CCC – Cost Calculation Chatbot

Award-winning HTWK team project focused on question answering over project cost data with Knowledge Graphs, RDF/SPARQL, LangChain, and Qanary.

Overview

CCC is relevant to my current AI direction because it connects question answering, semantic search, structured knowledge representation, and practical chatbot workflows. The project was awarded the Best Semantic Web Poster Award 2026 at the 14th Leipziger Semantic Web Tag.

Tech stack

Knowledge GraphsRDFSPARQLSemantic WebQuestion AnsweringLangChainQanaryChatbots

Award and relevance

  • •Best Semantic Web Poster Award 2026 at the 14th Leipziger Semantic Web Tag.
  • •Question-answering approach for making structured project cost data accessible through natural language.
  • •Demonstrates practical experience with Knowledge Graphs, RDF/SPARQL, LangChain, Qanary, and semantic AI workflows.

Project structure

  • •Knowledge graph as the structured source of domain knowledge.
  • •RDF/SPARQL used to represent and query structured relationships.
  • •LangChain and Qanary used for chatbot and question-answering workflow orchestration.