.png){kind=icon}
返回
Supporting Uncertain Predicates in DBMS Using Approximate String Matching and Probabilistic Databases
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2020.3021945.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Current relational database systems are deterministic in nature and lack the support for approximate matching. The result of approximate matching would be the tuples annotated with the percentage of similarity but the existing relational database system can not process these similarity scores further. In this paper, we propose a system to support approximate matching in the DBMS field. We introduce a 'approximate to' (uncertain predicate operator) for approximate matching and devise a novel formula to calculate the similarity scores. Instead of returning an empty answer set in case of no match, our system gives ranked results thereby providing a glance at existing tuples closely matching with the queried literals. Two variants of the 'approximate to' operator are also introduced for numeric data: 'approximate to+' for higher-the-better and 'approximate to-' for lower-the-better cases. Efficient approximate string matching methods are proposed for matching string-type data whereas numeric closeness is used for other types of data (date, time, and number). We also provide results of our system taken over several sample queries that illustrate the significance of our system. All experiments are performed using the MySQL database, whereas the IMDb movie database and European Football database are used as sample datasets.
Keyword:
Approximate string matching
probabilistic databases
uncertain predicate
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
Distributed Processing of Probabilistic Top-k Queries in Wireless Sensor Networks无线传感器网络中概率Top-k查询的分布式处理
PREAI
分享收藏Exact String Matching Algorithms: Survey, Issues, and Future Research Directions.png)
IEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAI分享收藏
查看更多内容