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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In the domain of IT benchmarking collected data are often stored in natural language text and therefore intrinsically  unstructured. To ease data analysis and data evaluations across different types of IT benchmarking  approaches a semantic representation of this information is crucial. Thus, the identification of conceptual (semantical)  similarities is the first step in the development of an integrative data management in this domain. As  an ontology is a specification of such a conceptualization an association of terms, relations between terms and  related instances must be developed. Building on previous research we present an approach for an automated  term extraction by the use of natural language processing (NLP) techniques. Terms are automatically extracted  out of existing IT benchmarking documents leading to a domain specific dictionary. These extracted terms are  representative for each document and describe the purpose and content of each file and server as a basis for  the ontology development process in the domain of IT benchmarking.

Natural Language Processing Techniques for Document Classification in IT Benchmarking - Automated Identification of Domain Specific Terms