中国人平易近大年夜学藏书楼(信息检索)培训课件二.ppt

龙星计划课程:信息检索?? Course Overview Background Outline Course overview Essential background Probability statistics Basic concepts in information theory Natural language processing Course Overview Course Objectives Introduce the field of information retrieval (IR) Foundation: Basic concepts, principles, methods, etc Trends: Frontier topics Prepare students to do research in IR and/or related fields Research methodology (general and IR-specific) Research proposal writing Research project (to be finished after the lecture period) Prerequisites Proficiency in programming (C++ is needed for assignments) Knowledge of basic probability statistics (would be necessary for understanding algorithms deeply) Big plus: knowledge of related areas Machine learning Natural language processing Data mining … Course Management Teaching staff Instructor: ChengXiang Zhai (UIUC) Teaching assistants: Hongfei Yan (Peking Univ) Bo Peng (Peking Univ) Course website: /~course/cs410/ Course group discussion: /group/cs410pku Questions: First post the questions on the group discussion forum; if questions are unanswered, bring them to the office hours (first office hour: June 23, 2:30-4:30pm) Format Requirements Lecture-based: Morning lectures: Foundation Trends Afternoon lectures: IR research methodology Readings are usually available online 2 Assignments (based on morning lectures) Coding (C++), experimenting with data, analyzing results, open explorations (~5 hours each) Final exam (based on morning lectures): 1:30-4:30pm, June 30. Practice questions will be available Format Requirements (cont.) Course project (Mini-TREC) Work in teams Phase I: create test collections (~ 3 hours, done within lecture period) Phase II: develop algorithms and submit results (done in the summer) Research project proposal (based on afternoon lectures) Work in teams 2outline done within lecture period full proposal (5 pages) due later Coverage of Topics: IR vs. TIM What is Text Info. Management? TIM