Semantic Name Matching

摘要: Names are studied in different fields, and, among the issues they present,name variations (e.g., translations, misspellings, etc...) and name variants pseudonyms) pose a challenge to matching, i.e., discovering instances that differ typographically but represent same entity. Our scenario for matching is P2P, entity-based network of users divided local level (the users), community (groups global level(all entities). Entities at partial view real word entity, represented level. In this framework, change orthography names because linguistic social factors, their presence depends on considered. Thus, hard tackle by an automatic approach such as matching. Our proposed solutions use taxonomy we created understand predict entity names, divide entries accommodate original plus variations variants. novel take advantage multidisciplinary method, drawing from various fields (i.e., philosophy, sociology geography) importing terms views not found computer science. We also draw areas close building from their findings expanding them.