Hình 3.3 BiӇXÿӗ bong bóng vӅ ÿLӇPFӫDsinh viên khoa BD 18 Hình 3.4 BiӇXÿӗ bong bóng vӅ ÿLӇPFӫDsinh viên khoa CK 18 Hình 3.5 BiӇXÿӗ bong bóng vӅ ÿLӇPFӫDsinh viên khoa DD 18 Hình 3.6 BiӇXÿ
Trang 1ĈҤ,+Ӑ&48Ӕ&*,$73HCM
Trang 2MÔ HÌNH DӴ%ÁO ӂ748Ҧ+Ӑ&7Ұ36,1+9,Ç1
LUҰN VĂN THҤ&6Ƭ
Trang 3&Ð1*75Î1+ĈѬӦ&+2¬17+¬1+7Ҥ, 75ѬӠ1*ĈҤ,+Ӑ&%È&+KHOA ±Ĉ+4*-HCM
&+Ӫ7ӎ&++Ӝ,ĈӖ1* 75ѬӢ1*.+2$ KH&KTMT
Trang 4ĈҤ,+Ӑ&48Ӕ&*,$73+&0
75ѬӠ1*ĈҤ,+Ӑ&%È&+.+2$
&Ӝ1*+Ñ$;+Ӝ,&+Ӫ1GHƬ$9,ӊ71$0
ĈӝFOұS- 7ӵGR- +ҥQKSK~F
1+,ӊ09Ө/8Ұ19Ă17+Ҥ&6Ƭ +ӑWrQKӑFYLrQ TRҪ17+ӎ7+875$1* MSHV : 1670471 1Jj\WKiQJQăPVLQK 01/06/1982 Nѫi sinh: TPHCM Chuyên ngành: HӋWKӕQJWKông tin quҧQOý 0mVӕ : 60.34.04.05 I TÊ1Ĉӄ7¬, Áp dөQJNӻ thuұWJӧLý xây dӵQJPô hình dӵEáo kӃWTXҧKӑFWұSVLQKYLên (tên tiӃQJ $QK : Applying Recommender Systems for Predicting Student Performance) I N+,ӊ09Ө9¬1ӜI DUNG:
-
-II N*¬<*,$21+,ӊ09Ө : (GKLWKHRWURQJ4ĈJLDRÿӅWjL «««««
III NGÀY HOÀ17+¬1+1+,ӊ09Ө: (*KLWKHRWURQJ4ĈJLDRÿӅWjL «
IV &È1%Ӝ+ѬӞ1*'Ү1 Ghi rõ hӑFKjPKӑFYӏKӑWrQ
PGS.TS ThRҥi Nam
Tp HCM, ngày tháng 8 QăP.
&È1%͠+˰͢1*'̲1
+ӑWrQYjFKӳNê
&+ͮ1+,͎0%͠0Ð1Ĉ¬27̨2
(HӑWrQYjFKӳNê
75˰ͦ1*.+2$.+&KTMT
+ӑWrQYjFKӳNê
Trang 5/Ӡ,&Ҧ0Ѫ1
9ӟL OzQJ ELӃW ѫn sâu VҳF QKҩW, em xiQ JӱL ÿӃQ FiF 7Kҫ\ &{ NKRD.KRDKӑFvà ӻWKXұWMi\WtQKWUѭӡQJĈҥLKӑF%iFK.KRD73+&0ÿmKӃWOzQJFKӍGҥ\WUDQJEӏFKRHPNLӃQWKӭFQӅQWҧQJEәtFKcùng YӟLVӵKӛWUӧFӫDJLDÿuQKÿmWҥRÿLӅXNLӋQÿӝQJYLrQӫQJKӝHPWURQJTXiWUìnKKӑFWұSWҥi WUѭӡQg
ĈһFELӋWHP[LQFKkQWKjQKFҧPѫQ3*6767KRҥL1DP ÿmWұQWkP
KѭӟQJ GүQ ÿӝQJ YLrQ WUX\ӅQ ÿҥW QKLӅX NLӃQ WKӭF NLQK QJKLӋP TXê EiXgi~SHPWKӵFKLӋQOXұQYăQQj\
0һFGÿmFyQKLӅXFӕJҳQJQKѭQJOXұQYăQVӁNK{QJWKӇWUiQKkhӓLnKӳQJWKLӃu sót, FKѭDKRjQWKLӋQHPUҩWPRQJQKұQÿѭӧFQKӳQJêNLӃQÿyQJJyS TXê EiX FӫD TXê 7Kҫ\ &{ ÿӇ HP U~W NLQK QJKLӋP WtFK ONJ\ NLӃQ WKӭFWURQJOƭQKYӵFQj\ÿѭӧFKRjQWKLӋQKѫQ
6DXFQJHP[LQNtQKFK~FTXê7Kҫ\ Cô FQJJLDÿuQKGӗLGjRVӭFkhӓH, luôn thành công trRQJVӵQJKLӋSYjFXӝFVӕQJ
Trang 67Ï07Ҳ7
HӋWKӕQJgӧLý OjPӝWWURQJQKӳQJӭQJGөQJSKәELӃQQKҩWFӫDNKRDKӑFGӳOLӋXKLӋQQD\ÿһFELӋWOjNKDi phá GӳOLӋXJLiRGөF+Ӌ WKӕQJgӧLý ÿѭӧFWtFKKӧSYjRFiFKӋWKӕQJWUӵFWX\ӃQ ÿӇWӵÿӝQJ phân tícKGӳOLӋXWURQJTXiNKӭvà GӵÿRiQNӃWTXҧFKRQJѭӡLGQJ
