Abstract
Join operation is one of the most expensive ones in database management systems (DBMSs). In the context of the VQS (Vague Query System), which is a flexible query answering system built on top of DBMSs to provide them with similarity search/retrieval capabilities, vague joins are prohibitively expensive in terms of both IO-cost and CPU-cost because they must undergo intermediate processing steps with the sheer volume of multidimensional data in multiple feature spaces. This article presents problems arisen when processing complex vague joins in the VQS and introduces a new approach to efficiently solve these problems. This new approach not only reduces the costs significantly, but also returns to users the best matches or approximate nearest neighbors with a certain tolerant error e with respect to given vague join predicates. It is based on a novel, flexible, and efficient algorithm introduced recently for solving (approximate) complex vague queries in the VQS. Experimental results will show performance of the proposed approach
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 7th World Multiconference on Systemics, Cybernetics and Informatics - SCI 2003 |
| Publication status | Published - Jul 2003 |
Fields of science
- 102001 Artificial intelligence
- 102006 Computer supported cooperative work (CSCW)
- 102010 Database systems
- 102014 Information design
- 102015 Information systems
- 102016 IT security
- 102028 Knowledge engineering
- 102019 Machine learning
- 102022 Software development
- 102025 Distributed systems
- 502007 E-commerce
- 505002 Data protection
- 506002 E-government
- 509018 Knowledge management
- 202007 Computer integrated manufacturing (CIM)
- 102033 Data mining
- 102035 Data science
