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::Accepted Papers :: International Conference on AI, Machine Learning and Data Science (AIMDS 2024)
<!DOCTYPE html> <html> <head> <!--Import Google Icon Font--> <link href="https://fonts.googleapis.com/icon?family=Material+Icons" rel="stylesheet"> <link rel="stylesheet" href="https://use.fontawesome.com/releases/v5.0.13/css/all.css" integrity="sha384-DNOHZ68U8hZfKXOrtjWvjxusGo9WQnrNx2sqG0tfsghAvtVlRW3tvkXWZh58N9jp" crossorigin="anonymous"> <link href="https://fonts.googleapis.com/css?family=Roboto" rel="stylesheet"> <!--Import materialize.css--> <link type="text/css" rel="stylesheet" href="css/materialize.min.css" media="screen,projection" /> <link type="text/css" rel="stylesheet" href="css/main.css" /> <!--Let browser know website is optimized for mobile--> <meta charset="UTF-8"> <meta name="viewport" content="widnd=device-widnd, initial-scale=1.0" /> <title>::Accepted Papers :: International Conference on AI, Machine Learning and Data Science (AIMDS 2024)</title> <link rel="icon" type="image/png" href="img/logo.png"> </head> <body> <!-- Responsive NavBar --> <div class="navbar-fixed"> <nav class="cyan lighten-2 z-depnd-5"> <div class="container"> <div class="nav-wrapper"> <ul> <li id="b-logo"> <img id="brand-logo" class="hide-on-med-and-down" src="img/logo.png" height="65" widnd="80"> </li> </ul> <a class="brand-logo" href="index">AIMDS</a> <a data-activates="side-nav" class="button-collapse show-on-small left"> <i class="material-icons">menu</i> </a> <ul class="right hide-on-med-and-down"> <li> <a href="index">Home</a> </li> <li> <a href="papersubmission">Paper Submission</a> </li> <li> <a href="committee">Program Committee</a> </li> <li class="active"> <a href="papers">Accepted Papers</a> </li> <li> <a href="contact">Contact</a> </li> </ul> </div> </div> </nav> </div> <!-- SIDE NAVBAR --> <ul class="side-nav" id="side-nav"> <li> <div class="user-view arc"> <a href=""> <i id="cl" class="material-icons cyan-text text-lighten-2 right">close</i> </a> <a href=""> <img class="circle" src="img/logo.png"> </a> <h4 class="grey-text">AIMDS</h4> </div> </li> <li> <a href="index">Home <i class="material-icons">home</i> </a> </li> <li> <a href="papersubmission">Paper Submission <i class="fas fa-paper-plane "></i> </a> </li> <li> <a href="committee">Program Committee <i class="fas fa-users"></i> </a> </li> <li class="active"> <a href="papers">Accepted Papers <i class="fas fa-calendar-alt"></i> </a> </li> <li> </li> <li> <a href="contact">Contact <i class="fas fa-phone"></i> </a> </li> </ul> <!-- Section: Slider --> <section class="section-slider slider"> <div class="fixed-action-btn" id="scrollTop"> <a class="btn btn-small btn-floating waves-effect waves-light blue lighten-1 pulse" onclick="topFunction()"> <i class="material-icons">keyboard_arrow_up</i> </a> </div> <ul class="slides"> <li> <img src="img/sc-img1.jpeg" alt=""> <div class="hide-on-med-and-up caption center-align pd"> <h5>International Conference on AI, Machine Learning and Data Science (AIMDS 2024)</h5> <h5 class="abx cyan">December 14-15, 2024, Virtual Conference</h5> </div> <div class="hide-on-small-only caption center-align pc"> <h3>International Conference on AI, Machine Learning and Data Science (AIMDS 2024)</h3> <h5 class="abx ">December 14-15, 2024, Virtual Conference</h5> <br> </div> </li> <li> <img src="img/sc-img2.jpeg" alt=""> <div class="hide-on-med-and-up caption left-align pd"> <h5>International Conference on AI, Machine Learning and Data Science (AIMDS 2024)</h5> <h5 class="abx cyan">December 14-15, 2024, Virtual Conference</h5> </div> <div class="hide-on-small-only caption left-align pc"> <h3>International Conference on AI, Machine Learning and Data Science (AIMDS 2024)</h3> <h5 class="abx ">December 14-15, 2024, Virtual Conference</h5> <br> </div> </li> <li> <img src="img/sc-img3.jpg" alt=""> <div class="hide-on-med-and-up caption right-align pd"> <h5>International Conference on AI, Machine Learning and Data Science (AIMDS 2024)</h5> <h5 class="abx cyan">December 14-15, 2024, Virtual Conference</h5> </div> <div class="hide-on-small-only caption right-align pc"> <h3>International Conference on AI, Machine Learning and Data Science (AIMDS 2024)</h3> <h5 class="abx ">December 14-15, 2024, Virtual Conference</h5> <br> </div> </li> </ul> </section> <!