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Exploring Bigram Character Features For Arabic Text Clustering, Dia Eddin Abuzeina
Exploring Bigram Character Features For Arabic Text Clustering, Dia Eddin Abuzeina
Turkish Journal of Electrical Engineering and Computer Sciences
The vector space model (VSM) is an algebraic model that is widely used for data representation in text mining applications. However, the VSM poses a critical challenge, as it requires a high-dimensional feature space. Therefore, many feature selection techniques, such as employing roots or stems (i.e. words without infixes and prefixes, and/or suffixes) instead of using complete word forms, are proposed to tackle this space challenge problem. Recently, the literature shows that one more basic unit feature can be used to handle the textual features, which is the twoneighboring character form that we call microword. To evaluate this feature type, …
Segmented Character Recognition Using Curvature-Based Global Image Feature, Belaynesh Chekol, Numan Çelebi̇, Tuğrul Taşci
Segmented Character Recognition Using Curvature-Based Global Image Feature, Belaynesh Chekol, Numan Çelebi̇, Tuğrul Taşci
Turkish Journal of Electrical Engineering and Computer Sciences
Character recognition in natural scene images is a fundamental prerequisite for many text-based image analysis tasks. Generally, local image features are employed widely to recognize characters segmented from natural scene images. In this paper, a curvature-based global image feature and description for segmented character recognition is proposed. This feature is entirely dependent on the curvature information of the image pixels. The proposed feature is employed for segmented character recognition using Chars74k dataset and ICDAR 2003 character recognition dataset. From the two datasets, 1068 and 540 images of characters, respectively, are randomly chosen and 573-dimensional feature vector is synthesized per image. …
A Hybrid Of Fuzzy Theory And Quadratic Function For Estimating And Refining Transmission Map, Jyun-Yu Jhang, Chengjian Lin, Kuu-Young Young, Chin-Teng Lin
A Hybrid Of Fuzzy Theory And Quadratic Function For Estimating And Refining Transmission Map, Jyun-Yu Jhang, Chengjian Lin, Kuu-Young Young, Chin-Teng Lin
Turkish Journal of Electrical Engineering and Computer Sciences
In photographs captured in outdoor environments, particles in the air cause light attenuation and degrade image quality. This effect is especially obvious in hazy environments. In this study, a fuzzy theory is proposed to estimate the transmission map of a single image. To overcome the problem of oversaturation in dehazed images, a quadratic-function-based method is proposed to refine the transmission map. In addition, the color vector of the atmospheric light is estimated using the top 1\% of the brightest light area. Finally, the dehazed image is reconstructed using the transmission map and the estimated atmospheric light. Experimental results demonstrate that …
A Robust Smes Control For Enhancing Stability Of Distribution Systems Fed From Intermittent Wind Power Generation, Sayed Said, Mokhtar Aly, Balint Hartmann
A Robust Smes Control For Enhancing Stability Of Distribution Systems Fed From Intermittent Wind Power Generation, Sayed Said, Mokhtar Aly, Balint Hartmann
Turkish Journal of Electrical Engineering and Computer Sciences
The voltage and frequency stability issues of power systems are the main challenges that arise from high penetration levels of wind energy systems. This paper presents an effective solution for voltage and frequency stability problems by using a superconducting magnetic energy storage (SMES) system controlled with a fuzzy logic controller (FLC). The proposed control system can suppress the voltage and frequency fluctuations due to the high variations of wind speed. In addition, the proposed control system is suitable for both balanced and unbalanced distribution systems with high penetration levels of wind turbines (WTs). A squirrel cage induction generator (SCIG) is …
A New Model To Determine The Hierarchical Structure Of The Wireless Sensor Networks, Resmi̇ye Nasi̇boğlu, Zülküf Teki̇n Erten
A New Model To Determine The Hierarchical Structure Of The Wireless Sensor Networks, Resmi̇ye Nasi̇boğlu, Zülküf Teki̇n Erten
Turkish Journal of Electrical Engineering and Computer Sciences
Wireless sensor networks are one of the rising areas of scientific research. Common purpose of these investigations is usually constructing optimal structure of the network by prolonging its lifetime. In this study, a new model has been proposed to construct a hierarchical structure of wireless sensor networks. Methods used in the model to determine clusters and appropriate cluster heads are k-means clustering and fuzzy inference system (FIS), respectively. The weighted averaging based on levels (WABL) defuzzification method is used to calculate crisp outputs of the FIS. A new theorem for calculation of WABL values has been proved in order to …
A Fuzzy Model Of Directional Relationships From The Phi-Descriptor, Mohammad Naeem, Nasir Ahmad, Sahib Khan, Asma Gul
A Fuzzy Model Of Directional Relationships From The Phi-Descriptor, Mohammad Naeem, Nasir Ahmad, Sahib Khan, Asma Gul
Turkish Journal of Electrical Engineering and Computer Sciences
