Th詠c nghi羽m c嘘 8鵜nh chi 隠w"f k"ejw厩 ith 運i gian

Một phần của tài liệu Khai phá mẫu xu hướng tuần tự lên đối tượng từ tập dữ liệu chuỗi thời gian (Trang 82)

2. 305"Vt́pi"mj噂 p (Match)

5.4.2 Th詠c nghi羽m c嘘 8鵜nh chi 隠w"f k"ejw厩 ith 運i gian

Trong ph亥n th詠c nghi羽o"p {."vc"e嘘 8鵜nh chi隠w"f k"ejw厩i Length = 100. Ta l亥p"n逢嬰v"vjc{"8鰻k"ikƒ"vt鵜 min-sup b茨pi"7.8.9.:"x ";0"永ng v噂i m厩k"vt逢運ng h嬰r"vc"e pi"

uq"uƒpj"x "ijk"pj壱n th運i gian ch衣y c栄a c違 2 gi違i thu壱t Brute Î Hqteg"x "gi違i thu壱t d詠c"vt‒p"e医w"vt¿e"e¤{0"U嘘 n逢嬰pi"8嘘k"v逢嬰pi"e pi"8逢嬰e"v<pi"f亥n trong t瑛pi"vt逢運ng h嬰p t瑛 1 t噂i 5.

ạ Ch衣y v噂i m瓜t chu厩i th運i gian S&P500

D違pi"5.6 K院t qu違 khi ch衣y v噂i chu厩i th運k"ikcp"U(R722"x "ejk隠w"f k chu厩i th運i gian = 100

min_sup Motif# Pattern# BF-time Tree-time BF/Tree

5 40 201 319.8 97.1 3

6 27 76 169.9 54.9 3

7 18 33 80.2 28.5 3

8 11 17 39.5 14.6 3

9 6 7 14.9 6.5 2

J·pj"5.11 A欝 th鵜 bi吋u di宇n th運i gian ch衣y 泳ng v噂i chu厩i th運k"ikcp"U(R722"x " chi隠w"f k"ejw厩i th運i gian = 100

D違pi"5.7 K院t qu違 khi ch衣y v噂i 2 chu厩i th運k"ikcp"U(R722."DC"x "ejk隠w"f k" chu厩i th運i gian = 100

min_sup Motif# Pattern# BF-time Tree-time BF/Tree

5 60 964 1732.2 382.4 5

6 43 273 698.2 196.3 4

7 31 106 367.1 109.7 3

8 20 47 175.3 56.8 3

9 14 22 95.0 34.6 3

J·pj"5.12 A欝 th鵜 bi吋u di宇n th運i gian ch衣y 泳ng v噂i 2 chu厩i th運i gian S&P500, DC"x "ejk隠w"f k"ejw厩i th運i gian = 100

c. Ch衣y v噂i ba chu厩i th運k"ikcp"U(R722."DC"x "ECV

D違pi"5.8 K院t qu違 khi ch衣y v噂i 3 chu厩i th運i gian S&P500, BA, CAT x "ejk隠w"f k"ejw厩i th運i gian = 100

min_sup Motif# Pattern# BF-time Tree-time BF/Tree

5 100 2646 8248.6 1303.4 6

6 71 591 2222.7 574.2 4

7 51 223 1073.7 294.1 4

8 33 103 530.3 152.4 3

J·pj"5.13 A欝 th鵜 bi吋u di宇n th運i gian ch衣y 泳ng v噂i 3 chu厩i th運i gian S&P500, DC."ECV"x "ejk隠w"f k"ejw厩i th運i gian = 100

d. Ch衣y v噂i b嘘n chu厩i th運k"ikcp"U(R722."DC."ECV"x "EUZ

D違pi"5.9 K院t qu違 khi ch衣y v噂i 4 chu厩i th運k"ikcp"U(R722."DC."ECV."EUZ"x " chi隠w"f k"ejw厩i th運i gian = 100

min_sup Motif# Pattern# BF-time Tree-time BF/Tree

5 130 5394 19482.2 1976.2 10

6 94 1036 4628.6 1080.7 4

7 68 365 2075.9 546.6 4

8 43 160 972.4 270.7 4

9 30 67 519.9 145.9 4

J·pj"5.14 A欝 th鵜 bi吋u di宇n th運i gian ch衣y 泳ng v噂i 4 chu厩i th運i gian S&P500, DC."ECV."EUZ"x "ejk隠w"f k"ejw厩i th運i gian = 100

