'Index term' presentation slideshows

Modeling the Internet and the Web: Text Analysis

Modeling the Internet and the Web: Text Analysis. Outline. Indexing Lexical processing Content-based ranking Probabilistic retrieval Latent semantic analysis Text categorization Exploiting hyperlinks Document clustering Information extraction. Information Retrieval.

1.15k views • 102 slides

A Selection of Print & Electronic Library Resources For MAE 4344

A Selection of Print & Electronic Library Resources For MAE 4344. Edmon Low Library Oklahoma State University Kevin Drees Engineering Librarian July 2002

1.04k views • 85 slides

IR Models

IR Models. J. H. Wang Mar. 11, 2008. Text. User Interface. 4, 10. user need. Text. Text Operations. 6, 7. logical view. logical view. Query Operations. DB Manager Module. Indexing. user feedback. 5. 8. inverted file. query. Searching. Index. 8. retrieved docs. Text

778 views • 58 slides

Chapter 2 Modeling

Chapter 2 Modeling. Modern Information Retrieval by R. Baeza-Yates and B. Ribeiro-Neto. Introduction. Traditional information retrieval systems usually adopt index terms to index and retrieve documents.

888 views • 45 slides

Motivation and Outline

Motivation and Outline. Background Definitions, etc. The Problem 100,000+ pages The Solution Ranking docs Vector space Extensions Relevance feedback, clustering, query expansion, etc. Motivation. IR: representation, storage, organization of, and access to information items

450 views • 38 slides

Your topics II: SciFinder for smart or functional materials hbz 2013

Your topics II: SciFinder for smart or functional materials hbz 2013. Smart Materials take a closer look I. 1844 entries in SciFinder for Smart materials (2/2013) Valid CA concept heading 1997 to present Used for intelligent materials as well . Smart Materials take a closer look II.

501 views • 33 slides

Modern Information Retrieval Chapter 5 Query Operations

Modern Information Retrieval Chapter 5 Query Operations. ??????? ??? 89522022. Introduction. It is difficult to formulate queries which are well designed for retrieval purposes. Improving the initial query formulation through query expansion and term reweighting . Approaches based on:

735 views • 33 slides

Information Retrieval: Foundation to Web Search

412 views • 32 slides

Special Topics in Computer Science Advanced Topics in Information Retrieval Chapter 2: Modeling

Special Topics in Computer Science Advanced Topics in Information Retrieval Chapter 2: Modeling. Alexander Gelbukh www.Gelbukh.com. Previous chapter. User Information Need Vague Semantic, not formal Document Relevance Order, not retrieve Huge amount of information Efficiency concerns

500 views • 29 slides

Hierarchical Indexing and Flexible Element Retrieval for Structured Document

373 views • 28 slides

Visual Thinking

Visual Thinking. Rich Miller LexisNexis Research Scientist Alliances & New Technology richard.miller@lexisnexis.com. What is Visual Thinking?. An approach to understanding, creating, and communicating A collection of visually-based concepts and methods

763 views • 27 slides

University of Palestine

418 views • 26 slides

University of Palestine

397 views • 26 slides

INFORMATION RETRIEVAL AND WEB SEARCH

INFORMATION RETRIEVAL AND WEB SEARCH. CC437. (Based on original material by Udo Kruschwitz). INFORMATION RETRIEVAL. GOAL: Find the documents most relevant to a certain QUERY Latest development: WEB SEARCH Use the Web as the collection of documents Related: QUESTION-ANSWERING

609 views • 25 slides

346 views • 25 slides

Introduction

Introduction. IR systems usually adopt index terms to process queries Index term: a keyword or group of selected words any word (more general) Stemming might be used: connect: connecting, connection, connections An inverted file is built for the chosen index terms. Introduction. Docs.

348 views • 24 slides

Chapter 2 Modeling

Chapter 2 Modeling. ?? 4B 86075800 ???. Introduction. Traditional information retrieval systems usually adopt index terms to index and retrieve documents. An index term is a keyword (or group of related words) which has some meaning of its own (usually a noun).

334 views • 24 slides

WMES3103 : INFORMATION RETRIEVAL

WMES3103 : INFORMATION RETRIEVAL. TEXT OPERATIONS. INTRODUCTION. Not all words in a document = significant to represent the contents/meanings of a document Some word carry more meaning than others Noun words or group of noun words = most representative of a document content

342 views • 21 slides

LIS618 lecture 6

LIS618 lecture 6. Thomas Krichel 2003-03-05. structure. DIALOG basic vs additional index initial database file selection (files) Lexis/Nexis. basic vs additional index. the basic index has information that is relevant to the substantive contents of the data

280 views • 18 slides

IR Models

Algebraic. Set Theoretic. Generalized Vector Lat. Semantic Index Neural Networks. Structured Models. Fuzzy Extended Boolean. Non-Overlapping Lists Proximal Nodes. Classic Models. Probabilistic. Boolean Vector Probabilistic. Inference Network Belief Network. Browsing.

358 views • 18 slides