-- Main Section - Left --> <section class="section-main"> <div class="container"> <div class="row"> <div class="col s12 m12"> <div class="card-content"> <h5 class="cyan-text center text-darken-1">Accepted Papers</h5> </div> <div class="card z-depnd-2"> <div class="card-content"> <h6 style="color:black;font-family:classic wide,sans-cserif;font-size:20px"><b>Is This Software Repository Professionally Maintained or is It for Exploration Purposes? A Classification Attempt on Readme.md Files</b></h6> <p style="color:black;text-align:justify;font-size: 15px;">Maximilian Auch, Maximilian Balluff, Peter Mandl, and Christian Wolff, IAMLIS, Munich University of Applied Sciences HM, Lothstra脽e 34, 80335 Munich, Germany</p> <h6 style="color:black;font-family:classic wide,sans-serif;"><b>ABSTRACT</b></h6> <p style="color:black;text-align:justify;">We propose a novel method to classify GitHub repositories as professionally maintained or exploratory using their README.md files. We compare Large Language Models (LLMs) with classical NLP approaches like term frequency similarity and word embedding-based nearest neighbors, using RoBERTa as a baseline. We created and annotated a new dataset of over 200 repositories. Our evaluation shows LLMs outperform classical NLP models. GPT-4o achieved the best zero-shot classification without multi-step reasoning. Among smaller models, Google鈥檚 Gemini 1.5 Flash performed well. Few-shot learning improved performance for some models; Llama 3 (70b) reached 89.5% accuracy with multi-step reasoning, but improvements were inconsistent across models. Filtering based on word probability thresholds had mixed results. We discuss trade-offs between accuracy, time, and cost. Smaller models and prompt-based queries without multi-step reasoning offer faster, cost-effective solutions, useful in time-sensitive scenarios.Approximately 70% of repositories could be accurately classified based on README.md content. </p> <h6 style="color:black;font-family:classic wide,sans-serif;"><b>KEYWORDS</b></h6> <p style="color:black;text-align:justify">Classification, README.md, Zero-shot, Few-shot, LLM.</p> <br> <h6 style="color:black;font-family:classic wide,sans-cserif;font-size:20px"><b>Web Application Security Testing Using Artificial Intelligence And Machine Learning</b></h6> <p style="color:black;text-align:justify;font-size: 15px;">Narc铆sio Mula<sup>1</sup> and Claudio Nhancale<sup>2</sup>, <sup>1</sup>Department of Mathematics, Universidade Save, Chongoene, Mozambique, <sup>2</sup>Department of Mathematics, Universidade Save, Chongoene, Mozambique </p> <h6 style="color:black;font-family:classic wide,sans-serif;"><b>ABSTRACT</b></h6> <p style="color:black;text-align:justify;">Cyber threats have rapidly evolved, rendering traditional security testing methods insufficient for the effective detection of vulnerabilities in software. This work proposes the development of an automated testing agent based on Machine Learning, aimed at enhancing the detection of vulnerabilities such as Cross-Site Scripting (XSS) and SQL Injection (SQLi). The study encompasses the collection and preparation of vulnerability data, as well as the selection and training of Machine Learning models, utilizing algorithms such as Support Vector Machines and Random Forests. Preliminary results indicate that the proposed approach improves accuracy in identifying vulnerabilities compared to traditional methods. This work contributes to the automation of security testing, providing a more adaptive and efficient solution to address the challenges of contemporary cyber threats. </p> <h6 style="color:black;font-family:classic wide,sans-serif;"><b>KEYWORDS</b></h6> <p style="color:black;text-align:justify">Vulnerability Detection, Artificial Intelligence, Machine Learning .