Gray, Alexander - College of Computing, Georgia Institute of Technology

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Gray, Alexander - College of Computing, Georgia Institute of Technology

Massachusetts Institute of Technology Course Notes 1 6.042J/18.062J, Fall '02: Mathematics for Computer Science
What does Collaboration mean in a Computer Science class? Welcome to this CS class! You will be turning in source code for many of your homework
Recap Introduction BSBI algorithm SPIMI algorithm Distributed indexing Dynamic indexing Web Search and Text Mining
Recap Compression Term statistics Dictionary compression Postings compression Web Search and Text Mining
Introduction Basic XML concepts Challenges in XML IR Vector space model for XML IR Evaluation of XML IR Web Search and Text Mining
Probabilistic Approach to Retrieval Basic Probability Theory Probability Ranking Principle Appraisal & Extensions Web Search and Text Mining
Text classification Naive Bayes NB theory Evaluation of TC Web Search and Text Mining
Feature selection Intro vector space classification Rocchio kNN Linear classifiers > two classes Web Search and Text Mining
Support Vector Machines Issues in the classification of text documents Learning Boolean Weights Learning Real-Valued Web Search and Text Mining
Latent semantic indexing Dimensionality reduction LSI in information retrieval Web Search and Text Mining
Anchor text Citation analysis PageRank HITS: Hubs & Authorities Web Search and Text Mining
CS 1050B: Constructing Proofs Supplementary Exercises 1 : Proof, Induction, and Recursion
CS 1050B: Constructing Proofs Supplementary Exercises 2 : Counting, Discrete Probability
Recap Why ranked retrieval? Term frequency tf-idf weighting The vector space model Web Search and Text Mining
CS 1050B: Constructing Proofs Supplementary Exercises 3 : Comprehensive
Introduction Inverted index Processing Boolean queries Query optimization Web Search and Text Mining
Language models Language Models for IR Discussion Web Search and Text Mining
Recap Introduction Single-link/Complete-link Centroid/GAAC Variants Labeling clusters Web Search and Text Mining
Recap A simple crawler A real crawler Web Search and Text Mining
Recap Documents Terms Skip pointers Phrase queries Web Search and Text Mining
Motivation Relevance feedback: Basics Relevance feedback: Details Query expansion Web Search and Text Mining
Big picture Ads Duplicate detection Spam Web IR Size of the web Web Search and Text Mining
Recap Dictionaries Wildcard queries Edit distance Spelling correction Soundex Web Search and Text Mining
he goals of IBM Research are to advance computer science by exploring new ways for computer technology to affect
A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition
CS 70 Discrete Mathematics for CS Spring 2004 Papadimitriou/Vazirani Lecture 1
Recap Why rank? More on cosine Implementation of ranking The complete search system Web Search and Text Mining
CS 1050B: Constructing Proofs Supplementary Exercises 3 : Comprehensive
Unranked evaluation Ranked evaluation Evaluation benchmarks Result summaries Web Search and Text Mining