English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Collocations are important for many tasks of Natural language processing suchas information retrieval, machine translation, computational lexicography etc.So far many statistical methods have been used for collocation extraction.Almost all the methods form a classical crisp set of collocation. We propose afuzzy logic approach of collocation extraction to form a fuzzy set ofcollocations in which each word combination has a certain grade of membershipfor being collocation. Fuzzy logic provides an easy way to express naturallanguage into fuzzy logic rules. Two existing methods; Mutual information andt-test have been utilized for the input of the fuzzy inference system. Theresulting membership function could be easily seen and demonstrated. To showthe utility of the fuzzy logic some word pairs have been examined as anexample. The working data has been based on a corpus of about one million wordscontained in different novels constituting project Gutenberg available onwww.gutenberg.org. The proposed method has all the advantages of the twomethods, while overcoming their drawbacks. Hence it provides a better resultthan the two methods.

The Application of Fuzzy Logic to Collocation Extraction