1 “GARIS-GARIS BESAR PROGRAM PENGAJARAN” PEMROSESAN TEKS “GARIS-GARIS BESAR PROGRAM PENGAJARAN” PEMROSESAN TEKS SHINTA P STMIK GI MDP 2012.

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““GARIS-GARIS BESAR PROGRAM GARIS-GARIS BESAR PROGRAM

PENGAJARAN”PENGAJARAN”

PEMROSESAN TEKSPEMROSESAN TEKS

““GARIS-GARIS BESAR PROGRAM GARIS-GARIS BESAR PROGRAM

PENGAJARAN”PENGAJARAN”

PEMROSESAN TEKSPEMROSESAN TEKS

SHINTA P

STMIK GI MDP

2012

ABOUT ME

Bachelor Degree In Mathematics, University Of SriwijayaMaster Degree In Computer Science University Of IndonesiaDomain Interest : IR , Image & Text

ProcessingMail me : [email protected]

SYLLABUS

Rencana Kuliah

No. Topik

1. Pendahuluan

2. Aplikasi pemrosesan teks

3. Inverted index

4. Model IR

5. Evaluasi IR

6. Relevance Feedback and Query Expansion

7. Probabilistic IR

UTS

Rencana Kuliah

No. Topik

8. Text Classification

9. Clustering

10. Text Summarization

11.

12. Multimedia Information Retrieval System (MIRS)

13. Question Answering System and CLIR

14. Web Search

UAS

References

Modern Information Retrieval, Ricardo & Berthier, Addison, 1999

Statistical Natural Language Processing, 2002

RULES OF THE CLASS (1/3)

ATTENDANCE10 minutes late are allow75% attendance in the class

BEHAVIOR DURING THE CLASSBe respectful to each other and to all materials.No talking while materials are presentedNo eating or drinking in the classroom.Follow all other school and district rules. I encourage you to ask questions, do not hesitate

to ask.

RULES OF THE CLASS (2/3)

ASSIGNMENT

No late work will be accepted unless you are absent because of sickness.

All assignments will be turned in at the beginning of class.  After class starts the assignment can still be turned in but ten points will be deducted .

Quiz at the end of the class

RULES OF THE CLASS (3/3)

CONSEQUENCES To be sent out of the current class. Point deduction.

10

THANKS FOR YOUR GOOD ATTENTION

QA!

Overview IR

SE Top Rank

Web spider

Why SE ?