Efficient processing of continuous queries utilizing F-relationship in stock databases

Sanghyun Park, You Min Ha, Chihyun Park, Sang Wook Kim

Research output: Contribution to journalArticle

Abstract

This paper analyzes the properties of user queries in a system for stock investment recommendation, and defines the F-relationship, which is a new type of a relationship between two queries. A query is composed of user defined conditions for an interesting stock item and is systematically invoked whenever the price of that stock item is changed. An F-relationship between two queries Q1 and Q2 means that, if the recommendation type of a preceding query Q1 is X, then its following query Q2 always has X as its recommendation type, where the recommendation type is one of SELL, HOLD, BUY, and NONE. If there is an F-relationship between Q1 and Q2, the recommendation type of Q2 is decided immediately by that of Q1, therefore we can keep Q2 from being actually processed. To exploit this fact, we suggest two methods in this paper. The former analyzes all the F-relationships among user queries in the system and represents them as a graph. The latter searches the graph and decides the order of queries to be processed, which makes the number of unexecuted queries maximized. With these methods, a large portion of user queries are not actually processed. As a result, the performance of processing all the queries is greatly improved. We examined the superiority of the suggested methods through a variety of experiments using real-world stock market data. According to the results of our experiments, the overall time of continuous query processing with our proposed methods has reduced to less than 10% of that with the traditional method.

Original languageEnglish
Pages (from-to)131-149
Number of pages19
JournalComputer Science and Information Systems
Volume13
Issue number1
DOIs
Publication statusPublished - 2016 Jan

Fingerprint

Query processing
Processing
Experiments
Financial markets

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

Cite this

Park, Sanghyun ; Ha, You Min ; Park, Chihyun ; Kim, Sang Wook. / Efficient processing of continuous queries utilizing F-relationship in stock databases. In: Computer Science and Information Systems. 2016 ; Vol. 13, No. 1. pp. 131-149.
@article{5d1537ba850543b4b7d0d2b4a8822059,
title = "Efficient processing of continuous queries utilizing F-relationship in stock databases",
abstract = "This paper analyzes the properties of user queries in a system for stock investment recommendation, and defines the F-relationship, which is a new type of a relationship between two queries. A query is composed of user defined conditions for an interesting stock item and is systematically invoked whenever the price of that stock item is changed. An F-relationship between two queries Q1 and Q2 means that, if the recommendation type of a preceding query Q1 is X, then its following query Q2 always has X as its recommendation type, where the recommendation type is one of SELL, HOLD, BUY, and NONE. If there is an F-relationship between Q1 and Q2, the recommendation type of Q2 is decided immediately by that of Q1, therefore we can keep Q2 from being actually processed. To exploit this fact, we suggest two methods in this paper. The former analyzes all the F-relationships among user queries in the system and represents them as a graph. The latter searches the graph and decides the order of queries to be processed, which makes the number of unexecuted queries maximized. With these methods, a large portion of user queries are not actually processed. As a result, the performance of processing all the queries is greatly improved. We examined the superiority of the suggested methods through a variety of experiments using real-world stock market data. According to the results of our experiments, the overall time of continuous query processing with our proposed methods has reduced to less than 10{\%} of that with the traditional method.",
author = "Sanghyun Park and Ha, {You Min} and Chihyun Park and Kim, {Sang Wook}",
year = "2016",
month = "1",
doi = "10.2298/CSIS141101042P",
language = "English",
volume = "13",
pages = "131--149",
journal = "Computer Science and Information Systems",
issn = "1820-0214",
publisher = "ComSIS Consortium",
number = "1",

}

Efficient processing of continuous queries utilizing F-relationship in stock databases. / Park, Sanghyun; Ha, You Min; Park, Chihyun; Kim, Sang Wook.

In: Computer Science and Information Systems, Vol. 13, No. 1, 01.2016, p. 131-149.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Efficient processing of continuous queries utilizing F-relationship in stock databases

AU - Park, Sanghyun

AU - Ha, You Min

AU - Park, Chihyun

AU - Kim, Sang Wook

PY - 2016/1

Y1 - 2016/1

N2 - This paper analyzes the properties of user queries in a system for stock investment recommendation, and defines the F-relationship, which is a new type of a relationship between two queries. A query is composed of user defined conditions for an interesting stock item and is systematically invoked whenever the price of that stock item is changed. An F-relationship between two queries Q1 and Q2 means that, if the recommendation type of a preceding query Q1 is X, then its following query Q2 always has X as its recommendation type, where the recommendation type is one of SELL, HOLD, BUY, and NONE. If there is an F-relationship between Q1 and Q2, the recommendation type of Q2 is decided immediately by that of Q1, therefore we can keep Q2 from being actually processed. To exploit this fact, we suggest two methods in this paper. The former analyzes all the F-relationships among user queries in the system and represents them as a graph. The latter searches the graph and decides the order of queries to be processed, which makes the number of unexecuted queries maximized. With these methods, a large portion of user queries are not actually processed. As a result, the performance of processing all the queries is greatly improved. We examined the superiority of the suggested methods through a variety of experiments using real-world stock market data. According to the results of our experiments, the overall time of continuous query processing with our proposed methods has reduced to less than 10% of that with the traditional method.

AB - This paper analyzes the properties of user queries in a system for stock investment recommendation, and defines the F-relationship, which is a new type of a relationship between two queries. A query is composed of user defined conditions for an interesting stock item and is systematically invoked whenever the price of that stock item is changed. An F-relationship between two queries Q1 and Q2 means that, if the recommendation type of a preceding query Q1 is X, then its following query Q2 always has X as its recommendation type, where the recommendation type is one of SELL, HOLD, BUY, and NONE. If there is an F-relationship between Q1 and Q2, the recommendation type of Q2 is decided immediately by that of Q1, therefore we can keep Q2 from being actually processed. To exploit this fact, we suggest two methods in this paper. The former analyzes all the F-relationships among user queries in the system and represents them as a graph. The latter searches the graph and decides the order of queries to be processed, which makes the number of unexecuted queries maximized. With these methods, a large portion of user queries are not actually processed. As a result, the performance of processing all the queries is greatly improved. We examined the superiority of the suggested methods through a variety of experiments using real-world stock market data. According to the results of our experiments, the overall time of continuous query processing with our proposed methods has reduced to less than 10% of that with the traditional method.

UR - http://www.scopus.com/inward/record.url?scp=85000415125&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85000415125&partnerID=8YFLogxK

U2 - 10.2298/CSIS141101042P

DO - 10.2298/CSIS141101042P

M3 - Article

AN - SCOPUS:85000415125

VL - 13

SP - 131

EP - 149

JO - Computer Science and Information Systems

JF - Computer Science and Information Systems

SN - 1820-0214

IS - 1

ER -