'Spelling correction' diaporamas de présentation

Lunch & Learn Intent Guide

Lunch & Learn Intent Guide. Welcome . Lunch & Learn Intent Guide. 10.00-10.30 Opening & Introduction Intent Guide by Marcel Smit, VP Natural Language Search Solutions 10.30-11.30 Research & Product Management by Leonoor van der Beek, Manager Research 11.30-11.45 Break (Atrium)

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Information Retrieval and Search Engines

Information Retrieval and Search Engines. Lecture 3: Dictionaries and Tolerant Retrieval Prof. Michael R. Lyu. Motivation of This Lecture. What data structure should we use to store the dictionary in index? How to design index so that we could search goog * and ba *du?

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Machine Learning basics

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Sequence Models

Sequence Models. With slides by me, Joshua Goodman, Fei Xia. Outline. Language Modeling Ngram Models Hidden Markov Models Supervised Parameter Estimation Probability of a sequence Viterbi (or decoding) Baum-Welch. A bad language model. A bad language model. A bad language model.

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CS276: Information Retrieval and Web Search

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Spelling Correction and the Noisy Channel

Spelling Correction and the Noisy Channel. The Spelling Correction Task. Applications for spelling correction. Word processing. Phones. Web search. Spelling Tasks. Spelling Error Detection Spelling Error Correction: Autocorrect hte ? the Suggest a correction Suggestion lists.

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Handwriting Recognition

Handwriting Recognition. CPSC 4600 @ UTC/CSE. Handprint Recognition. Handprint Recognition aims to design systems which are able to recognize handwriting of natural language Methods and recognition rates depend on the level of constraints on handwriting.

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Chapter 6 Three Simple Classification Methods

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CS188 Guest Lecture: Statistical Natural Language Processing

CS188 Guest Lecture: Statistical Natural Language Processing. Prof. Marti Hearst School of Information Management & Systems www.sims.berkeley.edu/~hearst. School of Information Management & Systems. School of Information Management & Systems. Information economics and policy.

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Spelling correction

Spelling correction. Two di?erent methods for spelling correction Isolated word spelling correction Check each word on its own for misspelling Will not catch typos resulting in correctly spelled words, e.g., an asteroid that fell form the sky Context-sensitive spelling correction

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A BAYESIAN APPROACH TO SPELLING CORRECTION

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Problem 1: Word Segmentation

Problem 1: Word Segmentation. whatdoesthisreferto. what does this refer to. Application: Chinese Text. Application: Internet Domain Names. www. visitbritain .com. Visit Britain. Statistical Machine Learning. Best segmentation = one with highest probability

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Online Spelling Correction for Query Completion

Online Spelling Correction for Query Completion. Huizhong Duan, UIUC Bo-June (Paul) Hsu, Microsoft WWW 2011 March 31, 2011. Background. Typing quickly ex x it mis [s] pell Inconsistent rules conc ie ve conc ei rge Keyboard adjacency impor y ant Ambiguous word breaking silver _ light

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Metodi statistici nella linguistica computazionale

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Metodi statistici nella linguistica computazionale

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Human Language Technology

Human Language Technology. Spelling Models. References. Eric Mays, Fred J. Damerau, and Robert L. Mercer. 1991. Context based spelling correction. Inf. Process. Manage. 27, 5 (September 1991), 517-522.

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Viewing AutoTutor as a step-based tutoring system

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