'Evaluation metric' diaporamas de présentation

Metadata Extraction: Human Language Technology and the Semantic Web

Metadata Extraction: Human Language Technology and the Semantic Web http://gate.ac.uk/ http://nlp.shef.ac.uk/ Hamish Cunningham Kalina Bontcheva Valentin Tablan Diana Maynard SEKT meeting, London, 21 January 2004. Gartner, December 2002:

1.34k views • 117 slides

Metadata Extraction: Human Language Technology and the Semantic Web

Metadata Extraction: Human Language Technology and the Semantic Web http://gate.ac.uk/ http://nlp.shef.ac.uk/ Hamish Cunningham Kalina Bontcheva Valentin Tablan Diana Maynard SEKT meeting, London, 21 January 2004. Gartner, December 2002:

1.28k views • 117 slides

Named Entity Recognition gate.ac.uk/ nlp.shef.ac.uk/ Hamish Cunningham

Named Entity Recognition http://gate.ac.uk/ http://nlp.shef.ac.uk/ Hamish Cunningham Kalina Bontcheva RANLP, Borovets, Bulgaria, 8 th September 2003. Structure of the Tutorial. task definition applications corpora, annotation evaluation and testing how to preprocessing

1.32k views • 110 slides

Named Entity Recognition gate.ac.uk/ nlp.shef.ac.uk/ Hamish Cunningham

Named Entity Recognition http://gate.ac.uk/ http://nlp.shef.ac.uk/ Hamish Cunningham Kalina Bontcheva RANLP, Borovets, Bulgaria, 8 th September 2003. Structure of the Tutorial. task definition applications corpora, annotation evaluation and testing how to preprocessing

1.23k views • 109 slides

Named Entity Recognition gate.ac.uk/ nlp.shef.ac.uk/ Hamish Cunningham

Named Entity Recognition http://gate.ac.uk/ http://nlp.shef.ac.uk/ Hamish Cunningham Kalina Bontcheva RANLP, Borovets, Bulgaria, 8 th September 2003. Structure of the Tutorial. task definition applications corpora, annotation evaluation and testing how to preprocessing

1.24k views • 108 slides

Named Entity Recognition gate.ac.uk/ nlp.shef.ac.uk/ Hamish Cunningham

Named Entity Recognition http://gate.ac.uk/ http://nlp.shef.ac.uk/ Hamish Cunningham Kalina Bontcheva RANLP, Borovets, Bulgaria, 8 th September 2003. Structure of the Tutorial. task definition applications corpora, annotation evaluation and testing how to preprocessing

1.16k views • 104 slides

Language Modeling for ASR

Language Modeling for ASR. Andreas Stolcke Microsoft and ICSI (based on slides from Dan Jurafsky at Stanford). Outline. What is language modeling Noisy channel and its applications The 99%: N-gram modeling and smoothing The 1%: Cache LMs Parsing-based LMs Discriminative LMs

933 views • 71 slides

Evaluating Algorithms for GRE

Evaluating Algorithms for GRE. Kees van Deemter (work with Albert Gatt, Ielka van der Sluis, and Richard Power) University of Aberdeen, Scotland, UK. Outline. GRE: G eneration of R eferring E xpressions TUNA project: Corpus and Annotation Evaluation of Algorithms Furniture Domain

523 views • 37 slides

SI485i : NLP

SI485i : NLP. Set 3 Language Models. Fall 2012 : Chambers. Language Modeling. Which sentence is most likely (most probable)? I saw this dog running across the street. Saw dog this I running across street the. Why ? You have a language model in your head.

437 views • 30 slides

Introduction to Language Acquisition Theory Janet Dean Fodor St. Petersburg July 2013

Introduction to Language Acquisition Theory Janet Dean Fodor St. Petersburg July 2013. Class 5. The Subset Principle: Essential but impossible?. T oday: How far to generalize?.

302 views • 29 slides

Semantic Evaluation of Machine Translation

Semantic Evaluation of Machine Translation. Billy Wong, City University of Hong Kong 21 st May 2010. Introduction. Surface text similarity is not a reliable indicator in automatic MT evaluation Insensitive to variation of translation Deeper linguistic analysis is preferred

257 views • 10 slides

Statistical Models and Machine Learning Algorithms --Review

Statistical Models and Machine Learning Algorithms --Review. B. Ramamurthy. Lets review LM. "lm" by default seeks to find a trend line that minimizes the sum of squares of the vertical distances between the approximated or predicted and observed y's .

91 views • 9 slides

Research Challenges in Recommender Systems / Survey of the Netflix Contest

By Rachsuda Jiamthapthaksin 10/09/2009. Research Challenges in Recommender Systems / Survey of the Netflix Contest. Edited by Christoph F. Eick. Recommender Systems (RSs). Goal: To help users to find items that they likely appreciate (and buy/lease) from huge catalogues.

219 views • 8 slides

193 views • 2 slides