i Hc Quc gia TPHCM

Cng ngh tri thc v ng dngGS.TSKH. Hong Kim

Ni dung mn hcM u: Gii thiu tng quanPhn I: Qun l tri thc (knowledge management) Chng 1: Tip nhn, biu din tri thc

Chng 2: Ti u ha CSTTPhn II: Cc h CSTT (knowledge-based systems) Chng 3: Bn trong mt h CSTT

Chng 4: Phn loi cc h CSTTChng 5: Mt s h in hnh Phn III: Khai m d liu v khm ph tri thc (Data mining and Knowledge Discovery) Chng 6: My hc & khm ph tri thc. Chng 7: Khai m d liu.

Tng kt: Tm tt, gii thiu mt s cng trnh ni bt

M u: Gii thiu tng quan

Cng ngh tri thc l g ? Cng ngh tri thc (Knowledge Engineering): c th xem l mt nhnh nghin cu ca tr tu nhn to, phn tch tri thc lnh vc v chuyn n thnh nhng m hnh tnh ton a vo my tnh phc v nhng nhu cu cn thit. (John F.Sowa. Knowledge representation: Logical, philosophical, and Computational Foundations. Copyright @2000 by Brooks/Cole. A division of Thomson Learning)

Cng ngh tri thc l g ? (tt) Cng ngh tri thc (Knowledge Engineering): l cc phng php, k thut c nhng k s tri thc (knowledge engineers) dng xy dng nhng h thng thng minh nh: h chuyn gia, h c s tri thc, h h tr quyt nh, etc. (Dr Dickson Lukose. Department of Mathematics, Statistics and Computer Science - The University of New England. Dr Rob Kremer Department of Computer Science The University of Calgary Calgary, Alberta, T2N 1N4 Canada. Courses: KNOWLEDGE ENGINEERING, PART A: Knowledge Representation. July 1996) Cng ngh tri thc l nhng phng php, k thut dng : Tip nhn, biu din tri thc. Xy dng cc h c s tri thc Khm ph tri thc

Khoa hc tri thc (knowledge science)

Vai tr ca cng ngh tri thc Cng vi s pht trin nhanh chng, vt bc ca ngnh cng nghip my tnh, nhu cu ca ngi dng i vi my tnh ngy mt cao hn: khng ch gii quyt nhng cng vic lu tr, tnh ton bnh thng, ngi dng cn mong i my tnh c kh nng thng minh hn, c th gii quyt vn nh con ngi. V t tr tu nhn to ni chung v c bit l cng ngh tri thc ra i v pht trin Cng ngh tri thc ng vai tr ht sc quan trng trong vic pht trin Cng ngh thng tin, nng cao s hu dng ca my tnh, gip con ngi gn gi vi my tnh hn. Cng ngh tri thc cn gp phn thc y nhiu ngnh khoa hc khc pht trin, kh nng pht trin khoa hc da trn tri thc lin ngnh

Cc lnh vc trong thng minh nhn to (AI)

ARTIFICIAL INTELLIGENCE ROBOTICS NATURAL LANGUAGE PROCESSING KNOWLEDGE - BASED SYSTEMS EXPERT SYSTEMS

MACHINE LEARNING

p dng cc khi nim ca AI vo my tnh

Inputs (questions, problems, ..)

KNOWLEDGE BASE

INFERENCING CAPABILITY

Outputs (answers, solutions, ..)

Mt trong nhng mc tiu quan trng ca lnh vc nghin cu ny l lm cho my tnh c kh nng tip nhn, gii quyt vn ging nh con ngi, thm ch hn c con ngi (my tnh IBM Deep Blue chin thng vua c Kasparov).

Hng nghin cu, pht trin cng ngh tri thc inputs Outputs

MY TNH

TIP NHN, BIU DIN, TI U HA CSTT

CC H C S TRI THC

KHAI THC D LIU, KHM PH TRI THC

Qun l tri thc (knowledge management): bao gm tip nhn, biu din v ti u ha c s tri thc Cc h c s tri thc (knowledge-based systems): tm hiu cu trc bn trong ca mt h c s tri thc, phn loi cc h c s tri thc, v mt s h c s tri thc in hnh. khai m d liu, khm ph tri thc (Data mining, knowledge discovery): nghin cu v phng php, k thut khai m d liu v khm ph tri thc.

a tri thc vo my tnh

Nhn thc Suy lun Phn ng Tnh cm

Tip nhn, biu din v ti u ha c s tri thc ng c suy din Phn ng, tr li B x l tnh cm ?

