Education and Publishing Technology 2018-03-13T16:29:20+00:00
OSU - Student Data Analytics

Technology for Education and Publishing – Content Delivery, Editorial and Production Systems

Give your content the visibility it deserves

Quantilus is helping education and publishing companies make the leap as the publishing world moves from paper-based to digital-only content. Quantilus provides end-to-end Educational and Publishing solutions –building innovative content delivery apps, streamlining the author-editor workflows, designing content models/taxonomy, configuring and implementing CMS solutions, authoring and editorial systems.

Do you need immersive and adaptive apps for students? Are your CMS investments looking like a black hole? Is the automated workflow system you just implemented turning into an impediment to your production process? Are you struggling to put structured authoring and editorial systems in place? Is your offshore editorial and production process costing way too much and resulting in too many errors? We have solved these problems many times over and can do it for you.

FEATURED WORK

Wiley Online Library - Content Delivery
Wiley Online Library – Digital Journals for Higher Education.
Wiley Online Library - Content Delivery
Wolters Kluwer - Content Management

Wolters Kluwer – CMS Solutions for Legal Content Publishing

Wolters Kluwer - Content Management
DASNY - Document Repository

Dormitory Authority of NY – Centralized Content Management Repository

DASNY - Document Repository
Triumph - Digital Learning Content

Triumph Learning – Learning Content and Interactive Assessments

Triumph - Digital Learning Content
Pearson System of Courses - K-12 Mobile App
Pearson System of Courses – Mobile Learning Platform for K-12 Classrooms
Pearson System of Courses - K-12 Mobile App
Edukate – Online Real-Time Video Tutoring Platform.
Morgan Stanley - Contract Management

Morgan Stanley – Contract Management and Workflow System

Morgan Stanley - Contract Management

TECHNOLOGY STACK

Some of the frameworks and tools that our development teams have used recently. A list that grows by the day.

RELATED RESEARCH

Relevant, interesting and current curated research content in the field.

Detecting Offensive Language in Tweets Using Deep Learning

January 5th, 2018|Categories: AI, NLP, Machine Learning, Content Mgmt and Publishing Tech|Tags: , , , , |

This paper addresses the important problem of discerning hateful content in social media. It proposes a detection scheme that is an ensemble of Recurrent Neural Network (RNN) classifiers, and it incorporates various features associated with user-related information, such as the users’ tendency towards racism or sexism. These data are fed as input to the above classifiers along with the word frequency vectors derived from the textual content. The scheme can successfully distinguish racist and sexist messages from normal text, and achieve higher classification quality than current state-of-the-art algorithms.

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