dc.contributor.author	Ganesan, Kaushik	en
dc.contributor.author	Nanjundan, Deepak	en
dc.contributor.author	Srivastava, Deval	en
dc.contributor.author	Neog, Abhilash	en
dc.contributor.author	Jayaprakash, Dharneeshkar	en
dc.contributor.author	Shah, Aditya	en
dc.date.accessioned	2023-03-10T18:01:06Z	en
dc.date.available	2023-03-10T18:01:06Z	en
dc.date.issued	2023-01-11	en
dc.description.abstract	Under the guidance of Dr. Edward A. Fox, the class of CS5604 Fall 2022 semester at Virginia Tech was assigned the task of building an Information Retrieval and Analysis System that can support a collection of at least 5000 Electronic Theses and Dissertations (ETDs). The system would act as a search engine, supporting a number of features, such as searching, providing recommendations, ranking search results, and browsing. In order to achieve this, the class was divided into five teams, each assigned separate tasks with the intent of collaborating through CI/CD. The roles can be described as follows: Content and Representation, End-user Recommendation and Search, Object Detection and Topic Models, Classification and Summarization with Language Models, and Integration and Coordination. The intent of the report is to outline the contribution of Team 4, which focuses on language models, classification, summarization, and segmentation. In this project, Team 4 was successful in reproducing Akbar Javaid Manzoor’s pipeline to segment ETD into chapters, summarize the segmented chapters using extractive and abstractive summarizing techniques, and classify the chapters using deep learning and language models. Using the APIs developed by Team 1, Team 4 was also tasked with storing the outcomes of 5000 ETDs in the file system and database. Team 4 containerized the services and assisted Team 5 with workflow automation to help automate the services. The project’s main lessons were effective team collaboration, efficient code maintenance, containerization of services, upkeep of a CI/CD workflow, and finally effective information storage retrieval at scale. The report describes the goals, tasks, and achievements, along with our coordination with the other teams in completing the higher-level tasks concerning the entire project.	en
dc.description.notes	Team4ClassSummReport.zip - Final report (Zip from Overleaf) Team4ClassSummReport.pdf - Final report (PDF version) Team4ClassSummPresentation.pptx - Final presentation (PowerPoint version) Team4ClassSummPresentation.pdf - Final presentation (PDF version) team4_documentView_demo.mp4 - Document View Page of User Interface Demo Video team4_experimenter_demo.mp4 - Experimenter Page User Interface Demo Video	en
dc.identifier.uri	http://hdl.handle.net/10919/114077	en
dc.language.iso	en_US	en
dc.publisher	Virginia Tech	en
dc.rights	Attribution-NonCommercial-ShareAlike 4.0 International	en
dc.rights.uri	http://creativecommons.org/licenses/by-nc-sa/4.0/	en
dc.subject	Natural Language Processing	en
dc.subject	Segmentation	en
dc.subject	Summarization	en
dc.subject	Classification	en
dc.subject	Language Models	en
dc.title	Team 4: Segmentation, Summarization, and Classification	en
dc.type	Presentation	en
dc.type	Report	en
dc.type	Video	en

Team 4: Segmentation, Summarization, and Classification

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