Presentation | 2004/1/22 Sales Related Knowledge Acquisition by Time Series Co-occurrence Algorithm : Experimental Results with Daily Sales Reports Ken UENO, Shigeaki SAKURAI, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | It might be helpful to acquire time series sales activity knowledge from daily sales reports in order to plan the next sales action in time series. We implemented a time series knowledge extraction algorithm based on the algorithm Generalized Sequential Patterns (GSP), focusing on the time-series co-occurrences between events in sales reports. From the experimental results we found that frequent time series sequences with and without time duration on sales activities are successfully extracted. We also found that the processing time of the algorithm could be dependent on the average length of time series sequence data. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Time-Series Data Mining / GSP / Knowledge Acuiqisition / Daily Sales Report / SFA |
Paper # | AI2003-73 |
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Committee | AI |
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Conference Date | 2004/1/22(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Artificial Intelligence and Knowledge-Based Processing (AI) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Sales Related Knowledge Acquisition by Time Series Co-occurrence Algorithm : Experimental Results with Daily Sales Reports |
Sub Title (in English) | |
Keyword(1) | Time-Series Data Mining |
Keyword(2) | GSP |
Keyword(3) | Knowledge Acuiqisition |
Keyword(4) | Daily Sales Report |
Keyword(5) | SFA |
1st Author's Name | Ken UENO |
1st Author's Affiliation | Knowledge Media Laboratory, TOSHIBA CORPORATION() |
2nd Author's Name | Shigeaki SAKURAI |
2nd Author's Affiliation | Knowledge Media Laboratory, TOSHIBA CORPORATION |
Date | 2004/1/22 |
Paper # | AI2003-73 |
Volume (vol) | vol.103 |
Number (no) | 623 |
Page | pp.pp.- |
#Pages | 6 |
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