Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/13018
Title: Answering topband queries in time series data
Authors: LI LING
Keywords: k-topband, consistent performance, time series data
Issue Date: 29-Dec-2007
Source: LI LING (2007-12-29). Answering topband queries in time series data. ScholarBank@NUS Repository.
Abstract: Top k queries are queries that request for k answers having the highest or lowest values for some attribute, expression, or function. These queries arise naturally in many database applications where users are interested in finding records that are closest to the values specified in a query. Example applications include census data analysis, data mining, information retrieval and similarity search of multimedia data. For example, rather than finding all publications on a certain topic, a researcher may want to retrieve the ten most heavily referenced papers on the topic at hand.There has been a long stream of research work that address the efficient evaluation of top k queries in relational databases. In this thesis, we investigate the usefulness of top k queries in time series data and introduce a new class of queries called k-topband. Topband queries aim to retrieve objects that are within top k at every time point over a specified time interval. This kind is queries is designed from the observation that objects which exhibit some consistent behavior over a period of time would enable decision-makers to assess, with greater confidence, the potential merits of the objects. A rank-based approach is proposed to evaluate topband queries efficiently. Experiment results on both synthetic and real world datasets indicate that the proposed approach is efficient and scalable, and has direct applications in real world scenarios.
URI: http://scholarbank.nus.edu.sg/handle/10635/13018
Appears in Collections:Master's Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
mThesis-ml.pdf452.46 kBAdobe PDF

OPEN

NoneView/Download

Page view(s)

198
checked on Dec 11, 2017

Download(s)

140
checked on Dec 11, 2017

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.