'Eigen decomposition' diaporamas de présentation

Latent Semantic Indexing

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Latent Semantic Indexing

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CS276: Information Retrieval and Web Search Christopher Manning and Pandu Nayak

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Web Search and Data Mining

Web Search and Data Mining. Lecture 4 Adapted from Manning, Raghavan and Schuetze. Recap of the last lecture. MapReduce and distributed indexing Scoring documents: linear comb/zone weighting tf ? idf term weighting and vector spaces Derivation of idf. This lecture. Vector space models

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Lecture 13: Matrix Factorization and Latent Semantic Indexing

Web Search and Mining. Lecture 13: Matrix Factorization and Latent Semantic Indexing. Topic. Matrix factorization = matrix decomposition Latent Semantic Indexing (LSI) Term-document matrices are very large But the number of topics that people talk about is small (in some sense)

751 views • 47 slides

Lecture 13: Matrix Factorization and Latent Semantic Indexing

Web Search and Mining. Lecture 13: Matrix Factorization and Latent Semantic Indexing. Topic. Matrix factorization = matrix decomposition Latent Semantic Indexing (LSI) Term-document matrices are very large But the number of topics that people talk about is small (in some sense)

477 views • 47 slides

CS276: Information Retrieval and Web Search Christopher Manning and Prabhakar Raghavan

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Introduction to Information Retrieval

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ITCS 6265 Information Retrieval & Web Mining

ITCS 6265 Information Retrieval & Web Mining. Lecture 16 Latent semantic indexing Thanks to Thomas Hofmann for some slides. This lecture. Latent Semantic Indexing Term-document matrices are very large But the number of topics that people talk about is small (in some sense)

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Text Categorization Moshe Koppel Lecture 12:Latent Semantic Indexing

Text Categorization Moshe Koppel Lecture 12:Latent Semantic Indexing. Adapted from slides by Prabhaker Raghavan, Chris Manning and TK Prasad. Clustering documents (and terms). Latent Semantic Indexing Term-document matrices are very large

584 views • 42 slides

Eigen Decomposition and Singular Value Decomposition

Eigen Decomposition and Singular Value Decomposition. Based on the slides by Mani Thomas Modified and extended by Longin Jan Latecki. Introduction. Eigenvalue decomposition Spectral decomposition theorem Physical interpretation of eigenvalue/eigenvectors Singular Value Decomposition

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433 views • 27 slides

Eigen Decomposition and Singular Value Decomposition

Eigen Decomposition and Singular Value Decomposition. Mani Thomas CISC 489/689. Introduction. Eigenvalue decomposition Spectral decomposition theorem Physical interpretation of eigenvalue/eigenvectors Singular Value Decomposition Importance of SVD Matrix inversion

769 views • 18 slides

Feature Space Based Watermarking in Multi-Images

Feature Space Based Watermarking in Multi-Images. Xin Zhou. Outlines. Introduction Feature Space Based Watermarking Simulation Results Conclusion. Introduction. Goal: Implement the watermarking in a set of images or video based on eigen-decomposition or SVD (Singular Value Decomposition).

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Part I: Web Structure Mining Chapter 2: Hyperlink Based Ranking

Part I: Web Structure Mining Chapter 2: Hyperlink Based Ranking. Social Network Analysis PageRank Authorities and Hubs Link Based Similarity Search Enhanced Techniques for Page Ranking. Social Networks. Directed graph with weights assigned to its edges

340 views • 9 slides