Now showing items 1-6 of 6
Improving classification of tweets using word-word co-occurrence information from a large external corpus
(Association for Computing Machinery (ACM), 2016)
Classifying tweets is an intrinsically hard task as tweets are short messages which makes traditional bags of words based approach ine cient. In fact, bags of words approaches ig- nores relationships between important ...
Improving Classification of Tweets Using Linguistic Information from a Large External Corpus
The bag of words representation of documents is often unsat- isfactory as it ignores relationships between important terms that do not co-occur literally. Improvements might be achieved by expanding the vocabulary with ...
Automatic security classification by machine learning for cross-domain information exchange
Cross-domain information exchange is necessary to obtain information superiority in the military domain, and should be based on assigning appropriate security labels to the information objects. Most of the data found ...
Building sentiment Lexicons applying graph theory on information from three Norwegian thesauruses
(Bibsys Open Journal Systems, 2014)
Sentiment lexicons are the most used tool to automatically predict sentiment in text. To the best of our knowledge, there exist no openly available sentiment lexicons for the Norwegian language. Thus in this paper ...
Building domain specific sentiment lexicons combining information from many sentiment lexicons and a domain specific corpus
Most approaches to sentiment analysis requires a sentiment lexicon in order to automatically predict sentiment or opinion in a text. The lexicon is generated by selecting words and assigning scores to the words, and the ...
Categorization and Comparison of Accessibility Testing Methods for Software Development
(IOS Press, 2018)
There are many methods for testing accessibility and universal design, ranging from checklists and guidelines to automated testing and finally to human testing with participants from different user groups. It is, however, ...