Qun l tri thc: Tip nhn tri thc

C th chia thnh 2 cch tip nhn tri thc nh sau:

Th ng- Gin tip: nhng tri thc kinh in. -Trc tip: nhng tri thc kinh nghim (khng kinh in) do chuyn gia lnh vc a ra. Ch ng - i vi nhng tri thc tim n, khng r rng h thng phi t phn tch, suy din, khm ph c thm tri thc mi

Qun l tri thc: Tip nhn tri thc Giao tip ngi-my In: Keyboard, Mouse, sensors, touch-pad, touchable screen, speech-recognition, Out: text, graphics, voice, Con ngi B x l ngn ng t nhin

Qun l tri thc: Biu din tri thc Phng php biu din tri thc Logic mnh & logic v t

H lut dni tng-thuc tnh-gi tr Mng ng ngha Frame Script

Qun l tri thc: Ti u c s tri thcTi sao ti u c s tri thc ? Vn mu thun, trng lp, d tha ny sinh khi tri thc c tip nhn v biu din trong c s tri thc. V vy i hi chng ta phi c phng php ti u c s tri thc. Ty thuc vo cch biu din tri thc, chng ta s c phng php thch hp ti u c s tri thc. V d: in hnh cho vn ny l bi ton loi b lut tha trong c s tri thc lut.

Tng quan h c s tri thcTri thc Tip nhn tri thc Vng nh lm vic

C s tri thc (s kin, lut, )

ng c suy din Tm kim

Gii thch B x l ngn ng t nhin

iu khin

Cc h c s tri thc: ng, m, kt hp H c s tri thc ng: l nhng h c s tri thc c xy dng vi mt s tri thc lnh vc ban u, v ch nhng tri thc m thi trong sut qu trnh hot ng hay sut thi gian sng ca n. V d: nhng h c s tri thc v kinh dch, nhng h gii ton, thng l nhng h c s tri thc gii quyt vn

Cc h c s tri thc: ng, m, kt hp (tt) H c s tri thc m: l nhng h c s tri thc tin tin hn, n c kh nng b sung tri thc trong qu trnh hot ng, khm ph. V d: Nhng h gii ton cho php b sung tri thc trong qu trnh suy lun (tri thc ban u l nhng tin v mt s nh l, tri thc b sung l nhng nh l mi, nhng tri thc heurictis, ); nhng h c s tri thc chn on, d bo chng hn: h chn on y khoa MYCIN v EMYCIN, nhng h d bo thi tit, kh hu, ng t,

Cc h c s tri thc: ng, m, kt hp (tt) H c s tri thc kt hp: bao gm s kt hp gia h ng v h m, h kt hp gia CSTT v CSDL, h kt hp gia h CSTT ny vi mt h CSTT khc, Nhng h c s tri thc kt hp thng pht trin mnh da trn tri thc lin ngnh.

V d: nhng h h tr ra quyt nh trong i sng, kinh t v khoa hc; (kinh dch, t vi p dng vi i sng; kinh dch, t vi p dng vi y hc; ); nhng h chn on, d bo di hi tri thc lin ngnh;

Cc h c s tri thc: phn loi theo phng php biu din tri thc Ty thuc vo phng php biu din tri thc m chng ta c th phn loi cc h c s tri thc H c s tri thc da trn logic mnh v logic v t

H c s tri thc da trn lut dnH c s tri thc da trn i tng

H c s tri thc da trn FrameH c s tri thc da trn mng ng ngha H CSTT kt hp mt s phng php biu din nu trn.

Cc h c s tri thc: phn loi theo ng dng H gii quyt vn : thng l h c tnh cht ng, nhng i khi cng c h mang tnh m. V d: Nhng h gii ton, thut gii Vng Ho, thut gii Robinson, H h tr quyt nh: thng l cc h mang tnh kt hp (CSDL + tri thc ngnh + hm ton hc + ..), i tng s dng l cc nh lnh o.

V d: nhng h thng nh gi doanh nghip (tnh hnh ti chnh, kt qu kinh doanh, qui trnh nghip v, qui trnh sn xut, tnh chuyn nghip trong qun l, ), nhng h thng lp k hoch (planning),

Cc h c s tri thc: phn loi theo ng dng (tt) H d bo, chn on: thng cng ging nh nhng h h tr ra quyt nh vi tnh ngoi suy cao hn. V d: Bi ton chn on hng hc xe, chn on y khoa, d bo th trng chng khon, thi tit H iu khin: l nhng h iu khin c gn vi CSTT. Nhng h thng ny thng ng dng trong cng nghip, trong iu khin t ng ha, thng l nhng h thng thi gian thc (realtime systems). Mt s h thng ny c s dng kt hp l thuyt m x l.

V d: My git, My bm nc vi b iu khin m,

My hc v khm ph tri thc Th no l khm ph tri thc (knowledge discovery) ? Khm ph tri thc l tm ra nhng tri thc tim n, nhng tri thc mi (khng phi l nhng tri thc kinh in, kinh nghim, ) Tha d liu, thng tin nhng thiu tri thc.

Tri thc Mc tru tng Thng tin D liu S lng

My hc v khm ph tri thc (tt) V d: Trong ton hc D liu: 1, 1, 2, 3, 5, 8, 13, 21, 34, Mi lin h ny c th c biu din bng cng thc sau: Un = Un-1 + Un-2 Cng thc tm ra trn chnh l tri thc V d: Trong vt l Cng thc: U = IxR l tri thc rt ra t thc nghim V d: Chun chun bay thp th ma, bay cao th nng, bay va th rm Li nhn xt trn l tri thc rt ra t kinh nghim i sng.