ẹ Ch衣y v噂k"p<o"ejw厩i th運k"ikcp"U(R722."DC."ECV."EUZ"x "FG

D違pi"5.10 K院t qu違 khi ch衣y v噂i 5 chu厩i th運i gian S&P500, BA, CAT, CSX, DE x "ejk隠w"f k"ejw厩i th運i gian = 100

min_sup Motif# Pattern# BF-time Tree-time BF/Tree

5 167 8943 69068.7 4600.9 15

6 122 1558 8985.9 1685.1 5

7 89 527 3713.1 880.8 4

8 58 223 1751.0 437.8 4

9 43 92 983.7 256.2 4

J·pj"5.15 A欝 th鵜 bi吋u di宇n th運i gian ch衣y 泳ng v噂i 5 chu厩i th運i gian S&P500, DC."ECV."EUZ."FG"x "ejk隠w"f k"ejw厩i th運i gian = 100

K院t qu違 th詠c nghi羽m trong 5 b違pi"vt‒p"ejq"vj医y r茨pi"vj»pi"swc"ik違i thu壱t d詠c"vt‒p"e医w"vt¿e"e¤{."ej逢挨pi"vt·pj"e„"vj吋 ik¿r"v<pi"v嘘e"swƒ"vt·pj"mjck"rjƒ"v瑛 3 t噂i 15 l亥p0"Vc"e pi"n逢w"#"t茨pi"mjk"ikƒ"vt鵜 min-sup e pi"n噂p"vj·"u嘘 n逢嬰ng 泳pi"xk‒p"8逢嬰c t衣q"tc"pi {"e pi" v"8k0"Ikƒ"vt鵜 min-sup l噂p"e pi"8欝pi"pij c"x噂i vi羽c m瓜t 泳pi"xk‒p" 8逢嬰c t衣o ra ch雨 e„"vj吋 8逢嬰e"zgo"n "rj鰻 bi院n n院w"p„"zw医t hi羽n v噂i t亥n s嘘 l噂p0"Ej pj" x·"x壱{"o "u嘘 m磯u ph鰻 bi院p"mjck"rjƒ"8逢嬰e"e pi"ik違m d亥n theo chi隠w"v<pi"e栄a min- sup.

5.4.3 Th詠c hi羽n ki吋m tra s嘘 l逢嬰ng k院t h嬰r"8逢嬰e"{‒w"e亥u t衣o ra

Lu壱p"x<p"e pi"vk院p"j pj"uq"uƒpj"v鰻ng s嘘 n逢嬰ng k院t h嬰p 8逢嬰e"{‒w"e亥u t衣o ra cho Ck t瑛 Lk-1 o "jck"ik違i thu壱v"8«"i丑i trong su嘘v"swƒ"vt·pj"mjck"rjƒ0"Eƒe"d違ng k院t qu違 s胤ejq"ej¿pi"vc"vj医y t鰻ng s嘘n逢嬰ng k院t h嬰p c栄a gi違i thu壱t d詠a vt‒p"e医w"vt¿e"e¤{"-

Tree Combination Function Calls (Tree- EHE+" n " v" j挨p" uq" x噂i gi違i thu壱t Brute- Force (BF-CFC).

B違ng 5.11 s胤 th吋 hi羽n t鰻ng s嘘n逢嬰pi"rjfir k院t h嬰p c栄a t瑛ng gi違i thu壱t v噂k"eƒe" vj»pi"u嘘8亥w"x q"v逢挨pi"v詠pj逢"o映c 5.4.1 (c嘘8鵜nh min_sup = 5)

