[1] Excel Excel... [3]. CSV RDF. [4] LinkedData. [5] LinkedData 1 RDF. OLAP. OLAP. [6] RDBMS. Excel CSV. CSV JSON RDF. Excel RDF. RDF RDF..
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1 DEIM Forum 2017 B4-4 Recognition and semantics interpretation of header hierarchies in statistical tables with complicated structures AI. AI. AI. Excel. Excel. Excel.. Excel. (appearance) Excel 1... Excel. 1 Excel Excel. Excel.. Excel Excel. Excel.. Excel. (appearance)
2 [1] Excel Excel... [3]. CSV RDF. [4] LinkedData. [5] LinkedData 1 RDF. OLAP. OLAP. [6] RDBMS. Excel CSV. CSV JSON RDF. Excel RDF. RDF RDF.. RDF 1. OLAP Kieninger [7].. [8] (CRF).. [9] HTML. HTML.. Excel HTML. Excel Excel. CSV. Excel CSV. 1. Excel... CSV Excel. Excel pdf. pdf Excel 1. ImageMagick 2 pdf. OCR. density 600. Excel. Excel
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3 1 1 cell no page 3 x x y y percentage x x percentage y y width height area normalized area lower left x x lower left y y upper right x x upper right y y lower right x x lower right y y text type. OpenCV Excel.. OCR. OCR tesseract Google Cloud Vision API 5.. tesseract OCR. Google Vision API tesseract., Google Vision API tesseract. tesseract tesseract GBDT Gradient Boosting Decision Tree. XGBoost [10] CSV. CSV ( ) 3 Excel.Excel
4 3 ( ) 4 ( ) ( ) Excel Population- -Both sexes Population- -Male Population- -Female Households- -Total Households- -Private-households Households- - -(a) x y x y (1) 8 (2) 9 (3) 7 x. 8 x Japan -Both sexes -Both sexes-a -Both sexes-a -I -Both sexes-a -I -(1) -Both sexes-a -I -(2)
5 -Both sexes-a -I -(3) -Both sexes-a -I -(4) Japan -Japan. 1 -Japan. 2 -Both sexes x 1 -Japan. -Both sexes. 3 A -Both sexes x. -Both sexes A. 4 I A x (1) Excel CSV.. Excel XGBoost. XGBoost eta( ) 0.3 max depth( ) 6 min child weight( ) 1 subsample() 1 colsample bytree( ) , ,600 11, ,271 84, ,676 41, XGBoost. 3.. Excel CSV CSV. 3 F 0.972(138/142) (138/142) (78/85) 0.940(78/83) (910/958) 0.960(910/ (10,909/11,102) 0.991(10,909/11,006) (84,129/84,512) 0.994(84,129/84,614) (164/180) 0.742(164/221) (40,509/41,034) 0.988(40,509/41,034) percentage x percentage y normalized area. 4 F percentage y 2,702 cell no 2,071 normalized area 1,830 width 1,523 percentage x 1, CRF( ). CRFSuit
6 ( ) N. N= IOB2. 5 IOB2 B TITLE I TITLE 2 B SUB TITLE I SUB TITLE 2 B COL HEADER I COL HEADER 2 B ROW HEADER I ROW HEADER 2 B BODY ( ) I BODY ( ) 2 B COMMENT I COMMENT IOB N=6 F. 6 N=6. F.. 6 N=6 F 0.854(94/110) 0.662(94/142) (37/49) 0.446(37/83) (686/741) 0.724(686/ (8,844/9,408) 0.803(8,844/11,006) (82,076/86,557) 0.970(82,076/84,614) (115/150) 0.520(115/221) CSV 14 Excel CSV 15. INCA OCR. Excel CSV OCR. Excel CSV OCR. OCR Google Cloud Vision API.. Excel OCR Google Cloud Vision API. TemplateMatching OCR Related member or more.
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7 . Related member A.. A (4). I Family nuclei 1. Excel. Excel Excel Excel CSV.. CSV OCR. OCR Google Cloud Vision API. OCR. pdf OCR... OCR Excel CSV.. [1] (2013) Excel okumura/sss2013.pdf (:2016/12/31) [2] (2015) -nsei/kaseguchikara/pdf/ pdf (:2016/1/7) [3] (2014) UNISYS TECHNOLOGY REVIEW 121 SEP [4] (2011) Linked Data The 25th Annual Conference of the Japanese Society for Artificial Intelligence 2011 [5] (2013) RDF 12 F-034 [6] (1996) RDB OLAP [7] T.G. Kieninger and B. Strieder(1999) T-Recs Table Recognition and Validation Approach AAAI Fall Symposium on Using Layout for the Generation Understanding and Retrieval of Documents. [8] (2015) DEIM Forum 2015 B4-5. [9] (2003) HTML. [10] Tianqi Chen Carlos Guestrin(2016) XGBoost: A Scalable Tree Boosting System (:2016/12/31)
8 図 14 Excel 統計表の例 図 15 CSV 化の例
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