtags On Twitter?, Paula Dooley
Dissertations
Twitter is a microblogging application used by its members to interact and stay socially connected by sharing instant messages called tweets that are up to 280 characters long. Within these tweets, users can add hashtags to relate the message to a topic that is shared among users. Wikidata is a central knowledge base of information relying on its members and machines bots to keeping its content up to date. The data is stored in a highly structured format with the added SPARQL protocol and RDF Query Language (SPARQL) endpoint to allow users to query its knowledge base.