PPT-Information Retrieval and Web Search

Boolean retrieval Instructor Rada Mihalcea Note some of the slides in this set have been adapted from a course taught by Prof Chris Manning at S tanford University Typical IR task. Miguel Costa. , Daniel Gomes (speaker). Portuguese Web . Archive. Information Retrieval. is the activity of obtaining . information resources relevant. . to an . information need. from a . collection. Information Retrieval in Practice. All slides ©Addison Wesley, 2008. Search and Information Retrieval. Search on the Web. 1. is a daily activity for many people throughout the world. S. earch and communication are most popular uses of the computer. Miguel Costa. , Daniel Gomes (speaker). Portuguese Web . Archive. Information Retrieval. is the activity of obtaining . information resources relevant. . to an . information need. from a . collection. Tutorial. Introduction. Miriam Fernandez | KMI, Open University, UK. Thanh Tran | Institute AIFB, KIT, DE. Peter Mika| Yahoo Research, Spain. Search . Document Retrieval vs. Data Retrieval. Differences of search technologies. 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. Hongning. Wang. CS@UVa. Classical search engine architecture. “The . Anatomy of a Large-Scale . Hypertextual. Web Search . Engine”. - Sergey . Brin. and . Lawrence Page, . Computer networks and ISDN systems. Hongning. Wang. CS@UVa. Classical search engine architecture. “The . Anatomy of a Large-Scale . Hypertextual. Web Search . Engine”. - Sergey . Brin. and . Lawrence Page, . Computer networks and ISDN systems. Hongning. Wang. CS@UVa. Recap: Core IR concepts. Information need. “. an individual or group's desire to locate and obtain information to satisfy a conscious or unconscious need. ” – wiki. An IR system is to satisfy users’ information need. All slides ©Addison Wesley, 2008. Beyond Bag of Words. “Bag of Words”. a document is considered to be an unordered collection of words with no relationships. Extending representation. feature-based models. BY. DR. ADNAN ABID. Lecture # . Introduction. Library Management System. Structured Data Storage / Tables. Semi-Structured and Unstructured . Employee Department Salary. Library Digitization. Information Retrieval Models. Hongning. Wang. CS@UVa. CS@UVa. CS6501: Information Retrieval. 1. Abstraction of search engine architecture. User. Ranker. Indexer. Doc Analyzer. Index. results. Crawler. Doc . Representation . Query Rep. What is IR?. Sit down before fact as a little child, . be prepared to give up every conceived notion, . follow humbly wherever and whatever abysses nature leads, . or you will learn nothing. . . -- Thomas Huxley --. PRESENTED BY . Peter Mika, Sr. Research Scientist, Yahoo Labs. . ⎪ . November 27, . 2014 . The Semantic Web (2001-). 11/27/14. 2. Part of Tim . Berners-Lee’s . original proposal . for the . Web. Session 10 – Information Retrieval and Dissemination. Lecturer: Dr. . Perpetua. S. . Dadzie. , Dept. of Information Studies. Contact Information: psdadzie@ug.edu.gh. Session Overview . At the end of the session, the student will be able to.