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Chatbots applications in education: A systematic review

Computers and Education: Artificial Intelligence 2021年 2卷

作者： Okonkwo, Chinedu Wilfred Ade-Ibijola, Abejide Formal Structures Algorithms and Industrial Applications Research Cluster Department of Applied Information Systems School of Consumer Intelligence and Information Systems University of Johannesburg Bunting Road Campus Johannesburg South Africa

The introduction of Artificial Intelligence technology enables the integration of Chatbot systems into various aspects of education. This technology is increasingly being used for educational purposes. Chatbot technology has the potential to provide quick and personalised services to everyone in the sector, including institutional employees and students. This paper presents a systematic review of previous studies on the use of Chatbots in education. A systematic review approach was used to analyse 53 articles from recognised digital databases. The review results provide a comprehensive understanding of prior research related to the use of Chatbots in education, including information on existing studies, benefits, and challenges, as well as future research areas on the implementation of Chatbot technology in the field of education. The implications of the findings were discussed, and suggestions were made. © 2021 The Authors

关键词： Artificial intelligence

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An Optimal WordNet Based Emotional Word Extraction and Hybrid Deep Learning Classifier for Sentiment Analysis

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SSRN 2022年

作者： Obare, Stephen Ade-Ibijola, Abejide Okeyo, George Ogada, Kennedy School of Computing & Information Technology Jomo Kenyatta University of Agriculture and Technology Nairobi Kenya Formal Structures Algorithms and Industrial Applications Research Cluster School of Consumer Intelligence and Information Systems University of Johannesburg South Africa Carnegie Mellon University Africa Rwanda

Every day, over one billion social media text messages are generated worldwide, which is a rich source of data that can lead to improvements in the lives of citizens through evidence-based decision making. Twitter is rich in such data but there are a number of challenges in processing tweets with respect to volume, speed, ambiguity of the language in which tweets are written, which is an information extraction problem, in the domain of Natural Language Processing (NLP). While there is a growing interest in sentiment analysis for detecting emotions from tweets, there are no major efforts for detecting emotions that are disguised in tweets based on context of word usage, which is important for tasks such as identification of events such as hate speech, mental health related disorders. This paper presents a novel approach to context-based hate speech detection based on an optimal WordNet. Taking a modified Mayfly Optimization algorithm (MMO), we pre-process tweets and normalize the data using an NLP pipeline. We argument an improved Horse Herd Optimization algorithm (HHO) with WordNet and SentiWordNet to compute a tweet sentiment polarity. A hybrid Deep Belief Artificial Neural Network (hybrid DB-ANN) is then used to classify tweets. The performance of the proposed approach is compared to best known sentiment analysis algorithms using three standard benchmark datasets: Crowdflower-1, Crowdflower-2, and Kaggle Twitter. We demonstrate that the proposed approach outperforms industry benchmarks as it achieves over 90% in terms of accuracy, precision, recall, and F-measure. © 2022, The Authors. All rights reserved.

关键词： Sentiment analysis

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TalkSQL: A Tool for the Synthesis of SQL Queries from Verbal Specifications 2

TalkSQL: A Tool for the Synthesis of SQL Queries from Verbal...

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2nd International Multidisciplinary Information Technology and Engineering Conference, IMITEC 2020

作者： Obaido, George Ade-Ibijola, Abejide Vadapalli, Hima School of Computer Science and Applied Mathematics University of the Witwatersrand Johannesburg South Africa Formal Structures Algorithms and Industrial Applications Research Cluster School of Consumer Intelligence and Information Systems University of Johannesburg Johannesburg South Africa

ISBN: (纸本)9781728195209

Recent advances in the field of Natural Language Processing (NLP) have led to many robust user interfaces (UIs) designed as intelligent tutoring systems (ITS) that help students learn, query and access data in relational databases. Such tools are generally referred to as Natural Language Interfaces to Databases (NLIDBs). Many of these UIs rely on voice or typewritten for further processing. research has shown that typewritten remains the preferred input method used by database UIs designers for querying relational databases due to its flexibility. Still, there is a dearth of tools that require voice-based inputs for querying relational databases. Despite the scarcity of these tools, many of them fail to provide a comprehensive feedback to a user. In this paper, we introduce a voice-based query system named TalkSQL that takes voice inputs from a user, converts these words into SQL queries and returns a feedback to the user. Automatic feedback generation is of immense importance. To achieve this, we have used regular expressions, a representation of regular languages for the recognition of the Create, Read, Update, Delete (CRUD) operations in SQL and automatically generate a feedback using pre-defined templates. A survey on 53 participants showed that 91.2% agreed that they were able to understand the CRUD command using TalkSQL. The expected contributions are in two-fold: this work may assist a special (e.g. visually impaired) learner to understand SQL queries, and show that a voice-based interface can assist users in understanding SQL queries. © 2020 IEEE.

