서울대학교 컴퓨터공학부 바이오지능 연구실 2014 Spring Semester Course Instructor: Prof. Byoung-Tak Zhang TAs: Ha-Young Jang & Beom-Jin Lee Classroom: , Time: Tue & Thu, 2:00 pm - 3:15pm Data Mining and Information Retrieval

 Objectives To review recent developments in web search, knowledge discovery, business intelligence, and recommender systems To study technical tools for data mining and information retrieval for building smart services based on web- based and mobile devices To learn analytics algorithms for classification, regression, clustering, anomaly detection, collaborative filtering, network analysis, and time series analysis To get future perspectives on intelligent services based on IoT, cloud computing, wearable smart devices, social media, and big data  Text Recommender Systems: An Introduction, Jannach, Zanker, Felfernig, and Friedrich, Recommender Systems: An Introduction, Jannach, Zanker, Felfernig, and Friedrich,  Reference Materials will be provided in the classes © 2014, SNU CSE Biointelligence Lab., 2 Data Mining and Information Retrieval

 Evaluation Two exams (50%) Two miniprojects (30%) ‒ Background 와 데이터 특성, 문제 특성 파악 및 솔루션 방향 제시 ‒데이터 특성에 따른 Model 선택, Formulation 전개, 알고리즘 작성 ‒완성 소스코드 ‒결과 보고서 Project presentation (10%) Participation in discussion (10%) ‒책 Chapter 읽고 생각 정리 올리기 (ETL) ‒ Data Mining and Information Retrieval Tool 조사 결과 보고서 and 발표 ‒ Mining Tool 숙제  Projects Project 1: Movie recommendation Project 2: Text mining © 2014, SNU CSE Biointelligence Lab., 3 Data Mining and Information Retrieval

 What is Data Mining and Information Retrieval? 1. Predictive Analytics & Machine Learning with SAP HANA 2. DATA MINING | The Checkout | ABC1  Big Success of Google 1. The Google Boys 01/ The Google Boys 02/ The Google Boys 03/05 © 2014, SNU CSE Biointelligence Lab., 4 Data Mining and Information Retrieval

 Q&A © 2014, SNU CSE Biointelligence Lab., 5 Data Mining and Information Retrieval