Directional spatial relationships are a category of spatial relationships and have applications in the fields of image processing, geographic information systems, natural language processing, and robot navigation. They can be directly extracted from images or can be interpreted from a type of image descriptors called the relative position descriptors. Examples of relative position descriptors are the angle histogram, the force histogram, and the recently proposed phi-descriptor. So far, fuzzy models of directional spatial relationships from the angle histogram and force histograms have been proposed in the literature. These include the compatibility method, the aggregation method, and the method of effective …
Data Analysis Through Social Media According To The Classified Crime, Serkan Savaş, Nuretti̇n Topaloğlu
Data Analysis Through Social Media According To The Classified Crime, Serkan Savaş, Nuretti̇n Topaloğlu
Turkish Journal of Electrical Engineering and Computer Sciences
The amount and variety of data generated through social media sites has increased along with the widespread use of social media sites. In addition, the data production rate has increased in the same way. The inclusion of personal information within these data makes it important to process the data and reach meaningful information within it. This process can be called intelligence and this meaningful information may be for commercial, academic, or security purposes. An example application is developed in this study for intelligence on Twitter. Crimes in Turkey are classified according to Turkish Statistical Institute criminal data and keywords are …
A Tree-Based Approach For English-To-Turkish Translation, Özge Bakay, Begüm Avar, Olcay Taner Yildiz
A Tree-Based Approach For English-To-Turkish Translation, Özge Bakay, Begüm Avar, Olcay Taner Yildiz
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we present our English-to-Turkish translation methodology, which adopts a tree-based approach. Our approach relies on tree analysis and the application of structural modification rules to get the target side (Turkish) trees from source side (English) ones. We also use morphological analysis to get candidate root words and apply tree-based rules to obtain the agglutinated target words. Compared to earlier work on English-to-Turkish translation using phrase-based models, we have been able to obtain higher BLEU scores in our current study. Our syntactic subtree permutation strategy, combined with a word replacement algorithm, provides a 67 % relative improvement from …
Automatic Concept Identification Of Software Requirements In Turkish, Fatma Bozyi̇ği̇t, Özlem Aktaş, Deni̇z Kilinç
Automatic Concept Identification Of Software Requirements In Turkish, Fatma Bozyi̇ği̇t, Özlem Aktaş, Deni̇z Kilinç
Turkish Journal of Electrical Engineering and Computer Sciences
Software requirements include description of the features for the target system and express the expectations of users. In the analysis phase, requirements are transformed into easy-to-understand conceptual models that facilitate communication between stakeholders. Although creating conceptual models using requirements is mostly implemented manually by analysts, the number of models that automate this process has increased recently. Most of the models and tools are developed to analyze requirements in English, and there is no study for agglutinative languages such as Turkish or Finnish. In this study, we propose an automatic concept identification model that transforms Turkish requirements into Unified Modeling Language …
Turkish Lexicon Expansion By Using Finite State Automata, Mustafa Burak Öztürk, Burcu Can Buğlalilar
Turkish Lexicon Expansion By Using Finite State Automata, Mustafa Burak Öztürk, Burcu Can Buğlalilar
Turkish Journal of Electrical Engineering and Computer Sciences
Turkish is an agglutinative language with rich morphology. A Turkish verb can have thousands of different word forms. Therefore, sparsity becomes an issue in many Turkish natural language processing (NLP) applications. This article presents a model for Turkish lexicon expansion. We aimed to expand the lexicon by using a morphological segmentation system by reversing the segmentation task into a generation task. Our model uses finite-state automata (FSA) to incorporate orthographic features and morphotactic rules. We extracted orthographic features by capturing phonological operations that are applied to words whenever a suffix is added. Each FSA state corresponds to either a stem …
Lexicon-Based Emotion Analysis In Turkish, Mansur Alp Toçoğlu, Adi̇l Alpkoçak
Lexicon-Based Emotion Analysis In Turkish, Mansur Alp Toçoğlu, Adi̇l Alpkoçak
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we proposed a lexicon for emotion analysis in Turkish for six emotional categories happiness, fear, anger, sadness, disgust, and surprise. Besides, we also investigated the effects of a lemmatizer and a stemmer, two term-weighting schemes, four lexicon enrichment methods, and a term selection approach for lexicon construction. To do this, we generated Turkish emotion lexicon based on a dataset, TREMO, containing 25,989 documents. We then preprocessed the documents to obtain dictionary and stem forms of each term using a lemmatizer and a stemmer. Afterwards, we proposed two different weighting schemes where term frequency, term-class frequency and mutual …
A Polarity Calculation Approach For Lexicon-Based Turkish Sentiment Analysis, Gökhan Yurtalan, Murat Koyuncu, Çi̇ğdem Turhan
A Polarity Calculation Approach For Lexicon-Based Turkish Sentiment Analysis, Gökhan Yurtalan, Murat Koyuncu, Çi̇ğdem Turhan
Turkish Journal of Electrical Engineering and Computer Sciences