关键词： Specifications

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Synthesis of regular expression problems and solutions

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International Journal of Computers and applications 2020年第8期42卷 748-764页

作者： Ade-Ibijola, Abejide Formal Structures Algorithms and Industrial Applications Research Cluster School of Consumer Intelligence and Information Systems University of Johannesburg Johannesburg South Africa

formal languages and automata (FLA) theory is perceived by many as one of the hardest topics to teach or learn at the undergraduate level, due to the abstract nature of its contents;often containing proofs, lots of symbolic notations, and specifications of abstract computing machines that are difficult for many students to relate with. One way of approaching this problem is to administer numerous practice problems to students to aid learning. In this paper, we present: definitions of formal rules (using context-free grammar notations) for the synthesis of practice problems and solutions in a sub-domain of formal language theory–regular expressions, new algorithms for implementing these rules with iterations of generated problem instances and associated solutions. Generated problems are then embedded in predefined, short text response and multiple-choice question templates. The implementation of this technique produced numerous problems and solutions that can be used as practice, test or examination questions to support the teaching of regular expressions as a topic in FLA at the undergraduate level. © 2018 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Context free grammars

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Trend Analysis: A Decision Tool in SA Healthcare

Trend Analysis: A Decision Tool in SA Healthcare

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2019 International Multidisciplinary Information Technology and Engineering Conference, IMITEC 2019

作者： Abbott, Simon G Ade-Ibijola, Abejide Formal Structures Algorithms and Industrial Applications Research Cluster School of Consumer Intelligence and Information Systems University of Johannesburg Department of Applied Information Systems South Africa

ISBN: (纸本)9781728100401

The use of medical surveillance and predictive analysis is now more readily available through the intelligent use of modern technology with the use of software tools. Google Trends (GT) is an internet research tool initially utilised for the surveillance of the occurrence of influenza (Flu) internet search trends. Within the last 20 years the internet has become integral to health surveillance by reducing the time to the actual recognition of a disease outbreak, or the detection of a disease trend. GT primarily focused on detecting an outbreak of various strains of the Flu infecting different regions, sporadically or endemically, by monitoring the internet user seeking such medical information. It is currently utilised as an adjunct to the traditional surveillance tools used in traditional modern medicine. In this paper we have attempted to apply such search criteria using GT within a typical healthcare scenario or disease trend. We focused on the most common diseases found within the South African healthcare environment and presented the results accordingly. The results were found to be aligned to the results of traditional medical surveillance tools. The GT results presented in this paper may have similar applications in other areas of medicine and disease monitoring efforts in South Africa whereby the general population can derive meaningful insights of such disease trends. In addition there is a distinct awareness of this research tool, where many users are utilising the tool for healthcare searches which is becoming more evident in the medical literature. © 2019 IEEE.

关键词： Search engines

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A Metric for Estimating the Difficulty of Programming Problems by Ranking the Constructs in their Solutions

A Metric for Estimating the Difficulty of Programming Proble...

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2019 International Multidisciplinary Information Technology and Engineering Conference, IMITEC 2019

作者： Kalemba, Elsa Ade-Ibijola, Abejide Formal Structures Algorithms and Industrial Applications Research Cluster School of Consumer Intelligence and Information Systems University of Johannesburg Department of Applied Information Systems Johannesburg South Africa

ISBN: (纸本)9781728100401

Several studies have been conducted on the complexity of computer programs. Metrics of quantifying computer programs based on programming language, lines of code, or number of modules have been studied. One open problem is: how to measure the complexity of computer programming problems, based on the constructs in their solutions. In this paper, we present a tool called NOPCE (The NOvice Program Complexity Estimator) that measures the complexity of programming problems based on the constructs they contain. NOPCE takes any given novice program written in C# and computes an aggregated weight based on a look-up table of predefined weights for programming constructs. We have presented an evaluation that compares the human perception of problem complexity with that of NOPCE. Results show that, humans agreed with NOPCE on problem ranking, most of the time. This tool may find applications in computer education, where difficulty balancing of programming problems is paramount. © 2019 IEEE.

关键词： Table lookup

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Lecturer's Apprentice: A Chatbot for Assisting Novice Programmers

Lecturer's Apprentice: A Chatbot for Assisting Novice Progra...