D違pi"5.11 Uq"uƒpj"v鰻ng s嘘n逢嬰ng k院t h嬰r"8逢嬰e"{‒w"e亥u t衣o ra t瑛 hai gi違i thu壱t

Time series

Length Motif# Pattern# BF-CFC Tree- CFC BF/Tree S&P500 20 0 0 40 4 0 325 280 1 60 14 9 4322 3635 1 80 26 92 18841 14585 1 100 40 201 52814 39887 1 S&P500, Boeing 20 0 0 40 7 4 1089 821 1 60 22 49 12363 9659 1 80 42 356 69524 42690 1 100 60 964 234731 108026 2 S&P500, Boeing, CAT 20 1 0 10 6 1 40 9 12 2120 1477 1 60 35 184 37940 25432 2 80 72 850 248850 124296 2 100 100 2646 1110838 322215 3 S&P500, Boeing, CAT, CSX 20 2 0 45 28 2 40 14 14 4394 3247 2 60 48 292 70976 46052 2 80 95 1821 654827 223493 3 100 130 5394 3425875 572419 6 S&P500, Boeing, CAT, CSX, DE 20 2 0 45 28 2 40 20 16 8664 6523 1 60 62 451 124109 76411 2 80 116 3375 1462348 353637 4 100 167 8943 7594717 997459 8 B違ng 5.12. s胤 th吋 hi羽n t鰻ng s嘘 n逢嬰ng k院t h嬰p c栄a t瑛ng gi違i thu壱t v噂k" eƒe" vj»pi"u嘘 8亥w"x q"v逢挨pi"v詠 pj逢"o映c 5.4.2 (c嘘 8鵜pj"vkog"ugtkgu"ngpivj"?"322"x "8鰻i min-sup)

D違pi"5.12 Uq"uƒpj"v鰻ng s嘘n逢嬰ng k院t h嬰p gi英a hai gi違i thu壱t

Time series

min_sup Motif# Pattern# BF-time Tree- time BF/Tree S&P500 5 40 201 52814 39887 1 6 27 76 29061 22423 1 7 18 33 16529 12080 1 8 11 17 8545 5625 2 9 6 7 4011 2210 2 S&P500, Boeing 5 60 964 234731 108026 2 6 43 273 95446 63246 1 7 31 106 55205 37646 2 8 20 47 30201 18953 2 9 14 22 18863 10754 2 S&P500, Boeing, CAT 5 100 2646 1110838 322215 3 6 71 591 291584 176527 2 7 51 223 154807 102291 2 8 33 103 82678 51751 2 9 24 45 51917 30549 2 S&P500, Boeing, CAT, CSX 5 130 5394 3425875 572419 6 6 94 1036 580370 307893 6 7 68 365 282326 179793 2 8 43 160 142031 87018 2 9 30 67 83085 47970 2 S&P500, Boeing, CAT, CSX, DE 5 167 8943 7597862 997459 8 6 122 1558 1063560 527015 2 7 89 527 497156 311257 2 8 58 223 255860 157503 2 9 43 92 159943 95401 2

5.4.4Th詠c hi羽n ki吋m tra s嘘泳pi"xk‒p"e栄a hai gi違i thu壱t

Lu壱p"x<p"vk院p"j pj"uq"uƒpj"v鰻ng 泳pi"xk‒p"Ek荏 t医t c違eƒe"o泳c c栄a t瑛ng gi違i thu壱t. B違ng 5.13 s胤 th吋 hi羽n t鰻ng s嘘泳pi"xk‒p"e栄a t瑛ng gi違i thu壱t v噂k"eƒe"vj»pi"u嘘 8亥w"x q"v逢挨pi"v詠pj逢"o映c 5.4.1 (c嘘8鵜nh min_sup = 5).

D違pi"5.13 Uq"uƒpj"v鰻ng s嘘泳pi"xk‒p"8逢嬰c t衣o gi英a hai gi違i thu壱t

Time series

Length Motif# Pattern# BF- Candidates Tree- Candidates BF/Tree S&P500 20 0 0 0 0 40 4 0 217 217 1 60 14 9 3052 3052 1 80 26 92 11851 11851 1

100 40 201 32959 32959 1 S&P500, Boeing 20 0 0 0 0 40 7 4 723 723 1 60 22 49 8467 8467 1 80 42 356 35680 35680 1 100 60 964 88600 88600 1 S&P500, Boeing, CAT 20 1 0 0 0 40 9 12 1324 1324 1 60 35 184 21889 21889 1 80 72 850 103442 103442 1 100 100 2646 251370 251370 1 S&P500, Boeing, CAT, CSX 20 2 0 22 22 1 40 14 14 3027 3027 1 60 48 292 40463 40463 1 80 95 1821 185259 185259 1 100 130 5394 432304 432304 1 S&P500, Boeing, CAT, CSX, DE 20 2 0 22 22 1 40 20 16 6161 6161 1 60 62 451 67960 67960 1 80 116 3375 289470 289470 1 100 167 8943 733221 733221 1