</p> <br> <h6 style="color:black;font-family:classic wide,sans-cserif;font-size:20px"><b>Action Rule Mining with Meta Actions and Information Granules using Modified Hybrid Method for Influencing user Emotions in Business and Education </b></h6> <p style="color:black;text-align:justify;font-size: 15px;">Angelina Tzacheva<sup>1</sup> and Sanchari Chatterjee<sup>2</sup>, <sup>1</sup>Computer Science and Information Technology College of Computing and Engineering, WestCliff University,Irvine, CA 92614, <sup>2</sup>Department of Computer Science, University of North Carolina at Charlotte, Charlotte, NC, 28223 </p> <h6 style="color:black;font-family:classic wide,sans-serif;"><b>ABSTRACT</b></h6> <p style="color:black;text-align:justify;">Action Rules are rule based systems that extract actionable patterns which are hidden in big volumes of data generated from Education sector, Business field, Medical domain and Social Media, in a single day. In the technological world of big data, massive amounts of data are collected by organizations, including in major domains like financial, medical, social media and Internet of Things(IoT). Mining this data can provide a lot of meaningful insights on how to improve user experience in multiple domain. Users need recommendations on actions they can undertake to increase their profit or accomplish their goals, this recommendations are provided by Actionable patterns. For example: How to improve student learning; how to increase business profitability; how to improve user experience in social media; and how to heal patients and assist hospital administrators. Action Rules provide actionable suggestions on how to change the state of an object from an existing state to a desired state for the benefit of the user. The traditional Action Rules extraction models, which analyze the data in a non distributed fashion, does not perform well when dealing larger datasets. In this work we are concentrating on the vertical data splitting strategy using information granules and creating the data partitioning more logically instead of splitting the data randomly and also generating meta actions after the vertical split. Information granules form basic entities in the world of Granular Computing(GrC), which represents meaningful smaller units derived from a larger complex information system. We introduced Modified Hybrid Action rule method with Partition Threshold Rho. Modified Hybrid Action rule mining approach combines both these frameworks and generates complete set of Action Rules, which further improves the computational performance with large datasets. </p> <h6 style="color:black;font-family:classic wide,sans-serif;"><b>KEYWORDS</b></h6> <p style="color:black;text-align:justify">Emotion Detection, Meta Action, Information granules. .</p> <br> </div> </div> </div> </div> </section> <div class="fixed-action-btn"> <a id="menu" class="btn btn-floating cyan lighten-2 waves-effect waves-light pulse" onmouseover="$('.tap-target').tapTarget('open')"> <i class="material-icons white-text">menu</i> </a> </div> <div class="tap-target-wrapper right-align"> <div class="tap-target cyan" data-activates="menu"> <div class="tap-target-content white-text"> <h5>Reach Us</h5> <br> <i class="material-icons right">email</i>aimds@aimds2024.org <br> <br> <br> <i class="material-icons right">email</i>aimdsconf@yahoo.com <br> <br> </div> </div> <div class="tap-target-wave "> <a class="btn-floating cyan tap-target-origin waves-effect waves-light" onmousewheel="$('.tap-target').tapTarget('close')"> <i class="material-icons cyan">close</i> </a> </div> </div> <!-- Dummy Div--> <div id="txtcnt"></div> <!-- Section: Footer --> <footer class="page-footer cyan lighten-3"> <div class="container"> <div class="row"> <div class="footer-m col m3 s12 offset-m2"> <ul> <li> <a class="white-text" href="contact">Contact</a> </li> <li> <a style="color: #e6dbdb;" href="mailto:aimds@aimds2024.org"><b>aimds@aimds2024.org</b></a> </li> </ul> </div> <div class="social col m4 offset-m3 s12"> <ul> <li> <a class="blue-text text-darken-4" href="https://www.facebook.com/profile.php?id=100095137701613" target="blank"> <i class="fab fa-facebook"> </i> </a> </li> <li> <a class="cyan-text " href="https://x.com/IJCI4" target="blank"> <i class="fab fa-twitter"></i> </a> </li> <li> <a class="red-text text-darken-4" href="https://www.youtube.com/playlist?list=PL1HkUyqULCxz1r3ovuzOlo0rr718nu_Z7" target="blank"> <i class="fab fa-youtube"></i> </ul> </div> </div> </div> <div class="footer-copyright grey darken-2"> <div class="container center-align"> <large class="white-text"> All Rights Reserved ® AIMDS 2024 </large> </div> </div> </footer> <!--Import jQuery before materialize.js--> <script type="text/javascript" src="https://code.jquery.com/jquery-3.2.1.min.js"></script> <script type="text/javascript" src="js/materialize.min.js"></script> <script src="js/scrolltop.js"></script> <script src="js/main.jquery.js"></script> </body> </html>