Dataset Groups Activity Stream PoWareMatch: a Quality-aware Deep Learning Approach to Improve Human Schema Matching The dataset used in the paper is a human matching dataset, consisting of 7,618 matching decisions from 175 human matchers over common benchmarks. BibTex: @dataset{Roee_Shraga_and_Avigdor_Gal_2025, abstract = {The dataset used in the paper is a human matching dataset, consisting of 7,618 matching decisions from 175 human matchers over common benchmarks.}, author = {Roee Shraga and Avigdor Gal}, doi = {10.57702/wvyw3yqp}, institution = {No Organization}, keyword = {'deep learning', 'human matching', 'ontology alignment', 'quality-aware', 'schema matching'}, month = {jan}, publisher = {TIB}, title = {PoWareMatch: a Quality-aware Deep Learning Approach to Improve Human Schema Matching}, url = {https://service.tib.eu/ldmservice/dataset/powarematch--a-quality-aware-deep-learning-approach-to-improve-human-schema-matching}, year = {2025} }
