'Word senses' diaporamas de présentation

Natural Language Processing

Natural Language Processing. Chapter 19 Computational Lexical Semantics Part 2 [Includes slides from a AAAI-2005 tutorial by Rada Mihalcea and Ted Pedersen]. Word Senses. The meaning of a word in a given context Word sense representations With respect to a dictionary

2.13k views • 186 slides

Advances in Word Sense Disambiguation

Advances in Word Sense Disambiguation. Tutorial at AAAI-2005 July 9, 2005 Rada Mihalcea University of North Texas http://www.cs.unt.edu/~rada Ted Pedersen University of Minnesota, Duluth http://www.d.umn.edu/~tpederse [Note: slides have been modified/deleted/added]. Definitions.

2.11k views • 186 slides

Towards Semantics for IR

Towards Semantics for IR. Eugene Agichtein Emory University. Acknowledgements A bunch of slides in this talk are adapted from lots of people, including Chris Manning, ChengXiang Zhai, James Allan, Ray Mooney, and Jimmy Lin. Who is this guy?.

1k views • 85 slides

Word Sense and Subjectivity

Word Sense and Subjectivity. Jan Wiebe Rada Mihalcea University of Pittsburgh University of North Texas. Introduction. Growing interest in the automatic extraction of opinions, emotions , and sentiments in text (subjectivity).

931 views • 71 slides

Word Sense and Subjectivity

Word Sense and Subjectivity. Jan Wiebe Rada Mihalcea University of Pittsburgh University of North Texas. Introduction. Growing interest in the automatic extraction of opinions, emotions , and sentiments in text (subjectivity).

830 views • 71 slides

On WordNet, Text Mining, and Knowledge Bases of the Future

On WordNet, Text Mining, and Knowledge Bases of the Future. Peter Clark March 2006 Knowledge Systems Boeing Phantom Works. Introduction. Interested in text understanding & question-answering use of world knowledge to go beyond text Used WordNet as (part of) the knowledge repository

824 views • 71 slides

Word Similarity

Word Similarity. David Kauchak CS457 Fall 2011. Admin. Assignment 3 grades sent back Quiz 2 Average 22.7 Assignment 4 Reading. Text Similarity. A common question in NLP is how similar are texts. ,. sim (. ) = ?. score:. ?. rank:. Bag of words representation.

822 views • 70 slides

Medical FactNet

VR. Medical FactNet. Barry Smith University at Buffalo and IFOMIS, Leipzig Christiane Fellbaum Princeton University. A consumer health medical information system must be able to map between expert and non-expert medical vocabulary

850 views • 64 slides

CS626/449 : Speech, NLP and the Web/Topics in AI Programming (Lecture 4: Word Sense Disambiguation; Wordnet)

CS626/449 : Speech, NLP and the Web/Topics in AI Programming (Lecture 4: Word Sense Disambiguation; Wordnet). Pushpak Bhattacharyya CSE Dept., IIT Bombay . Word Sense Disambiguation. WSD is a well know difficult problem Questions: Should the approach be Knowledge based Statistical Combined

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Semantics (Representing Meaning)

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Statistical NLP Winter 2008

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Cross-Lingual Image Search on the Web

585 views • 35 slides

Using corpora to study Classifiers in Mandarin Chinese

Using corpora to study Classifiers in Mandarin Chinese. Richard Xiao z.xiao@lancaster.ac.uk. Chinese corpus linguistics. In relation to English, Chinese has a much shorter history of using corpora Sinica Balanced Corpus of Chinese The first annotated corpus of Mandarin

495 views • 34 slides

A Knowledge-Driven Approach to Meaning Processing

A Knowledge-Driven Approach to Meaning Processing. Peter Clark Phil Harrison John Thompson Boeing Mathematics and Computing Technology . Goal. Answer questions about text, especially questions which go beyond explicitly stated facts.

461 views • 27 slides

Vector-Space (Distributional) Lexical Semantics

Vector-Space (Distributional) Lexical Semantics. Document corpus. Query String. 1. Doc1 2. Doc2 3. Doc3. Ranked Documents. Information Retrieval System. IR System. The Vector-Space Model. Graphic Representation. Term Weights: Term Frequency. Term Weights: Inverse Document Frequency.

571 views • 25 slides

An Experiment in Using Lexical Disambiguation to Enhance Information Access

An Experiment in Using Lexical Disambiguation to Enhance Information Access. Robert Wilensky, Isaac Cheng, Timotius Tjahjadi, and Heyning Cheng. Goal. Enhance information access by fully automated text categorization by adding searching by word sense Applied to the World Wide Web.

348 views • 23 slides

Extracting Knowledge-Bases from Machine-Readable Dictionaries: Have We Wasted Our Time?

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Aiding WSD by exploiting hypo/hypernymy relations in a restricted framework

479 views • 19 slides

WordNet

WordNet. WordNet, WSD. WordNet. What is WordNet?

554 views • 17 slides

Experiments on Using Semantic Distances Between Words in Image Caption Retrieval

Experiments on Using Semantic Distances Between Words in Image Caption Retrieval. Alan F. Smeaton and Ian Quigley School of Computer Applications Dublin City University. Presenter: Cosmin Adrian Bejan. IR implementation - traditional approach. Represent:

186 views • 9 slides