'Query terms' diaporamas de présentation

Factor and Component Analysis

Factor and Component Analysis. esp. Principal Component Analysis (PCA). Why Factor or Component Analysis?. We study phenomena that can not be directly observed ego, personality, intelligence in psychology Underlying factors that govern the observed data

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Developing i2b2 Ontologies for the Long Haul

Developing i2b2 Ontologies for the Long Haul. Lori Phillips, MS Partners HealthCare Systems, Inc April 25, 2012. National Centers for Biomedical Computing. What is i2b2?.

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Introducing Information Retrieval and Web Search

Introducing Information Retrieval and Web Search. Information Retrieval. Information Retrieval (IR) is finding material (usually documents) of an unstructured nature (usually text) that satisfies an information need from within large collections (usually stored on computers) .

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CS276 Information Retrieval

CS276 Information Retrieval. Lecture 2. Recap of the previous lecture. Basic inverted indexes: Structure: Dictionary and Postings Key step in construction: Sorting Boolean query processing Simple optimization Linear time merging Overview of course topics. Plan for this lecture.

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EVALUATING VISUALIZATIONS : USING A TAXONOMIC GUIDE

EVALUATING VISUALIZATIONS : USING A TAXONOMIC GUIDE By E. MORSET, M. LEWIS & K. A. OLSEN PRESENTORS CHANNA P. WITANA C ALVIN O R CONTENT Introduction Visual and domain tasks Methodology Tasks Results Discussion Conclusion INTRODUCTION Previous Papers published;

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Vector Space Model : Ranking Revisited

Vector Space Model : Ranking Revisited. Adapted from Lectures by Prabhakar Raghavan (Yahoo and Stanford) and Christopher Manning (Stanford). Recap: tf-idf weighting. The tf-idf weight of a term is the product of its tf weight and its idf weight.

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CS276 Information Retrieval and Web Search Pandu Nayak and Prabhakar Raghavan

CS276 Information Retrieval and Web Search Pandu Nayak and Prabhakar Raghavan Lecture 7: Scoring and results assembly. Ch. 6. Recap: tf-idf weighting. The tf-idf weight of a term is the product of its tf weight and its idf weight. Best known weighting scheme in information retrieval

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Dictionary and Postings; Query Processing

Dictionary and Postings; Query Processing. Adapted from Lectures by Prabhakar Raghavan (Yahoo and Stanford) and Christopher Manning (Stanford). Tokenizer. Friends. Romans. Countrymen. Token stream. Linguistic modules. friend. friend. roman. countryman. Modified tokens. roman.

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Discovering your Discovery System in Real-Time

Discovering your Discovery System in Real-Time. Annette Bailey Godmar Back. (Academic) Libraries in 2014: some observations. Majority of library resources used are electronic Physical space is being dedicated to student work areas and digital displays

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Computing Relevance, Similarity: The Vector Space Model

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Inverted Index Construction

Inverted Index Construction. Adapted from Lectures by Prabhakar Raghavan (Yahoo and Stanford) and Christopher Manning (Stanford). Unstructured data in 1650. Which plays of Shakespeare contain the words Brutus AND Caesar but NOT Calpurnia ?

634 views • 28 slides

Boolean and Vector Space Retrieval Models

Boolean and Vector Space Retrieval Models. Many slides in this section are adapted from Prof. Joydeep Ghosh (UT ECE) who in turn adapted them from Prof. Dik Lee (Univ. of Science and Tech, Hong Kong). Retrieval Models. A retrieval model specifies the details of: Document representation

288 views • 27 slides

Latent Semantic Indexing: A probabilistic Analysis

Latent Semantic Indexing: A probabilistic Analysis. Christos Papadimitriou Prabhakar Raghavan, Hisao Tamaki, Santosh Vempala. Motivation . Application in several areas: querying clustering, identifying topics Other: synonym recognition (TOEFL..) Psychology test essay scoring. Motivation.

476 views • 24 slides

Latent Semantic Indexing: A probabilistic Analysis

Latent Semantic Indexing: A probabilistic Analysis. Christos Papadimitriou Prabhakar Raghavan, Hisao Tamaki, Santosh Vempala. Motivation . Application in several areas: querying clustering, identifying topics Other: synonym recognition (TOEFL..) Psychology test essay scoring. Motivation.

368 views • 24 slides

Interactive Sense Feedback for Difficult Queries

Interactive Sense Feedback for Difficult Queries. Alexander Kotov and ChengXiang Zhai. University of Illinois at Urbana-Champaign. Roadmap. Query Ambiguity Interactive Sense Feedback Experiments Upper-bound performance User study Summary Future work. Query ambiguity. sports?.

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Learning to Rank at Query-Time using Association Rules

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Elementary IR: Scalable Boolean Text Search

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Motivation

Motivation. It is clear that humans are more complex than computer systems, and their motivations e behaviors are more difficult to measure and characterize. It is clear too that the information access is a complex activity.

367 views • 22 slides

Parallel and Distributed IR

Parallel and Distributed IR. Papers on Parallel and Distributed IR. Agenda. Introduction Paper A: Inverted file partitioning schemes in Multiple Disk Systems by Byeong-Soo Jeong and Edward Omiecinski [404]

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