Solve the Data Stream Problem by TOP-N Query based on Learning
The study of data stream,a series of conclusions can be drawn,such as:data stream with realtime,continuity,universality,semantic uncertainty and other features.In the traditional data stream processing techniques,such as:histogram method,sampling method,the hash method.Based on these method,this paper proposes the use of based on sliding window model constructed the summary of the database,so as to use TOP-N query based on learning solve the data stream problems provide possible.In the traditional TOP-N query,the paper proposes a topN query based on learning.The method first need to construct a knowledge database to store the query profile,and then to search the knowledge database.Knowledge database in the search,you can get the query radius r by calculate the density p,thus approximate get the requirements of the N results.When a new batch of data into the summary database,needed to update the knowledge database and maintain.
data stream sliding window model summary database TOP-N query knowledge database
Zhiqiang Cao
Hebei University HBU Baoding,China
国际会议
太原
英文
146-150
2011-02-26（万方平台首次上网日期，不代表论文的发表时间）