Bekli: A Simple Approach to Twitter Text Normalization Russell Beckley Oregon Health and Sciences University Portland, Oregon

Source URL: noisy-text.github.io

A Log-Linear Model for Unsupervised Text Normalization Yi Yang School of Interactive Computing Georgia Institute of Technology

Source URL: www.cc.gatech.edu

Normalization in Intuitionistic Set Theories Ulrik Buchholtz Stanford April 13, 2010

Source URL: www.andrew.cmu.edu

NCSU-SAS-Ning: Candidate Generation and Feature Engineering for Supervised Lexical Normalization Ning Jin Text Analytics R&D SAS Institute, Inc.

Source URL: noisy-text.github.io

NCSU_SAS_SAM: Deep Encoding and Reconstruction for Normalization of Noisy Text Samuel P. Leeman-Munk James C. Lester Center for Educational Informatics North Carolina State University

Source URL: noisy-text.github.io

Toward Tweets Normalization Using Maximum Entropy Mohammad Arshi Saloot Department of Artificial Intelligence, University of Malaya, 50603, Malaysia

Source URL: noisy-text.github.io

USZEGED: Correction Type-sensitive Normalization of English Tweets Using Efficiently Indexed n-gram Statistics Ervin Tasn´adi G´abor Berend University of Szeged University of Szeged

Source URL: noisy-text.github.io

Noether normalization guided by monomial cone decompositions Daniel Robertz Lehrstuhl B f¨ ur Mathematik, RWTH Aachen University, Templergraben 64, D–52062 Aachen, Germany

Source URL: wwwb.math.rwth-aachen.de

Shared Tasks of the 2015 Workshop on Noisy User-generated Text: Twitter Lexical Normalization and Named Entity Recognition Timothy Baldwin University of Melbourne Marie Catherine de Marneffe

Source URL: noisy-text.github.io

ATHANASIOS ORPHANIDES Fear of Liftoff: Uncertainty, Rules and Discretion in Monetary Policy Normalization Institute for Monetary and Financial Stability

Source URL: www.imfs-frankfurt.de

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