Brevium.

Get to the Point

Project Description

A smart system that abstracts the sentiment of long format contents to shorten them and present them in a meaningful way for consumption by the social media outlets and mobile devices. The solution collects, analyses and transforms content, based on patented technologies grounded in strong mathematical foundations such as Principle Component Analysis, Machine Learning and Computer Vision.

Problem
Current web information is filled with web sites such as search engines, news aggregators, social media sites, blog sites and content sites. None of them seem to address the challenge of getting to the point in least amount of time possible. In fact, current sites seem to have incentive not to deliver to-the-point information but keep users browsing around for longer time.

The challenge of the modern information age is keeping up with the exponential growth of information around us. It takes time to be aware of what is happening and even more time to sort out what is applicable to us and what is pure noise. Once we know what we are seeking, the entire process of search, retrieval, analysis, and information extraction is even more stressful, time consuming and confusing.

Brevium is the preferred solution to follow topics, people and places of your choice and save time, it is built to address the core requirement of information filtering and summarization.

Brevium creates automatic text summaries of Web pages, articles and documents. Users can share on any device, anywhere and anytime.

Features
• Document with links to the original material.
• Summarizes multiple RSS feeds into one summary with links to the original RSS feeds.
• Distributes summaries via e-mail, or social network messages or postings.
• Summarizes reader comments and reviews—plus keyword and article topic lists.
• Integrates with enterprise content and document management systems.

Project Details

  • Date January 12, 2017
  • Tags Machine Learning, Web Application

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