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 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.
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Keyword(in English) Time-Series Data Mining / GSP / Knowledge Acuiqisition / Daily Sales Report / SFA
Paper # AI2003-73
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Committee AI
Conference Date 2004/1/22(1days)
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Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
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
Date of Issue