'Lexical features' presentation slideshows

Language Independent Methods of Clustering Similar Contexts (with applications)

Language Independent Methods of Clustering Similar Contexts (with applications). Ted Pedersen University of Minnesota, Duluth http://www.d.umn.edu/~tpederse tpederse@d.umn.edu. The Problem. A context is a short unit of text

1.75k views • 164 slides

Language Independent Methods of Clustering Similar Contexts (with applications)

Language Independent Methods of Clustering Similar Contexts (with applications). Ted Pedersen University of Minnesota, Duluth http://www.d.umn.edu/~tpederse tpederse@d.umn.edu. Language Independent Methods. Do not utilize syntactic information

1.4k views • 126 slides

Exploiting Background Knowledge for Relation Extraction

686 views • 54 slides

SVM Anchored Learning and Model Tampering (a case study in Hebrew NP chunking)

SVM Anchored Learning and Model Tampering (a case study in Hebrew NP chunking). Toward Better Understanding of Hebrew NP Chunks. Yoav Goldberg and Michael Elhadad Ben Gurion University of the Negev, Israel. Lexicalization.

547 views • 54 slides

Chapter 8 Total Physical Response (TPR)

1.47k views • 50 slides

Yun - Nung ( Vivian ) Chen, Yu Huang, Sheng -Yi Kong, Lin-Shan Lee

Automatic Key Term Extraction from Spoken Course Lectures Using Branching Entropy and Prosodic/Semantic Features. Yun - Nung ( Vivian ) Chen, Yu Huang, Sheng -Yi Kong, Lin-Shan Lee. National Taiwan University, Taiwan. Introduction. Definition. Key Term Higher term frequency Core content

688 views • 50 slides

11.0 Spoken Document Understanding and Organization for User-content Interaction

565 views • 43 slides

Identifying Deceptive Speech

Identifying Deceptive Speech. Julia Hirschberg Computer Science Columbia University. Collaborators.

546 views • 43 slides

Programming for Linguists

Programming for Linguists. An Introduction to Python 15/12/2011. Tuples. A sequence of values They are similar to lists: the values can be any type they are indexed by integers Syntactically a tuple is a comma-separated list of values : t = 'a', ' b ', ' c ', ' d ', ' e '.

503 views • 38 slides

Exploiting document structure and feature hierarchy for semi-supervised domain adaptation

Exploiting document structure and feature hierarchy for semi-supervised domain adaptation. Andrew Arnold, Ramesh Nallapati , William W. Cohen Machine Learning Department Carnegie Mellon University Work from ACL:HLT & CIKM 2008 CMU Machine Learning Lunch September 29, 2008.

284 views • 28 slides

Japanese Dependency Structure Analysis Based on Maximum Entropy Models

344 views • 24 slides

Learning to Predict Readability using Diverse Linguistic Features

Learning to Predict Readability using Diverse Linguistic Features. Rohit J. Kate 1 Xiaoqiang Luo 2 Siddharth Patwardhan 2 Martin Franz 2 Radu Florian 2 Raymond J. Mooney 1 Salim Roukos 2 ChrisWelty 2 1 Department of Computer Science The University of Texas at Austin

382 views • 23 slides

Speech Summarization

Speech Summarization. Julia Hirschberg (thanks to Sameer Maskey for some slides) CS4706. Summarization ? Distillation.

399 views • 23 slides

Speech Summarization

Speech Summarization. Julia Hirschberg (thanks to Sameer Maskey for some slides) CS4706. Summarization ? Distillation.

451 views • 23 slides

LING/C SC/PSYC 438/538

LING/C SC/PSYC 438/538. Lecture 14 Sandiway Fong. Administrivia. Midterm This Wednesday A bit like doing a homework in real time Bring your laptop Exam slides available at class time Answer as many questions as you can and email me your answers at 7pm

311 views • 19 slides

Characteristics of English Administrative Law Text

Characteristics of English Administrative Law Text. See the difference. English. Indonesian. Characteristics of Legal Language.

534 views • 13 slides

Bang-Xuan Huang Department of Computer Science & Information Engineering

205 views • 13 slides

Improving Lecture Speech Summarization using Rhetorical Information

Improving Lecture Speech Summarization using Rhetorical Information. Presenter: Shih-Hsiang Lin 02/21/2008. Introduction. Unlike conversational speech, lecture and presentations are planned speech Lecture speakers will follow a relatively rigid rhetorical structure

255 views • 11 slides

Appalachia:

Appalachia:. Linguistic Traits & Characteristics. Appalachian Region. Southern highland region of the US Encompasses all of WV, follows east of Blue Ridge, NC in a SW direction into GA and turns to include AL, TN, and KY. A sampling: Nonstandard irregular verb forms Multiple negation

242 views • 10 slides

Natural Language Processing for the Web

Natural Language Processing for the Web. Prof. Kathleen McKeown 722 CEPSR, 939-7118 Office Hours: Wed, 1-2; Tues 4-5 TA: Yves Petinot 719 CEPSR, 939-7116 Office Hours: Thurs 12-1, 8-9. Logistics. Class evaluation Please do If there were topics you particularly liked, please say so

206 views • 9 slides