Repository for CS 838 (Spring 2017) Data Science project
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Updated
Apr 1, 2017 - Jupyter Notebook
Entity resolution (also known as data matching, data linkage, record linkage, and many other terms) is the task of finding entities in a dataset that refer to the same entity across different data sources (e.g., data files, books, websites, and databases). Entity resolution is necessary when joining different data sets based on entities that may or may not share a common identifier (e.g., database key, URI, National identification number), which may be due to differences in record shape, storage location, or curator style or preference.
Repository for CS 838 (Spring 2017) Data Science project
ProxCluster is a framework for Incremental Entity Resolution that leverages concepts similar to K-Means for clustering duplicates. This work was developed as the final paper for my Bachelor degree in Computer Science
A Single View application aggregates and reconciles data from multiple sources to create a single view of an entity.
AdapterEM: Pre-trained Language Model Adaptation for Generalized Entity Matching using Adapter-tuning
This projects aims to provide lists containing only great movies to users based only a gew filters and search parameters.
Crawl, matching and explore data about jobs in Viet Nam.
Weka Comparator to match rules to test data with filtering abilites
Undergraduate Final Project (needs README up to date!!) - Scientific paper soon to be included
Service for automatic matching two data sets without mapping
An extension for ASReview Lab to preprocess the dataset before importing in ASReview
An open-source compound AI toolchain for fast and accurate entity matching, powered by LLMs.
A collection of awesome resources regarding Record Linkage.
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.
🔎 Finds fuzzy matches between datasets
A maximum-strength name parser for record linkage.
Fuzzy string matching in R. Inspired by Python's thefuzz (but without the Python).
Welcome to Snowman App – a Data Matching Benchmark Platform.
A browser user interface for manual labeling of record pairs.
Curated list of awesome software and resources for Senzing, The First Real-Time AI for Entity Resolution.
Created by Halbert L. Dunn
Released 1946