0өF WLrX OXұQ iQ FӫD W{L Oj QJKLrQ FӭX Yj iS GөQJ FKR FiF KӋ WKӕQJNKX\ӃQQJKӏÿӇGӵÿRiQNӃWTXҧKӑFWұSFӫDVLQKYLrQWUѭӡQJĈҥLKӑF%iFKKhoa - Ĉ+4*- TPHCM 9ӟLYLӋc ánh xҥGӳOLӋXJLiRGөFÿӇWLӃSFұQFiFKӋWKӕQJgӧLý OjFiFSKѭѫQJSKiSOӑFFӝQJWiFOӑFGӵDWUrQsӵWѭѫQJÿӗQJgiӳDPôn hӑc-sinh viên và sinh viên-sinh viên YӟLFiFP{KuQK\ӃXWӕWLӅPҭQ3KѭѫQJSKiSQj\GӵÿRiQFiF[ӃSKҥQJ tiӅPҭQEҵQJ FiFKVӱGөQJVӵWѭѫQJÿӗQJJLӳDFiFVLQKYLrQWURQJFQJPӝWNKRDYj các môn hӑFÿӇÿӅ[XҩWnhӳQJP{QKӑFWLӃSWKHRFKRVLQKYLrQ %rQFҥQKÿyOXұQiQÿmWUuQKEj\FiFWUѭӡQJKӧSTiӅQ[ӱOý GӳOLӋXNKiFQKDXiSGөQJFKRFiFWKXұWWRiQNKiFQKDXÿӇJLiWUӏVDLVӕthҩSQKҩWYjWuPUDJLҧLSKiSSKKӧSFKRWұSGӳOLӋXQj\.ӃWTXҧWKӵFQJKLӋPFKRWKҩ\WKXұWWRiQ%DVHOLQHB6*'YӟLJLiWUӏ0$(FyÿӝFKtQK[iFGӵEiRWӕWKѫQFiFWKXұWWRiQNKiF
Trang 7accuracy better than others
Trang 8/ӠI CA0Ĉ2$1
Tôi xin cam ÿRDQOXұQYăQ³Áp dөQJNӻWKXұWJӧLý xây dӵQJPô hình dӵEáo kӃWTXҧKӑFWұSVLQKYLên´ là nghiên cӭXFӫDULêng tôi Các sӕOLӋX, tài liӋX sӱGөQJWURQJOXұQYăQOà trung thӵFTҩWFҧQKӳQJtài liӋXtham khҧR, kӃWKӯDÿӅXÿѭӧFWrích dүn và tham chiӃXÿҫ\ÿӫ
Trang 9
0Ө&/Ө&
/Ӡ,&Ҧ0Ѫ1 i
7Ï07Ҳ7 ii
ABSTRACT iii
/Ӡ,&$0Ĉ2$1 iv
0Ө&/Ө& v
'$1+0Ө&7Ӯ9,ӂ77Ҳ7 viii
'$1+0Ө&%Ҧ1* ix
'$1+0Ө&+Î1+%,ӆ8ĈӖ x
&+ѬѪ1*, *,Ӟ,7+,ӊ8 2
1.1 *LӟLWKLӋXÿӅWjL 2
1.1.1 *LӟLWKLӋXYҩQÿӅFҫQQJKLrQFӭX 2
1.1.2 ĈӕLWѭӧng nJKLrQFӭX 2
1.1.3 3KҥPYLQJKLrQFӭX 2
1.2 0өFWLrXQJKLrQFӭX 2
1.3 1ӝLGXQJQJKLrQFӭX 3
1.4 éQJKƭDNKRDKӑFFӫDÿӅWjL 3
1.5 éQJKƭDWKӵFWLӉQ 3
1.6 &ҩXWU~FOXұQYăQ 4
1.7 ӃWOXұQFKѭѫQJ*LӟLWKLӋX 5
&+ѬѪ1*,, &Ѫ6Ӣ/é7+8<ӂ7 7
2.1 7әQJTXDQYӅKӋWKӕQJJӧLê 7
2.2 /ӑFFӝQJWiF &ROODERUDWLYH)LOWHULQJ 7
2.2.1 Ma trұQKӳXtFh (Ultility Matrix) 8
2.2.2 +jPWѭѫQJÿӗQJ 6LPLODULW\)XQFWLRQ 9
2.2.3 +ҥQFKӃFӫD8VHU-based Collaborative Filtering 9
2.3 .ӻWKXұWSKkQUmPDWUұQ 0DWUL[IDFWRUL]DWLRQ 9
2.3.1 *LҧLWKXұWSingular Value Decomposition (SVD) 10
2.3.2 *LҧLWKXұW69' 11
2.3.3 Alternative Least Square (ALS) 11
2.3.4 *LҧLWKXұW%DVHOLQH6XUSULVH 12
2.4 ĈiQKJLiÿӝFKtQK[iFFӫDP{KuQK 12
2.5 &iFF{QJWUuQKQJKLrQFӭXQәLEұW 13
2.6 .ӃWOXұQFKѭѫQJ,, 14
&+ѬѪ1*,,, 3+Æ17Ë&+9¬*,Ҧ,3+È3 16
3.1 &iFÿһFWUѭQJFӫDGӳOLӋXVLQKYLrQĈҥLKӑF 16
3.1.1 Mô WҧEӝGӳOLӋXVLQKYLrQĈҥLKӑF 16
3.1.2 Ĉӝ[LrQ VNHZQHVV