Data analysis method and data analysis device

Patent metadata

Field	Value
Publication number	US-2021390623-A1
Application number	US-202117330411-A
Country	US
Kind code	A1
Filing date	May 26, 2021
Priority date	Jun 10, 2020
Publication date	Dec 16, 2021
Grant date	—

Abstract

A non-transitory computer-readable recording medium has stored therein a program that causes a computer to execute a process, the process including determining numerical values indicating features at respective timings having a predetermined time interval with respect to time-series data to be analyzed, numbers of the numerical values at the respective timings being made same, and generating an attractor related to the time-series data based on the determined numerical values.

First claim

What is claimed is:

1 . A non-transitory computer-readable recording medium having stored therein a program that causes a computer to execute a process, the process comprising:
determining numerical values indicating features at respective timings having a predetermined time interval with respect to time-series data to be analyzed, numbers of the numerical values at the respective timings being made same; and generating an attractor related to the time-series data based on the determined numerical values.

2 . The non-transitory computer-readable recording medium according to claim 1 , the process further comprising:
determining numerical values of a highest point and a lowest point included in the time-series data within time intervals corresponding to the respective timings and numerical values of interpolation points between the highest point and the lowest point, numbers of the interpolation points at the respective timings being made same.

3 . The non-transitory computer-readable recording medium according to claim 2 , the process further comprising:
determining the numerical values of the interpolation points by equally dividing between the highest point and the lowest point.

4 . The non-transitory computer-readable recording medium according to claim 2 , the process further comprising:
determining measured values included in the time-series data within the time intervals corresponding to the respective timings, as the numerical values of the interpolation points.

5 . The non-transitory computer-readable recording medium according to claim 1 , wherein
the time-series data are data that indicate a change in stock price over time, and the process further comprises: determining a high price and a low price of the stock price within time intervals corresponding to the respective timings and the numerical values of interpolation points between the high price and the low price, numbers of the interpolation points at the respective timings being made same.

6 . A data analysis method, comprising:
determining, by a computer, numerical values indicating features at respective timings having a predetermined time interval with respect to time-series data to be analyzed, numbers of the numerical values at the respective timings being made same; and generating an attractor related to the time-series data based on the determined numerical values.

7 . The data analysis method according to claim 6 , further comprising:
determining numerical values of a highest point and a lowest point included in the time-series data within time intervals corresponding to the respective timings and numerical values of interpolation points between the highest point and the lowest point, numbers of the interpolation points at the respective timings being made same.

8 . The data analysis method according to claim 7 , further comprising:
determining the numerical values of the interpolation points by equally dividing between the highest point and the lowest point.

9 . The data analysis method according to claim 7 , further comprising:
determining measured values included in the time-series data within the time intervals corresponding to the respective timings, as the numerical values of the interpolation points.

10 . The data analysis method according to claim 6 , wherein
the time-series data are data that indicate a change in stock price over time, and the data analysis method further comprises: determining a high price and a low price of the stock price within time intervals corresponding to the respective timings and the numerical values of interpolation points between the high price and the low price, numbers of the interpolation points at the respective timings being made same.

11 . A data analysis device, comprising:
a memory; and a processor coupled to the memory and the processor configured to: determine numerical values indicating features at respective timings having a predetermined time interval with respect to time-series data to be analyzed, numbers of the numerical values at the respective timings being made same; and generate an attractor related to the time-series data based on the determined numerical values.

12 . The data analysis device according to claim 11 , wherein
the processor is further configured to determine numerical values of a highest point and a lowest point included in the time-series data within time intervals corresponding to the respective timings and numerical values of interpolation points between the highest point and the lowest point, numbers of the interpolation points at the respective timings being made same.

13 . The data analysis device according to claim 12 , wherein
the processor is further configured to determine the numerical values of the interpolation points by equally dividing between the highest point and the lowest point.

14 . The data analysis device according to claim 12 , wherein
the processor is further configured to determine measured values included in the time-series data within the time intervals corresponding to the respective timings, as the numerical values of the interpolation points.

15 . The data analysis device according to claim 11 , wherein
the time-series data are data that indicate a change in stock price over time, and the processor is further configured to determine a high price and a low price of the stock price within time intervals corresponding to the respective timings and the numerical values of interpolation points between the high price and the low price, numbers of the interpolation points at the respective timings being made same.

Assignees

• Fujitsu Ltd

Inventors

• Todoriki Masaru
• Umeda Yuhei
• Kobayashi Ken
• Maruhashi Koji

Classifications

• G06F2218/10

  by analysing the shape of a waveform, e.g. extracting parameters relating to peaks · CPC title

• G06F2218/08

  Feature extraction · CPC title

• G06F18/213

  Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods · CPC title

• G06Q40/06 Primary

  Asset management; Financial planning or analysis · CPC title

• G06Q30/0201 Primary

  Market modelling; Market analysis; Collecting market data · CPC title