Search Results for author: Christian Bizer

Found 19 papers, 16 papers with code

Intermediate Training of BERT for Product Matching

2 code implementations DI2KG: International Workshop on Challenges and Experiences from Data Integration to Knowledge Graphs @ VLDB 2020 2020 Ralph Peeters, Christian Bizer, Goran Glavas

Adding the masked language modeling objective in the intermediate training step in order to further adapt the language model to the application domain leads to an additional increase of up to 3% F1.

 Ranked #1 on Entity Resolution on WDC Computers-small (using extra training data)

Entity Resolution Language Modelling +1

Supervised Contrastive Learning for Product Matching

1 code implementation4 Feb 2022 Ralph Peeters, Christian Bizer

We thus conclude that contrastive pre-training has a high potential for product matching use cases in which explicit supervision is available.

Contrastive Learning Data Augmentation +3

Using ChatGPT for Entity Matching

1 code implementation5 May 2023 Ralph Peeters, Christian Bizer

Always using the same set of 10 handpicked demonstrations leads to an improvement of 4. 92% over the zero-shot performance.

Entity Resolution In-Context Learning

Entity Matching using Large Language Models

1 code implementation17 Oct 2023 Ralph Peeters, Christian Bizer

We show that for use cases that do not allow data to be shared with third parties, open-source LLMs can be a viable alternative to hosted LLMs given that a small amount of training data or matching knowledge...

Entity Resolution

Dual-Objective Fine-Tuning of BERT for Entity Matching

1 code implementation Proceedings of the VLDB Endowment 2021 Ralph Peeters, Christian Bizer

The task can be approached by learning a binary classifier which distinguishes pairs of entity descriptions for the same real-world entity from descriptions of different entities.

Entity Resolution Multi-class Classification

Product Attribute Value Extraction using Large Language Models

1 code implementation19 Oct 2023 Alexander Brinkmann, Roee Shraga, Christian Bizer

We propose different prompt templates for instructing LLMs about the target schema of the extraction, covering both zero-shot and few-shot scenarios.

Attribute Attribute Value Extraction

Column Type Annotation using ChatGPT

1 code implementation TaDA@VLDB 2023 Keti Korini, Christian Bizer

Column type annotation is the task of annotating the columns of a relational table with the semantic type of the values contained in each column.

Column Type Annotation

Matching web tables to DBpedia-A feature utility study

1 code implementation EDBT 2017 Dominique Ritze, Christian Bizer

This paper contributes to improve the understanding of the utility of different features for web table to knowledge base matching by reimplementing different matching techniques as well as similarity score aggregation methods from literature within a single matching framework and evaluating different combinations of these techniques against a single gold standard.

Attribute Columns Property Annotation +2

Profiling Entity Matching Benchmark Tasks

1 code implementation International Conference on Information & Knowledge Management 2020 Anna Primpeli, Christian Bizer

In order to enable the exact reproducibility of evaluation results, matching tasks need to contain exactly defined sets of matching and non-matching record pairs, as well as a fixed development and test split.

Entity Resolution Feature Engineering

SC-Block: Supervised Contrastive Blocking within Entity Resolution Pipelines

1 code implementation6 Mar 2023 Alexander Brinkmann, Roee Shraga, Christian Bizer

To reduce these runtimes, entity resolution pipelines are constructed of two parts: a blocker that applies a computationally cheap method to select candidate record pairs, and a matcher that afterwards identifies matching pairs from this set using more expensive methods.

Blocking Contrastive Learning

Cross-Language Learning for Entity Matching

1 code implementation7 Oct 2021 Ralph Peeters, Christian Bizer

This poster explores along the use case of matching product offers from different e-shops to which extent it is possible to improve the performance of Transformer-based matchers by complementing a small set of training pairs in the target language, German in our case, with a larger set of English-language training pairs.

Cross-Lingual Transfer Entity Resolution

Product Information Extraction using ChatGPT

1 code implementation23 Jun 2023 Alexander Brinkmann, Roee Shraga, Reng Chiz Der, Christian Bizer

Hence, extracting attribute/value pairs from textual product descriptions is an essential enabler for e-commerce applications.

Attribute Language Modelling +1

Evaluating the Impact of Phrase Recognition on Concept Tagging

no code implementations LREC 2012 Pablo Mendes, Joachim Daiber, Rohana Rajapakse, Felix Sasaki, Christian Bizer

In this paper we evaluate the impact of the phrase recognition step on the ability of the system to correctly reproduce the annotations of a gold standard in an unsupervised setting.

Entity Linking Named Entity Recognition (NER) +1

DBpedia: A Multilingual Cross-domain Knowledge Base

no code implementations LREC 2012 Pablo Mendes, Max Jakob, Christian Bizer

The DBpedia project extracts structured information from Wikipedia editions in 97 different languages and combines this information into a large multi-lingual knowledge base covering many specific domains and general world knowledge.

Entity Linking Question Answering +4

A Large DataBase of Hypernymy Relations Extracted from the Web.

no code implementations LREC 2016 Julian Seitner, Christian Bizer, Kai Eckert, Stefano Faralli, Robert Meusel, Heiko Paulheim, Simone Paolo Ponzetto

Hypernymy relations (those where an hyponym term shares a {``}isa{''} relationship with his hypernym) play a key role for many Natural Language Processing (NLP) tasks, e. g. ontology learning, automatically building or extending knowledge bases, or word sense disambiguation and induction.

Word Sense Disambiguation

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