Platform for ontology generation and document summary

BACKGROUND

Companies accumulate millions of textual documents of different nature: invoices, contracts, reports, presentations, etc. An ontology can help process them in many ways.

Problem

The documents are distributed unorganised and their content is not considered, therefore losing huge amounts of knowledge. To have an overview of the entire information, it is necessary to contact one by one each user managing those files to analyze the content with them.

Benefit

By means of AI, a conceptual graph (ontology) describing the different properties found in the texts is generated. Thus, delivering an easy summary of all documents.

METHODOLOGY & results

Architecture: On-premise development using local databases such as MySQL.

Developing language: Java

ML techniques: Unsupervised learning algorithms and NLP techniques.

Results: Depending on the complexity of the texts and their associated vocabulary, the system generates a much deeper (or not) conceptual graph summarising the concepts available linking the most important aspects among them.

This project was carried out before AI Shepherds’ foundation by its team members.
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