T瑛 b違pi"vj»pi"vkp"vt‒p."vc"vj医y r茨ng s嘘 泳pi"xk‒p"8逢嬰c t衣o ra b荏i 2 gi違i thu壱t

n "jq p"vq p"ik嘘ng nhaụ Gi違i thu壱t theo c医w"vt¿e"e¤{"e„"v嘘e"8瓜 x穎 n#"pjcpj"j挨p"uq"

v噂i gi違i thu壱v"Dtwvg"Hqteg"n "pj運 gi違m b噂v"8逢嬰c s嘘 l亥n g丑k"rjfir"m院t h嬰p. Pij c"n " épi"o瓜t k院t qu違 s嘘 n逢嬰ng 泳pi"xk‒p"e pi"pj逢"u嘘 n逢嬰ng m磯u ph鰻 bi院p"pj逢"pjcw."

gi違i thu壱t d詠c"vt‒p"e医w"vt¿e"e¤{"u胤 s穎 d映pi" v"n羽nh t衣o k院t h嬰r"j挨p"uq"x噂i gi違i thu壱t Brute Force (xem k院t qu違 t瑛 m映c 5.4.3).

5.5 K院t qu違

K院t qu違 c栄c"vq p"d瓜swƒ"vt·pj"mjck"rjƒ"n "eƒe"o磯w"zw"j逢噂ng tu亥n t詠nk‒p"8嘘i

v逢嬰pi"vt‒p"f英 li羽u chu厩i th運k"ikcp0"Eƒe"o磯w"p {"e„"vj吋 8逢嬰e"n逢w"vt英vtqpi"e挨"u荏 d英

li羽u ho員c trong m瓜v"hkng"x<p"d違p0"J·pj 5.16 ucw"o»"v違 m瓜t s嘘 m磯u ph鰻 bi院n n茨m trong t壱p k院t qu違8逢嬰e"mjck"rjƒ"x噂k"eƒe"vj»pi"u嘘 sau:

-S嘘 c鰻 phi院u: 5 (S&P500, Boeing, DE, CAT, CSX)

-Chi隠w"f k"ejw厩i: 365

-min-sup: 15

-S嘘 pattern: 175571

J·pj"5.16 Minh h丑c"eƒe"o磯w"zw"j逢噂ng tu亥n t詠nk‒p"8嘘k"v逢嬰pi"8逢嬰e"v·o"tc (泳ng v噂k"7"8嘘k"v逢嬰pi"n "UPR722."ECV."FG."EUZ."Dqgkpi+

T瑛 t壱r"eƒe"o磯u ph鰻 bi院n 荏 vt‒p."vc"d逸v"8亥u ch丑n l丑c ra nh英ng m磯w"e„"v亥n s嘘

xu医t hi羽n cao nh医t ho員c nh英ng m磯w"nk‒p"j羽 tr詠c ti院p v噂k"8嘘k"v逢嬰pi"vc"swcp"v¤o"pj医t.

雲 8¤{ ta th穎 zfiv"o磯u s嘘 1: EE-CAT<p:59>BB-DẸ M磯w"p {"ejq"vj医y m嘘i quan h羽

ph鰻 bi院n gi英a 2 c鰻 phi院w"n "ECV"x "FG0"Vj»pi"vkp"e栄a m磯w"e„"8逢嬰e"n "v瑛 s詠 k院t h嬰p gi英a 2 chu厩i s詠 ki羽p"Ðik違m m衣pj"ucw"jck"rjk‒p"nk‒p"v映eÑ"e栄c"8嘘k"v逢嬰ng c鰻 phi院u

