PPT-Hinrich

Schütze and Christina Lioma Lecture 3 Dictionaries and tolerant retrieval 1 Overview Recap Dictionaries Wildcard queries Edit distance Spelling correction Soundex 2 Outline. V 2007 Abstract The colors of fruits and 64258owers are traditionally viewed as an adaptation to increase the detectability of plant organs to animal vectors The detectability of visual signals increases with increasing contrasts between target and b . Schütze. and Christina . Lioma. Lecture 1: Boolean Retrieval. 1. 2. Take-. away. Administrativa. Boolean Retrieval: Design and data structures of a simple . information. . retrieval. . system. . Schütze. and Christina . Lioma. Lecture . 14: Vector Space Classification. 1. Overview. Recap . . Feature selection. Intro vector space classification . . Rocchio. . kNN. Linear classifiers. . Schütze. and Christina . Lioma. Lecture . 20: Crawling. 1. Overview. . R. ecap . . A simple crawler. . A real crawler. 2. Outline. . R. ecap . . A simple crawler. . A real crawler. 3. 4. Search. . Schütze. and Christina . Lioma. Lecture . 11: Probabilistic Information Retrieval. 1. Overview. . Probabilistic Approach to Retrieval. . Basic Probability Theory. Probability Ranking Principle. . Schütze. and Christina . Lioma. Lecture 7: Scores in a Complete Search System. 1. Overview. Recap . . Why rank? . More on cosine. Implementation of ranking . The complete search system. 2. . Schütze. and Christina . Lioma. Lecture . 15-1: Support Vector Machines. 1. Overview. . Support Vector Machines. . Issues in the classification of . text . documents. 2. Outline. . Support Vector Machines. . Schütze. and Christina . Lioma. Lecture . 15-2: Learning to Rank. 1. Overview. . Learning . Boolen. Weights. . Learning Real-Valued Weights. Rank Learning as Ordinal Regression. 2. Outline. . . Schütze. and Christina . Lioma. Lecture 5: Index Compression. 1. Overview. Recap . . Compression. . Term statistics. Dictionary compression. Postings compression. 2. Outline. Recap . . Compression. . Schütze. and Christina . Lioma. Lecture 2: The term vocabulary and postings lists. 1. Overview. Recap . . Documents. . Terms. General + Non-English. English. Skip pointers. Phrase queries. 2. Lioma. Lecture 5: Index Compression. 1. Overview. Recap . . Compression. . Term statistics. Dictionary compression. Postings compression. 2. Outline. Recap . . Compression. Term statistics. Dictionary compression. Lioma. Lecture 3: Dictionaries and tolerant retrieval. 1. Overview. Recap . . Dictionaries. . Wildcard queries. Edit distance. Spelling correction. Soundex. 2. Outline. Recap . . Dictionaries. Wildcard queries. Lioma. Lecture . 20: Crawling. 1. Overview. . R. ecap . . A simple crawler. . A real crawler. 2. Outline. . R. ecap . . A simple crawler. . A real crawler. 3. 4. Search. . engines. rank . content. Lioma. Lecture . 18: Latent Semantic Indexing. 1. Overview. Latent semantic indexing . Dimensionality reduction. LSI in information retrieval. 2. Outline. Latent semantic indexing . Dimensionality reduction.