Co-Pilot for Project Managers: Developing a PDF-Driven AI Chatbot for Facilitating Project Management

IF 3.4 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Khorshed Alam;Mahbubul Haq Bhuiyan;Mohammad Shafiqul Islam;Abul Hossain Chowdhury;Zaheed Ahmed Bhuiyan;Suman Ahmmed
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引用次数: 0

Abstract

Our AI-driven PDF Chatbot is specialized for Project Management (PM) Automation and acts as a virtual Project Manager that offers continuous support to global teams. It interprets PDF data like SRS reports and interview transcripts by utilizing Open-Assistant’s SFT-1 12B Model. Insights from interviews of 15 project managers have enriched the knowledge base of our chatbot and ultimately enabled informative responses to the stakeholders of the project. Advanced AI techniques ensure efficient text preprocessing, including tokenization, numerical normalization, lowercasing, removing punctuation, removing extra spaces, recursive character text splitter, and lemmatization. It is primarily tailored for e-commerce project and provides precise guidance based on e-commerce data and risk management factors. With an average cosine similarity of 80.80% and semantic similarity score of 85.21%, it consistently aligns with PDF Contents and optimize the project management phases & methodologies. This innovation enhances Human-Robot Interaction, PM Automation, facilitates decision-making, and enables uninterrupted communication. While AI-driven PDF chatbots like ChatPDF and SciSummary exist, our chatbot is uniquely focused on automating project management tasks, providing tailored insights for e-commerce projects and decision-making, thus offering a breakthrough in PM automation. To ensure the chatbot’s robustness in context-aware responds, we compare our chatbot with ChatPDF and Sci-summary which are some PDF driven chatbots. Making our work available open-source on https://github.com/codewithkhurshed/SPM-project-repo can enhance its accessibility and promote future research opportunities in PDF driven chatbot development.
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来源期刊
IEEE Access
IEEE Access COMPUTER SCIENCE, INFORMATION SYSTEMSENGIN-ENGINEERING, ELECTRICAL & ELECTRONIC
CiteScore
9.80
自引率
7.70%
发文量
6673
审稿时长
6 weeks
期刊介绍: IEEE Access® is a multidisciplinary, open access (OA), applications-oriented, all-electronic archival journal that continuously presents the results of original research or development across all of IEEE''s fields of interest. IEEE Access will publish articles that are of high interest to readers, original, technically correct, and clearly presented. Supported by author publication charges (APC), its hallmarks are a rapid peer review and publication process with open access to all readers. Unlike IEEE''s traditional Transactions or Journals, reviews are "binary", in that reviewers will either Accept or Reject an article in the form it is submitted in order to achieve rapid turnaround. Especially encouraged are submissions on: Multidisciplinary topics, or applications-oriented articles and negative results that do not fit within the scope of IEEE''s traditional journals. Practical articles discussing new experiments or measurement techniques, interesting solutions to engineering. Development of new or improved fabrication or manufacturing techniques. Reviews or survey articles of new or evolving fields oriented to assist others in understanding the new area.
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