ECV"x "Ðv<pi"o衣pj"ucw"jck"rjk‒p"nk‒p"v映eÑ"e栄a DẸ S詠 ki羽n c鰻 phi院u CAT gi違m m衣pj"ucw"4"rjk‒p"nk‒p"v映c r欝k"ucw"8„ 7;"pi { c鰻 phi院w"FG"e„"mjw{pj"j逢噂pi"v<pi"

m衣pj"ucw"jck"rjk‒p"nk‒p"v映e"n "o瓜t trong nh英ng s詠 ki羽n n鰻i b壱t e„"v pj"ej医t l員r"8k"

l員p l衣ị T瑛 m磯u ph鰻 bi院p"vt‒p."pj "rj¤p"v ej"vj医{"8逢嬰c m嘘i quan h羽 gi英a 2 lo衣i c鰻

phi院w"ECV"x "FG."pij c"n "o嘘i quan h羽 nk‒p"8嘘k"v逢嬰ng t瑛 t壱r"eƒe"ejw厩i th運i gian

mjƒe"pjcw. Vi羽e"vt ej"zw医t ra nh英ng m磯u ph鰻 bi院p"pj逢"vj院 s胤ik¿r"pi逢運k"f́pi"vk院t ki羽o"8逢嬰c r医t nhi隠u th運i gian vtqpi"swƒ"vt·pj v·o"tc"pj英ng vj»pi"vkp"vk隠m 育n. D衣ng

vj»pi"vkp"e„"8逢嬰c s胤 n "vk隠p"8隠 ejq"eƒe"swƒ"vt·pj"rj¤p"v ej"u¤w"j挨p0"Vj»pi"swc"m "

thu壱v"t¿v"vt ej"nw壱t ho員e"eƒe"m "vjw壱v"rj¤p"v ej"f英 li羽w"mjƒe"f詠c"vt‒p"eƒe"o磯u ph鰻

j逢荏ng l磯n nhau th壱t s詠 jc{"mj»pi"*pj逢"泳ng v噂i m磯w"3"vc"e„"vj吋 bi院v"8逢嬰c li羽u c鰻

phi院w"ECV"e„"rj違k"n "e鰻 phi院u d磯n d逸v"FG"jc{"mj»pi+0"

""pij c<"v瑛 nh英ng m磯w"mjck"rjƒ."pj "rj¤p"v ej"u胤 e„"8逢嬰c m瓜t b瓜vj»pi"vkp" ej pj"zƒe th吋 hi羽n m嘘i quan h羽 ph鰻 bi院p"nk‒p"8嘘k"v逢嬰ng. T瑛 nh英pi"vj»pi"vkp"p {." pi逢運k"f́pi"e„"vj吋 u pi"n丑c ho員c l詠a ch丑p"tc"eƒe"o磯w"rj́"j嬰p v噂i n瓜k"fwpi"o "j丑 swcp"v¤o0"Eƒe"o磯w"v·o"tc"n "8亥w"x q"ejq"swƒ"vt·pj"rj¤p"v ej"pi英 pij c"jq員e"t¿v" vt ej"nw壱t v隠 saụ

5.6 Aƒpj"ikƒ"ejwpi

Gi違i thu壱t Brute Î Force 荏 8¤{"8逢嬰e"8„pi"xck"vt”"n "ik違i thu壱v"e挨"u荏 (base

nkpg+"ejq"eƒe"ik違i thu壱v"mjƒe0"Fq"8„"xk羽e"uq"uƒpj"ik違i thu壱t d詠c"vt‒p"e医w"vt¿e"e¤{"x噂i gi違i thu壱t Brute-Force s胤ik¿r"vc"mk吋o"vtc"8逢嬰e"v pj"8¿pi"8逸n c栄a gi違i thu壱t d詠c"vt‒p"

c医w"vt¿e"e¤{"vj»piswc"swƒ"vt·pj"8嘘i chi院u t壱p k院t qu違vjw"8逢嬰c c栄a hai gi違i thu壱t. M瓜v"eƒej"v鰻pi"swƒv."ik違i thu壱t d詠c"vt‒p"e医w"vt¿e"e¤{"e„"vj運i gian th詠c thi t嘘t

j挨p"uq"x噂i gi違i thu壱t Brute-Forcẹ K院t lu壱p"p {"e pi"ej pj"zƒe"mjk"u嘘n逢嬰ng ph亥n t穎 荏 m泳c L1 l噂p0"N#"fq"ej pj"n "ik違i thu壱t d詠c"vt‒p"e医w"vt¿e"e¤{"v壱n d映pi"8逢嬰c quy t逸c k院t h嬰p gi英c"eƒe"rj亥n t穎 trong t壱p Lk-1 khi sinh ra 泳pi"xk‒p"Ek pj逢"8«"v瑛pi"vt·pj"d {" 荏 m映e"605040"Vj»pi"swc"sw{"v逸e"p {."u嘘 n逢嬰pi"rjfir"m院t h嬰p 荏 gi違i thu壱t d詠c"vt‒p"

c医w" vt¿e" e¤{" v" j挨p" j鰯n so v噂i s嘘 rjfir" m院t h嬰r" 8逢嬰c g丑i trong gi違i thu壱t Brute- Forcẹ