My hc v khm ph tri thc (tt) Th no l my hc (Learning Machine) ? My tnh hay chng trnh my tnh c kh nng t hon thin t kinh nghim. My hc cn c ngha l vic m hnh ha mi trng xung quanh hay kh nng mt chng trnh my tnh sinh ra mt cu trc d liu mi khc vi cu trc hin c. Chng hn vic tm ra nhng lut Ifthen t tp d liu u vo.

(Krzysztof J. Cios, Witold Pedrycz, Roman W. Swiniarski. Data Mining Methods for Knowledge Discovery. Kluwer Academic Publishers, 1998)

My hc v khm ph tri thc (tt) Phn loi cc phng php my hc: c nhiu quan im phn loi khc nhau Phn loi th:

Hc gim st (supervised learning) Hc khng gim st (unsupervised learning) Phn loi theo 2 tiu chun cng lc: cp hc & cch tip cn Cp hc: Hc vt (Rote learning) Hc theo gii thch (by explanation) Hc theo v d, trng hp (by examples, cases) Hc khm ph (by discovering)

My hc v khm ph tri thc (tt)

Cch tip cn: Tip cn thng k Tip cn ton t logic Tip cn hnh hc (phn hoch khng gian, xy dng cy nh danh, ) Tip cn mng Neural Tip cn khai m d liu

Nh kho d liu v khai m d liu To DATA WAREHOUSE = Bin i d liu thnh tri thc ym tr tin trnh ra quyt nh.

D liuKhoa hc Gio dc

Cng nghKinh doanh Th trng Thi tit

To Data Warehouse

Data warehouse

Tri thc ym tr ra quyt nh

Nh kho d liu v khai m d liu (tt)

DatawareHouse = Business Information + Decision Making

(IBM BPEC96 Conference, San Diego, USA)

S bng n ca cc CSDL ln vt qu kh nng din dch v lnh hi ca con ngi, pht sinh yu cu sng to cc cng c k thut mi phn tch d liu mt cch thng minh v t ng nhm to ra tri thc hu dng h tr tt cho tin trnh ra quyt nh. (Usama, Data Mining and Knowledge Discovery, 1995)

Nh kho d liu v khai m d liu (tt) Mt s bi ton in hnh v data mining Bi ton khm ph lut kt hp

Bi ton nhn dng muBi ton phn loi d liu Bi ton gom nhm d liu Bi ton lp m hnh Bi ton d bo

Ti liu tham kho[1] GS.TSKH Hong Kim. Bi ging cao hc mn hc c s tri thc v ng dng. HKHTN-TPHCM.[2] GS.TSKH Hong Kim.Th vin nhng bo co khoa hc, bi thu hoch mn c s tri thc v ng dng. Cc lp cao hc thuc khoa CNTT- HKHTN. TPHCM. [3] GS.TSKH Hong Kim, TS. Vn Nhn, Th.s Phc. Gio trnh Cc h c s tri thc. i Hc Quc Gia TPHCM 2002. [4] GS.TSKH Hong Kim, Th.s inh Nguyn Anh Dng. Gio trnh Tr tu nhn to. i Hc Quc Gia TPHCM 2002. [5] John F.Sowa. Knowledge representation: Logical, Philosophical, and Computational Foundations. Copyright @ 2000 by Brooks/Cole. A division of Thomson Learning. [6] Adrian A.Hopgood. Knowledge-based systems for Engineers and Scientists. The Open University CRC Press. Boca-Raton Ann-Arbor London Tokyo 1998. [7] Sharon Wood. Planning and decision making in dynamic domains.Ellis Horwood Series in Artificial Intelligence - 1998. [8] Krzysztof J. Cios, Witold Pedrycz, Roman W. Swiniarski. Data Mining Methods for Knowledge Discovery. Kluwer Academic Publishers, 1998 [9] Citeseer - Scientific Literature Digital Library. Artificial Intelligencehttp://citeseer.nj.nec.com/ArtificialIntelligence/ - 2003

Th vin s CiteseerMt s nghin cu ang c quan tm v AI http://citeseer.nj.nec.com/ArtificialIntelligence/

- Expert Systems : http://citeseer.nj.nec.com/ArtificialIntelligence/ExpertSystems/ - Knowledge Representation: http://citeseer.nj.nec.com/ArtificialIntelligence/KnowledgeRepresentation/ - Natural Language Processing: http://citeseer.nj.nec.com/ArtificialIntelligence/NaturalLanguageProcessing/ - Optimization: http://citeseer.nj.nec.com/ArtificialIntelligence/Optimization/ - Planning: http://citeseer.nj.nec.com/ArtificialIntelligence/Planning/ - Robotics: http://citeseer.nj.nec.com/ArtificialIntelligence/Robotics/