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 language | English |
|---|---|
| Pages (from-to) | 131-149 |
| Number of pages | 19 |
| Journal | Computer Science and Information Systems |
| Volume | 13 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2016 Jan |
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All Science Journal Classification (ASJC) codes
- Computer Science(all)
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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 journal › Article
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 -