Paper Info
Title
Towards Shared Datasets for Normalization Research.
Abstract
In this paper we present a Dutch and English dataset that can serve as a gold standard for evaluating text normalization approaches. With the combination of text messages, message board posts and tweets, these datasets represent a variety of user generated content. All data was manually normalized to their standard form using newly-developed guidelines. We perform automatic lexical normalization experiments on these datasets using statistical machine translation techniques. We focus on both the word and character level and find that we can improve the BLEU score with ca. 20% for both languages. In order for this user generated content data to be released publicly to the research community some issues first need to be resolved. These are discussed in closer detail by focussing on the current legislation and by investigating previous similar data collection projects. With this discussion we hope to shed some light on various difficulties researchers are facing when trying to share social media data.
Year
Venue
Keywords
2014
LREC 2014 - NINTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION
user generated content,text normalization,resource sharing
Field
DocType
Citations 
User-generated content,Data collection,Social media,Normalization (statistics),Information retrieval,Computer science,Machine translation,Legislation,Artificial intelligence,Natural language processing,Shared resource,Text normalization
Conference
0
PageRank 
References 
Authors
0.34
10
4
Name
Order
Citations
PageRank
Orphée De Clercq11179.61
Sarah Schulz2313.72
Bart Desmet3757.92
Véronique Hoste431935.92