Multilingual Entity Matching
| Autor: | JooYoung Lee, Marius Frunza, Ilgiz Mustafin |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0303 health sciences
Matching (statistics) business.industry Computer science 030305 genetics & heredity String (computer science) 010501 environmental sciences computer.software_genre 01 natural sciences 03 medical and health sciences Transliteration Artificial intelligence business computer Natural language processing 0105 earth and related environmental sciences |
| Zdroj: | Advanced Information Networking and Applications ISBN: 9783030150310 AINA |
| DOI: | 10.1007/978-3-030-15032-7_68 |
| Popis: | The aim of this paper is to explore methods of multilingual entity matching. Name matching is currently the main technique used for entity resolution. When dealing with entities having features recorded in different languages and with different alphabets the basic approaches have serious limitation. The basic name matching approach using string comparison metrics is enriched with phonetic rules and with relational information. The results show that the approach using transliteration enhanced by phonetic matching provides with the best performance. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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