A隠 v k"mj»pi"u穎 d映pi"vj»pi"u嘘 max-span x·"o映e"8 ej"ej pj"e栄c"8隠 v k"n "e„"

th吋v·o"vj医y t医t c違eƒe"o磯w"o "mj»pi"ik噂i h衣n th運i kho違ng gi英c"eƒe"u詠 ki羽n.

Pj逢嬰e"8k吋m c栄a c違 hai gi違i thu壱v"vt‒p"n "mjk"ejk隠w"f k"ejw厩k"swƒ"n噂n ho員c min-sup swƒ"pj臼 vj·"mj»pi"ikcp"n逢w"vt英 s胤 r医v"jcq"rj 0"Vtqpi"vj詠c t院, vi羽e"zƒe"8鵜nh ch雨 s嘘 min-sup ucq"ejq"rj́"j嬰p v噂i chi隠w"f k"ejw厩i th運k"ikcp"8亥w"x q"e pi"8„pi"

m瓜v"xck"vt”"swcp"vr丑pi0"Swcp"uƒv"vtqpi"vj詠c t院, ta th医y r茨ng n院w"f”pi"vj運k"ikcp"e pi" f k"vj·"o瓜t s詠 ki羽n ch雨 e„"#"pij c"mjk"e„"v亥n s嘘 xu医t hi羽p"8栄 l噂n.

EJ姶愛PI"8 : KT LUN 6.1 T鰻ng k院t

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pijk‒p"e泳w"u¤w"j挨p"8吋 v壱n d映ng k院t qu違 p {"x q"swƒ"vt·pj"mjck"rjƒ"nw壱t ho員e"rj¤p" v ej"pi英pij c"e栄c"eƒe"o嘘i quan h羽. T瑛8„."vc"u胤 e„"o瓜v"i„e"pj·p"ej pj"zƒe"j挨p"x隠 #" pij c" e栄a s詠 vƒe" 8瓜ng qua l衣i gi英c" eƒe" 8嘘k" v逢嬰pi" e pi" pj逢" 違pj" j逢荏ng t瑛 o»k" vt逢運ng xung quapj"n‒p"j pj"xk"e栄c"eƒe"8嘘k"v逢嬰pi"8„0

VÉK"NK烏U THAM KHO

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Lodon,.

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]:̲"Ejcmtcdctvk."M0."Mgqij."G0."Rc¦¦cpk."O0."Ogjtqvtc."*4224+."ÐU0"Nqecnn{"cfcrvkxg"

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]32̲" Rqrkxcpqx." K0." Oknngt." T0" L" *4224+." ÐUkoknctkv{" ugctej" qxgt" vkog" ugtkgu" fcvc" wukpi"ycxgngvuÑ."In proceedings of the 18th KpvÓn"Eqphgtgpeg"qp"Fcvc"Gpikpggtkpi, 2002 Feb 26-Mar 1; San Jose, CA, pp 212-221.

]33̲"Ccej."L0"cpf"Ejwtej0I"*4223+."ÐCnkipkpi"igpg"gzrtguukqp"vkog"ugtkgu"ykvj"vkog" yctrkpi"cniqtkvjouÑ."Bioinformatics; 2001, Volume 17, pp. 495-508.

]34̲"Mcnrcmkụ"M0."Icfc."F0."Rwvvciwpvc."X"*4223+."ÐFkuvcpeg"ogcuwtgu"hqt"ghhgevkxg"

clustering of ARIMA time-ugtkguÑ."Rtqeggfkpiu" qh" vjg" KGGG" KpvÓn" Eqphgtgpeg" qp"

Data Mining, 2001 Nov 29-Dec 2, San Jose, CA, pp 273-280.

