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Council Insights Heidelberg  - Data Analytics on Council Work using LLM

Started ‎08-21-2024 by
Modified ‎11-21-2024 by
Views 4,721
 
PITCH VIDEO
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      TEAM PCITURE
      Hack24_CityCouncilHeidlberg_TeamPicture.jpg

      Team Name 

      Council Insights Heidelberg  

      Track 

      Public Sector 

      Use Case 

      Implementing Lage Language Models LLM for a strong Democracy

      Technology 

       SAS Viya Model Manager, Intelligent Decisioning, Visual Text Analytics, Visual Analytics, Python, LLM, NLP, SAS Viya

      Region 

      Heidelberg, Germany 

      Team lead 

      Benjamin Gärtner @benj_gaertner 

      Team members 

      Stephan Frenzel,   Ahsan Ali, Maria Shcheglova, Christoph Blattgerste (Student), Harsh Patel (Student) , Silvio Martin (Scientific Staff, KIT), Lutz Berger,  Ian Doig, Slava Kuliger, Stephan Verclas, Patrik Bannholzer,  Andreas Koch,   Sebastian Warkentin, Maik Röder
      Sundaresh Sankaran (Mentor), Ulrich Reincke (Mentor)

      Social media handles 

       See the team's  LinkedIn Page specific for the #SASHackathonhttps://www.linkedin.com/company/hack-team-heidelberg/posts/?feedView=all

      Is your team interested in participating in an interview? 

      yes 

      Optional: Expand on your technology expertise 

       

      ============== 

       

      Plan 

      1.  Create automated scripts to regularly retrieve and download relevant documents from the local council website (https://www.gemeinderat.heidelberg.de/info.asp). 
      2. Indexation and vectorization of the scraped data 
      3. Data Analytics on the vectorized data using NLP, LLM and SAS Viya 

      Motivation 

      Our aim is to improve the transparency and accessibility of the work of Heidelberg Municipal Council. We want to enable citizens, the press and other interested parties to find out quickly and easily about the resolutions and activities of the local council. By visualizing and better presenting the work of the committees, we can strengthen citizens' commitment and trust in local government. 

       

      Analysis of strategies 

       

      We would like to compare the strategic objectives of the city of Heidelberg with the activities and resolutions of the municipal council in order to identify specific resolutions that contribute to the implementation of strategic objectives. 

       

      Relevant strategies can be strategies developed by the city of Heidelberg, such as the Heidelberg Biodiversity Strategy, as well as strategies that are valid nationwide, such as the practical guide ‘Climate Protection in Municipalities’ from the German Institute of Urban Studies. 

       

      Possible outputs 

       

      • Analytics on stringency, consistency or legality of council work  
      • Location of resolutions on a map (e.g. by districts, streets, etc.) where possible 
      • Filter function according to districts, topics, committees, time reference (last 6 months or similar) 
      • Search functions (full text, language, locations/regions/environment) 
      • Summary of resolutions in understandable language 
      • Create a chatbot or integration of an intelligent search 
      • Possibly other types of visualizations – Mindmaps, Knowledge Graphs or similar according to keywords or districts (e.g. which topics have been discussed most frequently in the last 6 months) 
      Comments

      Link to the Team Page on LinkedIn with the making of the videos: https://www.linkedin.com/company/hack-team-heidelberg/posts/?feedView=all

      Hack24_CityCouncilHeidlberg_TeamPicture.jpg

      Fantastic work, great team effort - and so nice videos! I am impressed - and as a citizen of Heidelberg proud of those ambitions!!

      Great job ! you did something very useful for citizen as well 

      Congratulations team, great use case, applicable to every state, municipality and country. Also, great approach to solve it using LLMs, AI, analytics and SAS capabilities.

      Very cool project, great use of text analytics, and overall excellent team effort.  Well done!

      Version history
      Last update:
      ‎11-21-2024 09:24 AM
      Updated by:

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