WInte.r is a Java framework for end-to-end data integration. The WInte.r framework implements well-known methods for data pre-processing, schema matching, identity resolution, data fusion, and result evaluation.
- Updated
May 20, 2022 - Java
WInte.r is a Java framework for end-to-end data integration. The WInte.r framework implements well-known methods for data pre-processing, schema matching, identity resolution, data fusion, and result evaluation.
A tool facilitating matching for any dataset discovery method. Also, an extensible experiment suite for state-of-the-art schema matching methods.
Entity linking, entity typing and relation extraction: Matching CSV to a Wikibase instance (e.g., Wikidata) via Meta-lookup
A .NET class library that allows you to import data from different sources into a unified destination
A python tool using XGboost and sentence-transformers to perform schema matching task on tables.
AgreementMaker Ontology Matching System
Match schema attributes of relational databases by value similarity. As a study assignment, this isn't well documented, but you can contact me for questions and I may even add docs, if I sense enough interest.
Functional and structural analysis of tables in research papers (Table disentangling)
🌮 Table-based KB Completer
Master thesis - reproducing state-of-the-art schema matching algorithms
Valentine scalable deployment for VLDB demo
Knowledge Graph-based Retrieval-Augmented Generation for Schema Matching
Repository for developing and evaluating components and algorithms for data integration tasks
CLI tool for inserting SELECT query results into ClickHouse with automatic schema matching and type-safe casting. Ideal for ETL pipelines and SQL-driven data flows.
Data Integration - Schema Matching & Mapping
Python client for the Serene Data Integration software
The PyDI framework provides methods for end-to-end data integration. The framework covers all steps of the integration process, including schema matching, data translation, entity matching, and data fusion. The framework offers traditional string-based methods as well as modern LLM- and embedding-based techniques for these tasks.
[Information System] SMUTF: Schema Matching Using Generative Tags and Hybrid Features
Master thesis: Holistic Schema Matching at Scale
Collaborative Scoping in Action
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