PPT-Hinrich

Schütze and Christina Lioma Lecture 5 Index Compression 1 Overview Recap Compression Term statistics Dictionary compression Postings compression 2 Outline Recap Compression. org Abstract This paper presents a graphtheoretic model of the acquisition of lexical syntactic representa tions The representations the model learns are noncategorical or graded We propose a new evaluation methodology of syntactic ac quisition in th . 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 3: Dictionaries and tolerant retrieval. 1. Overview. Recap . . Dictionaries. . Wildcard queries. Edit distance. Spelling correction. Soundex. 2. Outline. . 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 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 9: Relevance Feedback & Query Expansion. 1. 2. Take-. away. . today. Interactive relevance feedback:. improve initial retrieval results by telling the IR system which docs are relevant / . . 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. . Schütze. and Christina . Lioma. Lecture . 19: Web Search. 1. Overview. Recap . . Big picture. Ads . Duplicate detection. 2. Outline. Recap . . Big picture. Ads . Duplicate detection. 3. 4. 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.