Developing a Geo-Semantic Search Engine Capable of Querying Spatial Data with Natural Language

 Suggested by: Omid Reza Abbasi, Johannes Scholz  

Keywords: Geo-Semantic Search, Natural Language Processing, Spatial Data, Semantic Indexing, GIS, Information Retrieval, GeoAI, Knowledge Graphs 

 

Objective: Develop a lightweight geo-semantic search engine that enables users to query geospatial datasets using natural language. The research will focus on implementing a small-scale prototype using a semantic indexing method and evaluating its effectiveness in retrieving spatial data. 

 

Short Description: This thesis explores the intersection of geospatial data and natural language processing by developing a geo-semantic search engine. The system will allow users to retrieve spatial information through natural language queries, eliminating the need for complex query languages. By leveraging semantic indexing and lightweight AI models, the project aims to enhance accessibility to geospatial datasets. A prototype will be built and evaluated based on retrieval accuracy and user experience. 

 

Start: 

As soon as possible 

 

Prerequisites/qualification: 

• Knowledge in GIS and spatial data processing 

• Interest/Knowledge in Knowledge Graphs 

• Interest/Knowledge in Natural Language Processing