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Interactive Testimony Analysis Using Natural Language Processing
CS-C-09
Yoav Vaknin; yoavva1@ac.sce.ac.il Dmitri Shpak; dmitrsh5@ac.sce.ac.il
Advisors: Mr. Idan Tobis1, Prof. Shlomo Greenberg1 1SCE - Shamoon College of Engineering, Ashdod
This project focused on developing a system that receives video interviews of Jewish soldiers from World War II, transcribes the spoken content into text, and automatically generates a concise summary. Using advanced natural language processing (NLP) techniques, the system identifies key themes such as geographic locations, time periods, and battle contexts. These elements enable the creation of thematic connections between different testimonies. A dedicated search engine, integrated into a custom-built website, allows users to explore related interviews based on shared topics or historical settings. The goal was to preserve these valuable historical narratives, structure them, and make them more accessible and searchable for researchers, educators, and the general public.
Keywords: Jewish soldiers, NLP, oral history, search engine, speech-to-text, summarization, testimonies, WWII
Efficiency Algorithm for a Sequence of Brauer Tree Mutations
CS-C-10
Or Loren; orlo3@ac.sce.ac.il
Advisor: Dr. Zehava Zvi
SCE - Shamoon College of Engineering, Ashdod
Brauer tree algebras are important fundamental blocks in the modular representation theory of groups. Aihara developed an algorithm known as a mutation reduction, for reducing a Brauer tree algebra to the simpler Brauer star algebra by using a sequence of mutations centered on edges. Zvi developed an algorithm which gives a natural numbering for the simpler Brauer star algebra. In this project, we applied computer science tools to obtain results in the modular representation theory. Our goal was to create a program to generate planar trees and to test the relative efficiency of Aihara's algorithm and Zvi's algorithm on these trees.
Keywords: Brauer tree algebras, efficiency program, mutations on Brauer trees