Reference website to measuring similarity of tree structured data using the tree edit distance measure. The runnable and source code of the RTED algorithm - most efficient tree edit distance algorithm.
A doctoral college in Geographic Information Sciences at the University of Salzburg. In the context of this project, the database research group works on extend GIS capabilities of database systems with a focus on two main topics:
An isochrone in a spatial network is a possibly disconnected subgraph that covers all space points from which a specific point of interest is reachable within a given time period at a specific point in time. Isochrones have interesting applications, for example, geomarketing (e.g., positioning of franchise stores) or urban planing (e.g., finding spots in the city that are hard to reach by public transportation). Isochrones are particularly interesting as part of a larger query that combines spatial and non-spatial aspects. Answering such queries is challenging, in particular when multimodal networks are involved. The goal of the project is to extend SQL with the notion of isochrones and develop efficient evaluation strategies for isochrones in multimodal networks.
Data often have an implicit spatial aspect (e.g., a restaurant has a location even if the location is not stored in the database). Enriching data with explicit spatial references, called geocoding, adds value to the data. In order to introduce spatial references into a data set, non-spatial attributes must be used to link the non-geocoded data to pre-existing geocoded data, i.e., a join must be computed. Since in geocoding the joined datasets often originate from different sources, there may be no common key value. Then, computing the join is challenging: exact join conditions (which are efficient and well studied) will fail since data items that represent the same real world object may differ. The goal of this project is to advance the state of the art in processing similarity queries on large data volumes in GIS-enabled relational database systems.
Duration: 2015 - 2019
Partners: Z_GIS, Dept. of Geographie and Geology (Univ. Salzburg), ZAMG, Louisiana State University
Funding: 2'133'000 EUR (Austrian Science Fund - FWF)
We empirically evaluated set similarity join techniques. We provide an extended version of our PVLDB paper as well as the runnable source code for the experiments.