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2019 International Multidisciplinary Information Technology and Engineering Conference, IMITEC 2019

作者： Ismail, Mohammed Ade-Ibijola, Abejide Formal Structures Algorithms and Industrial Applications Research Cluster School of Consumer Intelligence and Information Systems University of Johannesburg Department of Applied Information Systems Johannesburg South Africa

ISBN: (纸本)9781728100401

Students often struggle to communicate with their peers or lecturers about some of the issues they face during their time at university, either it be academic or personal. One of these issues is introductory programming, in instances were they choose to memorise code in order to pass rather than understanding how the logic behind the code actually works. Programming requires an understanding of how a certain logical flows and algorithm work. In this article, we discuss the difficulties that students face in introductory programming. We have also developed an interactive AI chatbot tool that students can interact with on some of the academic issues they may face. They can ask for advice on how to understand algorithms and what measures to take in order to understand programming logic and visualise metal models of the algorithms. The chatbot can also be used for personal advice. A survey that was conducted showed that there is a need for such a tool in aiding students through their university life. © 2019 IEEE.

关键词： Students

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TalkSQL: A Tool for the Synthesis of SQL Queries from Verbal Specifications

TalkSQL: A Tool for the Synthesis of SQL Queries from Verbal...

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International Multidisciplinary Information Technology and Engineering Conference (IMITEC)

作者： George Obaido Abejide Ade-Ibijola Hima Vadapalli School of Computer Science and Applied Mathematics University of the Witwatersrand Johannesburg South Africa Formal Structures Algorithms and Industrial Applications Research Cluster School of Consumer Intelligence and Information Systems University of Johannesburg Johannesburg South Africa

The following topics are dealt with: learning (artificial intelligence); computer aided instruction; educational institutions; Internet; Internet of Things; educational courses; regression analysis; support vector mac... 详细信息

ISBN: (数字)9781728195209

ISBN: (纸本)9781728195216

关键词： Structured Query Language Relational databases Tools User interfaces Natural language processing Information technology

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Syntactic Generation of Memorable Passwords

Syntactic Generation of Memorable Passwords

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2019 International Multidisciplinary Information Technology and Engineering Conference, IMITEC 2019

作者： Ade-Ibijola, Abejide Ogbuokiri, Blessing Formal Structures Algorithms and Industrial Applications Research Cluster School of Consumer Intelligence and Information Systems University of Johannesburg Johannesburg South Africa School of Computer Science and Applied Mathematics University of the Witwatersrand Johannesburg South Africa

ISBN: (纸本)9781728100401

Most tools for generating alphanumeric passwords often combine string tokens without considering semantics, as semantics contribute to the remembrance of a password string. We propose a formal method for the generation of passwords with semantic annotations using context-free grammars. A context-free grammar is a system with which one can make an infinite set of strings or objects. Users are allowed to specify their interests (such as music, movie, etc.) and phrases from these interests are used, in combination with at most three digits and one special character, to generate memorable passwords. This idea is implemented in a software tool called PassGen. PassGen takes, as input user interests, and generate n passwords for the user to choose from. 20,000 samples of generated passwords can be found at https://***/SyntacticPassword2018. A Survey of twenty seven responses shows that eighteen respondents agree that a tool that generates memorable secure passwords suggestion for users to pick from will be useful, while fourteen respondents agree that some passwords we generated using context-free grammars are memorable. © 2019 IEEE.

关键词： Context free grammars

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algorithms and a Tool for Automatic Decryption of Clinical Notes

Algorithms and a Tool for Automatic Decryption of Clinical N...

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International Conference on Soft Computing and Machine Intelligence (ISCMI)

作者： Simon G Abbott Abejide Ade-Ibijola Formal Structures Algorithms and Industrial Applications Research Cluster School of Consumer Intelligence and Information Systems University of Johannesburg South Africa

ISBN: (数字)9781728145778

ISBN: (纸本)9781728145785

Natural Language Processing (NLP) presents a set of techniques that are finding applications in modern healthcare, for the extraction and generation text. Clinical notes are classically originated and derived from various sources of narratives such as reports, referral letters, discharge notes and clinical summaries. In this paper, we present algorithms and a tool for enabling each member of a medical team to read and understand each others medical notes, using NLP techniques. We refer to this process as the decryption, or the deciphering, of complex clinical notes into simple readable language. We have presented a tool called the Clinical Note Translator (CNT). Based on the replacement of technical terms in clinical notes, CNT translates these notes to plain text. This solution is expected to assist multidisciplinary medical teams in understanding peer-to-peer expert notes.

关键词： Medical diagnostic imaging Medical services Encoding Data mining Dictionaries Tools

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