A Probabilistic Framework for Vague Queries and Imprecise Information in Databases

摘要: A probabilistic learning model for vague queries and missing or imprecise information in databases is described. Instead of retrieving only a set answers, our approach yields ranking objects from the database response to query. By using relevance judgements user about retrieved, actual query as well overall retrieval quality system can be further improved. For specifying different kinds conditions queries, notion predicates introduced. Based on underlying model, also attribute values treated easily. In addition, corresponding formulas applied combination with standard (from two-valued logic), thus extending systems coping data.