Introducing fise, the Open Source RESTful Semantic Engine
From the post:
fise is now known as the Stanbol Enhancer component of the Apache Stanbol incubating project.
As a member of the IKS european project Nuxeo contributes to the development of an Open Source software project named fise whose goal is to help bring new and trendy semantic features to CMS by giving developers a stack of reusable HTTP semantic services to build upon.
Presenting the software in Q/A form:
What is a Semantic Engine?
A semantic engine is a software component that extracts the meaning of a electronic document to organize it as partially structured knowledge and not just as a piece of unstructured text content.
Current semantic engines can typically:
- categorize documents (is this document written in English, Spanish, Chinese? is this an article that should be filed under the Business, Lifestyle, Technology categories? …);
- suggest meaningful tags from a controlled taxonomy and assert there relative importance with respect to the text content of the document;
- find related documents in the local database or on the web;
- extract and recognize mentions of known entities such as famous people, organizations, places, books, movies, genes, … and link the document to there knowledge base entries (like a biography for a famous person);
- detect yet unknown entities of the same afore mentioned types to enrich the knowledge base;
- extract knowledge assertions that are present in the text to fill up a knowledge base along with a reference to trace the origin of the assertion. Examples of such assertions could be the fact that a company is buying another along with the amount of the transaction, the release date of a movie, the new club of a football player…
During the last couple of years, many such engines have been made available through web-based API such as Open Calais, Zemanta and Evri just to name a few. However to our knowledge there aren't many such engines distributed under an Open Source license to be used offline, on your private IT infrastructure with your sensitive data.
Impressive work that I found through a later post on using this software on Wikipedia. See Mining Wikipedia with Hadoop and Pig for Natural Language Processing.