Introduction to information storage and retrieval (IR). IR vs. DBMS. User perspective, search models, evaluation of IR systems. Formal IR models. Data structures and techniques including, inverted files, signature files, information filtering, clustering and cluster-based retrieval, hypertext and multimedia systems. IR and the Internet, browsing strategies, search engines, web robots and intelligent agents.
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60% attendance to course lectures. Minimum 40 in the midterm exam.
IR Systems Overview System System Evaluation Different ways of calculating document by document similarity values to be used for clustering Clustering Methods and Their Implementation Cluster Validation (Cluster Purity, Rand's Coefficient, Yao's Formula) Stemming Automatic Indexing and Term Weighting Automatic Indexing, Term Weighting Term Discrimination Concept PAT Trees Inverted Files, Search Result Diversification and Evaluation Inverted vs. Signature Files Inverted vs. Signature Files Information Filtering Stance Detection and Some New Problems Related to Dynamic Data Stream Environments Student Project Presentation ECTS - Workload Table: Activities Number Hours Workload Midterm exam 1 2 2 Project (including preparation and presentation if applicable) 1 20 20 Final exam 1 2 2 Preparation for Final exam 1 15 15 Preparation for Midterm exam 1 10 10 Course hours 14 3 42 Homework 5 10 50 Individual or group work 14 1 14 Total Workload: 155 Total Workload / 30: 155 / 30 5.17 ECTS Credits of the Course: 5 Type of Course: Solving Problems - Independent Study - Lecture - Project - Research Paper - Seminar (where students are attendees) - Seminar (where students are presenters) Teaching Methods: Lecture - Assignments - Case studies - Independent study - Presentations