Tootfinder

2021 retro-link! https://info.crunchydata.com/blog/fuzzy-name-matching-in-postgresql - Fuzzy string matching in PostgreSQL.

Leveraging Large Language Models for Fuzzy String Matching in Political Science
Yu Wang
https://arxiv.org/abs/2403.18218 https://arxi…

Leveraging Large Language Models for Fuzzy String Matching in Political Science
Fuzzy string matching remains a key issue when political scientists combine data from different sources. Existing matching methods invariably rely on string distances, such as Levenshtein distance and cosine similarity. As such, they are inherently incapable of matching strings that refer to the same entity with different names such as ''JP Morgan'' and ''Chase Bank'', ''DPRK'' and ''North Korea'', ''Chuck Fleischmann (R)'' and ''Charles Fleischmann (R)''. In this letter, we propose to use larg…

Disambiguate Entity Matching through Relation Discovery with Large Language Models
Zezhou Huang
https://arxiv.org/abs/2403.17344 https://

Disambiguate Entity Matching through Relation Discovery with Large Language Models
Entity matching is a critical challenge in data integration and cleaning, central to tasks like fuzzy joins and deduplication. Traditional approaches have focused on overcoming fuzzy term representations through methods such as edit distance, Jaccard similarity, and more recently, embeddings and deep neural networks, including advancements from large language models (LLMs) like GPT. However, the core challenge in entity matching extends beyond term fuzziness to the ambiguity in defining what co…

Two Online Map Matching Algorithms Based on Analytic Hierarchy Process and Fuzzy Logic
Jeremy J. Lin, Tomoro Mochida, Riley C. W. O'Neill, Atsuro Yoshida, Masashi Yamazaki, Akinobu Sasada
https://arxiv.org/abs/2402.11866

Two Online Map Matching Algorithms Based on Analytic Hierarchy Process and Fuzzy Logic
Our aim of this paper is to develop new map matching algorithms and to improve upon previous work. We address two key approaches: Analytic Hierarchy Process (AHP) map matching and fuzzy logic map matching. AHP is a decision-making method that combines mathematical analysis with human judgment, and fuzzy logic is an approach to computing based on the degree of truth and aims at modeling the imprecise modes of reasoning from 0 to 1 rather than the usual boolean logic. Of these algorithms, the way…

This https://arxiv.org/abs/2401.17809 has been replaced.
link: https://scholar.google.com/scholar?q=a

SWEA: Changing Factual Knowledge in Large Language Models via Subject Word Embedding Altering
Model editing has recently gained widespread attention. Current model editing methods primarily involve modifying model parameters or adding additional modules to the existing model. However, the former causes irreversible damage to Large Language Models (LLMs), while the latter incurs additional inference overhead and fuzzy vector matching is not always reliable. To address these issues, we propose an expandable Subject Word Embedding Altering (SWEA) framework, which finds the fused embeddings…