Sentiment analysis attempts to resolve the senses or emotions that a writer or speaker intends to send across to the people about an object or event. It generally uses natural language processing and/or artificial intelligence techniques for processing electronic documents and mining the opinion specified in the content. In recent years, researchers have conducted many successful sentiment analysis studies for the English language which consider many words and word groups that set emotion polarities arising from the English grammar structure, and then use datasets to test their performance. However, there are only a limited number of studies for the Turkish …
A Hybrid Sentiment Analysis Method For Turkish, Buket Erşahi̇n, Özlem Aktaş, Deni̇z Kilinç, Mustafa Erşahi̇n
A Hybrid Sentiment Analysis Method For Turkish, Buket Erşahi̇n, Özlem Aktaş, Deni̇z Kilinç, Mustafa Erşahi̇n
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a hybrid methodology for Turkish sentiment analysis, which combines the lexicon-based and machine learning (ML)-based approaches. On the lexicon-based side, we use a sentiment dictionary that is extended with a synonyms lexicon. Besides this, we tackle the classification problem with three supervised classifiers, naive Bayes, support vector machines, and J48, on the ML side. Our hybrid methodology combines these two approaches by generating a new lexicon-based value according to our feature generation algorithm and feeds it as one of the features to machine learning classifiers. Despite the linguistic challenges caused by the morphological structure of Turkish, the …
Extending A Sentiment Lexicon With Synonym--Antonym Datasets: Swnettr++, Fati̇h Sağlam, Burkay Genç, Hayri̇ Sever
Extending A Sentiment Lexicon With Synonym--Antonym Datasets: Swnettr++, Fati̇h Sağlam, Burkay Genç, Hayri̇ Sever
Turkish Journal of Electrical Engineering and Computer Sciences
In our previous studies on developing a general-purpose Turkish sentiment lexicon, we constructed SWNetTR-PLUS, a sentiment lexicon of 37K words. In this paper, we show how to use Turkish synonym and antonym word pairs to extend SWNetTR-PLUS by almost 33 % to obtain SWNetTR++, a Turkish sentiment lexicon of 49K words. The extension was done by transferring the problem into the graph domain, where nodes are words, and edges are synonym--antonym relations between words, and propagating the existing tone and polarity scores to the newly added words using an algorithm we have developed. We tested the existing and new lexicons …
Hydrogen Production System With Fuzzy Logic-Controlled Converter, Sali̇h Nacar, Seli̇m Öncü
Hydrogen Production System With Fuzzy Logic-Controlled Converter, Sali̇h Nacar, Seli̇m Öncü
Turkish Journal of Electrical Engineering and Computer Sciences
Electrolyte current must be controlled in the water electrolysis systems. For this purpose, the power converter for the cell stack of the electrolyzer used in industrial hydrogen production is realized. A series resonant converter, which is suitable for high input voltage and low output current applications, is used as power stage of the electrolyzer. The high-frequency transformer is used for the impedance matching. While the system is running, the electrical resistance of the electrolyzer changes continuously; thus, fuzzy logic controller (FLC) is used to control the output current of the power converter. In this study, a 700-W converter prototype is …
Fast Nonsingular Terminal Decoupled Sliding-Mode Control Utilizing Time-Varying Sliding Surfaces, Ferhun Yorgancioğlu, Soydan Redif
Fast Nonsingular Terminal Decoupled Sliding-Mode Control Utilizing Time-Varying Sliding Surfaces, Ferhun Yorgancioğlu, Soydan Redif
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a fast form of nonsingular, terminal, decoupled, sliding-mode control, which utilizes time-varying sliding surfaces, is proposed for a class of fourth-order, single-input, multioutput, nonlinear systems. The novel control law features a fast term, in the manner of fast terminal sliding-mode control, which markedly improves the finite-time sliding-mode convergence speed near zero. Numerical simulation results, which are illustrated with a cart-pole inverted pendulum system and a ball-beam system, demonstrate that the proposed control law achieves, in general, favorable transient response and lower steady-state errors compared to state-of-the-art decoupled terminal sliding-mode control methods.
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 …
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 …
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 …
Citationally Enhanced Semantic Literature Based Discovery, John David Fleig
Citationally Enhanced Semantic Literature Based Discovery, John David Fleig
CCAC Theses and Dissertations
We are living within the age of information. The ever increasing flow of data and publications poses a monumental bottleneck to scientific progress as despite the amazing abilities of the human mind, it is woefully inadequate in processing such a vast quantity of multidimensional information. The small bits of flotsam and jetsam that we leverage belies the amount of useful information beneath the surface. It is imperative that automated tools exist to better search, retrieve, and summarize this content. Combinations of document indexing and search engines can quickly find you a document whose content best matches your query - if …
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
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 …
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 …
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 …