Search Engine Course Overview Course Introduction Search engine

Search Engine Course Overview

Course Introduction Search engine is the most prevalent method of finding information today. To understand how search engines work, this course examines basic information retrieval (IR) theory and discusses how IR theory may be applied to practice. After learning about such topics as IR models, automatic classification, clustering and Web IR, students will explore how these IR technology can be employed in working IR systems such as Web search engines to improve the search results. 오늘날 정보를 찾을때 쓰는 가장 일반적인 방법은 검색 엔진이다. 어떻게 검색 엔진이 작동 하는지를 이해하고 또한 어떻게 그들이 강화될수 있는지에 대한 통찰력을 얻기를 위해, 과 정은 기본적인 정보검색 (IR) 이론을 소개하고 정보 검색 이론을 실천에 적용할 수 있는 방법 들을 연구한다. IR 모델, 자동 분류, 클러스터링, 웹사이트 내용 검색, 통합 정보 검색등의 주 제에 대한 학습 후, 이러한 정보 검색 테크놀러지들을 어떻게 웹 검색 엔진과 같은 정보 검색 시스템에 응용하여 검색 결과를 개선할수있을지 모색한다. Search Engines 2

Course Objectives n Study the Fundamentals of Information Retrieval. u u n Understand Search Engines. u u n Learn basic IR theory. Consider IR problems. How do they work? How can they be improved? Learn How to Think u u Search Engines What questions to ask How to find answers 3

Course Requirements n Prerequisites u u u n Basic computer skills Technical background is not required. Willingness to ask questions, investigate existing solutions, and explore new possibilities. Grading u u u Search Engines Homework Assignments (20%) Midterm Assignment (10%) Final Assignment (10%) Course Blog (30%) Group Project (30%) Participation (Extra Credit) 4

Course Requirements: n Homework Assignments (20%) u u u n Weekly online journal entries to discuss lectures & class discussions Group Project (30%) u n Multiple choice questions similar to midterm Course Blog (30%) u n Computational problems + Multiple choice questions Final Assignment (10%) u n Computational problems based on IR theory Extension of lab exercises do the lab first Basis for the Midterm Assignment (10%) u n Grading Analysis report to outline the strengths, weaknesses & enhancement ideas for a search engine of choice Participation (Extra Credit) u Search Engines e. g. , Class interactions, course feedback, etc. 5

Course Policy n Students are expected to be active participant in class discussions, where they will ask questions, provide insights, and explore ideas. n This class advocates an open book policy of allowing students to consult textbooks, Internet resources, and classmates when working on assignments to facilitate learning and promote collaboration. n The Honor Code is in effect. With the open book policy, it is especially important to clearly indicate in submitted work any materials used from other sources. Full citation information should be given for such sources. Search Engines 6

Course Resources n Required Readings u n Lecture material and online contents Supplemental Readings u Readings in Information Retrieval Edited by Karen Sparck Jones & Peter Willett 1997, Elsevier Science & Technology u Information Retrieval (2 nd Edition) by Van Rijsbergen 1979, Butterworth-Heinemann u Introduction to Information Retrieval by Christopher D. Manning, Prabhakar Raghavan & Hinrich Schütze 2008, Cambridge University Press u Information Retrieval: Implementing and Evaluating Search Engines by Stefan Buttcher, Charles L. A. Clarke, Gordon V. Cormack 2010, The MIT Press n Course Website u Search Engines https: //widit 2. knu. ac. kr/~kiyang/teaching/SE/ 7

Course Resources: Course Website n Syllabus u n Schedule u n Access Tutorials & Resources | DB Resources | Web DB Resources Roster u n Description | Requirements | Evaluation | Past & Current Projects Resources u n Description | Readings Projects u n Lecture | Lab | Assignments u n Description | Prerequisite | Policy | Grading | Textbooks Student Roster (log-in required) Attendance & Gradebook u from Schedule page Attendance record & Assignment grades (log-in required) Database Design 8