Skip navigation.
Home
Semantic Software Lab
Concordia University
Montréal, Canada

Smarter Wikis through Integrated Natural Language Processing Assistants

Printer-friendly versionPrinter-friendly versionPDF versionPDF version
TitleSmarter Wikis through Integrated Natural Language Processing Assistants
Publication TypeConference Paper
Year of Publication2013
Refereed DesignationNon-Refereed
AuthorsSateli, B., and R. Witte
Conference NameSemantic MediaWiki Conference (SMWCon) Spring 2013
Date Published03/2013
Conference LocationNew York City, NY, USA
Type of WorkConference Presentation at SMWCon Spring 2013
Abstract

Wiki-NLP Integration is the first comprehensive open source solution for bringing Natural Language Processing (NLP) to wiki users, in particular for wikis based on the well-known MediaWiki engine and its Semantic MediaWiki (SMW) extension. It can run any NLP pipeline deployed in the General Architecture for Text Engineering (GATE), brokered as web services through the Semantic Assistants server. This allows you to bring novel text mining assistants to wiki users, e.g., for automatically structuring wiki pages, answering questions in natural language, quality assurance, entity detection, summarization, among others. The results of the NLP analysis are written back to the wiki, allowing humans and AI to work collaboratively on wiki content. Additionally, semantic markup understood by the SMW extension can be automatically generated from NLP output, providing semantic search and query functionalities.

In this presentation we will explain the Wiki-NLP Integration architecture and how NLP capabilities can be integrated within a given wiki environment. As application scenarios, we will also demonstrate two applications based on our Wiki-NLP Integration that is used in real-world projects, one from the Software Engineering and one from the Biomedical domain.

URLhttp://semantic-mediawiki.org/wiki/SMWCon_Spring_2013/Smarter_Wikis
Copyright

Copyright is held by the author/owner(s).

AttachmentSize
smwcon13_talk.pdf1.3 MB