Master of Science in Computer Engineering

Infomation Retrieval(INF 501)

Course Code Course Name Semester Theory Practice Lab Credit ECTS
INF 501 Infomation Retrieval 2 3 0 0 3 6
Prerequisites
Admission Requirements
Language of Instruction English
Course Type Compulsory
Course Level Masters Degree
Course Instructor(s) Uzay ÇETİN (Email)
Assistant
Objective Introduce current aspects of the design and the implementation of systems for gathering, indexing and searching documents. Present and evaluate searching systems on text, image, audio and video processing tools. Discuss modern architecture of indexation and query processing. Generation, tracking, compressing and filtering techniques in information retrieval and related features of multimodal and hybrid search engines. Advanced Topics in new generation search engines related to multimedia formats (indexing, storage and retrieval techniques) will be covered in this course.
Content 1- Boolean Retrieval,Scoring
2- Vector Space Models, Similarity and normalization in hyperspaces
3- Evaluation in IR, LAB: Introduction to text processing
4- Relevance Feedback
5- Query expansion, global and local methods
6- Probabilistic information retrieval
7- Machine learning in IR: kNN, Naive Bayes, Support Vector Machines, Voronoi diagrams
8- Midterm
9- Latent Semantic Retrieval, LAB: Classification
10- Content Based Image Retrieval-I: Feature extraction
11- Content Based Image Retrieval-II: Classification, evaluation and advanced applications
12- Content Based Music/Sound Retriveal: Time-Frequency features, applications
13- Video search engines, applications, LAB:Feature extraction and classification in multimedia
14- Projects
Course Learning Outcomes
Teaching and Learning Methods
References Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze, Introduction to Information Retrieval, Cambridge University Press. 2008.
Jens Rainer Ohm, Multimedia Content Analysis, Springer, 2016.
Maragos, Potomianos, Gros, Multimodal Processing and Interaction Audio, Video, Text, Springer, 2008.
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Theory Topics
Week Weekly Contents
Practice Topics
Week Weekly Contents
Contribution to Overall Grade
  Number Contribution
Contribution of in-term studies to overall grade 0 0
Contribution of final exam to overall grade 0 0
Toplam 0 0
In-Term Studies
  Number Contribution
Assignments 0 0
Presentation 0 0
Midterm Examinations (including preparation) 0 0
Project 0 0
Laboratory 0 0
Other Applications 0 0
Quiz 0 0
Term Paper/ Project 0 0
Portfolio Study 0 0
Reports 0 0
Learning Diary 0 0
Thesis/ Project 0 0
Seminar 0 0
Other 0 0
Toplam 0 0
No Program Learning Outcomes Contribution
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Activities Number Period Total Workload
Total Workload 0
Total Workload / 25 0.00
Credits ECTS 0
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