]35̲" Mgqij." G0." Rc¦¦cpk." O" *3;;:+." ÐCp" gpjcpegf" tgrtgugpvcvkqp" qh" vkog" ugtkgu" yjkej" cnnqyu" hcuv" cpf" ceewtcvg" encuukÝecvkqp." enwuvgtkpi" cpf" tgngxcpeg" hggfdcemÑ."

Rtqeggfkpiu" qh" vjg" 6vj" KpvÓn" Eqphgtgpeg" qp" Mpqyngfig" Fkueqxgt{" cpf" Fcvc"

Mining,1998 Aug 27-31, New York, NY, pp 239-241.

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]37̲"Iwtcnpkm."X0."Utkxcuvcxc."L"*3;;;+."ÐGxgpv"fgvgevkqp"htqo"vkog"ugtkgu"fcvcÑ0"In

rtqeggfkpiu" qh" vjg" 7vj" CEO" UKIMFF" KpvÓn" Eqphgtgpeg" qp" Mpqyngfig" Fkueqxgt{

]38̲"Mgqij."G"*4224+."ÐGzcev"kpfgzkpi"qh"f{pcoke"vkog"yctrkpiÑ."In Proceedings of 28th Internation Conference on Very Large Databases, 2002, Hong Kong, pp. 406-417.

]39̲"R0Rcvgn."G0Mgqij."Lguukec"Nkp"x "U0Nqpctfk"*4224+."ÐOkpkpi"Oqvkhu"kp"Ocuukxg" Vkog"Ugtkgu"FcvcdcuguÑ."In Proceedings of IEEE International Conference on Data Mining (ICDM 02), pp 370-377.

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[20̲"[qqp."L0R0."Nwq."[0."Pcọ"L"*4223+."ÐC"Dkvocr"Crrtqcej"vq"Vtgpf"Enwuvgtkpi"

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[21̲"[0Vcpcmc"x "M0Wgjctc"*4225+."ÐFkueqxgt"Oqvkhu"kp"Ownvk"Fkogpukqpcn"Vkog" Ugtkgu"Wukpi"vjg"Rtkpekrcn"Eqorqpgpv"Cpcn{uku"cpf"vjg"OFN"RtkpekrngÑ."Machine Learning and Data Mining in Pattern Recognition Lecture Notes in Computer Science Volume 2734, 2003, pp 252-265.

[22̲" Knfct" Dcv{tujkp." Ngqpkf" Ujgtgogvqx" x " Tcwn" Jgttgtc-Avelar (2007),

ÐRgtegrvkqp" Dcugf" Vkog" Ugtkgu" Fcvc" Okpkpi" hqt" Fgekukqp" OcmkpiÑ."Perception- based Data Mining and Decision Making in Economics and Finance vol 36, Springer Berlin Heidelberg Publisher, pp 85-118.

[23̲"Gcoqpp"Mgqij"cpf"Rcfjtcke"Uo{vj"*3;;9+."ÐC"Rtqdcdknkuvke"Crrtqcej"vq"Hcuv" Rcvvgtp"Ocvejkpi"kp"Vkog"Ugtkgu"FcvcdcuguÑ."Proceedings of the Third International Conference on Knowledge Discovery and Data Mining (KĐ-97), Newport Beach, California, USA, August 14-17, 1997, pp 24-30.

[24̲" Ugdcuvkcp" NØwjt." Igqhh" Yguv" x " Uxgvjc" Xgpmcvguj" *4227+." ÐCp" Gzvgpfgf" Htgswgpv" Rcvvgtp" Vtgg" hqt" Kpvgtvtcpucevkqp" Cuuqekcvkqp" Twng" OkpkpiÑ." "Technical Report TR-2005/1, Department of Computing, Curtin University of Technologỵ

[25̲" J0Nw." L0Jcp" x " Nkpi" Hgpi" *3;;:+." ÐUvqem" Oqxgogpv" Rtgfkevkqp" cpf" P- Dimensional Inter -Vtcpucevkqp" Cuuqekcvkqp" TwnguÑ."In Proceedings of the ACM SIGMOD Workshop on Research Issues on Data Mining and Knowledge Discovery, Seattle, Washington, June 1998, pp. 12:1Î12:7.

[26̲"E0Y0"Ejq."[0J0"Yw."L0"Nkw."cpf"C0N0R0"Ejgp."Fgegodgt"*4224+."ÐC"Itcrj-

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