PPT-Practical and Reliable Retrieval Evaluation

Through Online Experimentation WSDM Workshop on Web Search Click Data February 12 th 2012 Yisong Yue Carnegie Mellon University Offline Posthoc Analysis Launch some ranking function on live traffic. Document Image Retrieval. David Kauchak. cs160. Fall 2009. adapted from. :. David . Doermann. http://terpconnect.umd.edu/~oard/teaching/796/spring04/slides/11/796s0411.ppt. Assign 4 . writeups. Overall, I was very happy. INST 734. Module 3. Doug . Oard. Agenda. Ranked retrieval. Similarity-based ranking. Probability-based ranking. Boolean Retrieval. Strong points. Accurate, . if you know the right strategies. Efficient for the computer. CSC . 575. Intelligent Information Retrieval. 2. Source: . Intel. How much information?. Google: . ~100 . PB a . day; 3+ million servers (15 . Exabytes. stored). Wayback Machine has . ~9 . PB + . 100 . Faced . by Evaluation Professionals in Undertaking Consultancy Assignments in Evaluation . IDEAS . Conference 2011, Amman. Presenter. Preethi De Silva, Sri Lanka. Objective of the Presentation . . . Relevant. : . images which meet user’s information need. Irrelevant. : . images which don’t meet user’s information need. Query: cat. Relevant. Irrelevant. 1. Accuracy. Given a query, an engine classifies each image as “Relevant” or “. Reliability. How do I answer these questions?. i.e. How reliable is this source ....?. Balance. Most sources chosen are reliable in some ways but not others.. Comments on origin. Who produced it? In what circumstance? For what purpose? Did they have a motive to mislead? How might this affect reliability?. (for MODIS). Andy Harris. Jonathan . Mittaz. Prabhat. . Koner. (Chris Merchant, Pierre . LeBorgne. ). Satellite data – pros and cons. Main advantages of satellite data. Frequent and regular global coverage (cloud cover permitting for IR). Practical Assessment Research & Evaluation, Vol 10, No 65Dickey & Pearson, Recency Effect Training and DiaryDiary OnlyPre- and Post-test ControlPrePostPrePostPrePostPostMSDMSDMSDMSDMSDMSDMSD3.830.874 Information Retrieval. Information Retrieval. Konsep. . dasar. . dari. IR . adalah. . pengukuran. . kesamaan. sebuah. . perbandingan. . antara. . dua. . dokumen. , . mengukur. . sebearapa. . ChengXiang. (“Cheng”) . . Zhai. Department of Computer Science. University of Illinois at Urbana-Champaign. http://www.cs.uiuc.edu/homes/czhai. . Email: czhai@illinois.edu. 1. Yahoo!-DAIS Seminar, UIUC. Colorado Division . of Fire . Prevention . & Control . (DFPC). Class Presented By. . Instructor: . . Department:. Phone:. Email Address:. Introductions. Name. Department. Years in the Fire Service. Hongning. Wang. CS@UVa. What is information retrieval?. CS6501: Information Retrieval. CS@UVa. 2. Why information retrieval . Information overload. “. It refers to the . difficulty. a person can have understanding an issue and making decisions that can be caused by the presence of . Fatemeh. Azimzadeh. Books. (Manning et al., 2008). Christopher D. Manning, . Prabhakar. . Raghavan. , and . Hinrich. . Schütze. . Introduction to Information Retrieval. Cambridge University Press, 2008. . Retrieval Practice: Lesson 3. 1. What is an . autobiography. ?.  .  2. Does Roald Dahl consider . Boy . to be an . autobiography. ? Why or why not?.  .  3. What is an . anecdote. ?.  . 4. Describe one .