Text Analysis for Content Management
Interlink your organization’s data and content by using knowledge graph powered natural language processing.
Our Content Management solutions enable you to improve the discovery, organization and consumption of your content and unfold the value locked away in unstructured text. This empowers you to turn static documents into actionable data.
Verticals we benefit:
- Healthcare & Life Sciences
- Financial Industry Services
- Media & Publishing
- Public Sector & Defense
- Industry
How You’ll Benefit
Get value from information previously locked away in disconnected systems or in static content.
Utilize your enterprise data better to empower deeper insights.
Take advantage of text mining functionalities that happen on top of your data and content.
Make use of formalized knowledge about the world, provided by a custom knowledge graph.
Showcase Demonstrators
Ontotext’s Text Analysis for Content Management is based on off-the-shelf components, which we can also customize and extend to address the challenges specific to your business.
Whatever your use case or domain, we can help you apply your subject matter expertise to the data that is important to your organization.
Ivaylo Kabakov, Head of Semantic Analytics Solutions and Borislav Ankov, Project manager at Ontotext, talk about Text Analysis with Ontotext Platform.
How it Works
When building Content Management solutions, we need to go through the following 5 stages (optional steps are marked with *):
White Paper: Text Analysis for Content Management at Ontotext
5 Steps To Make Your Content Serve Your Business Better
Get started with your Text Analysis for Content Management today!
Features
Semantic Tagging
Discover mentions of known and novel concepts and link them to the relevant parts of your content.
Content Classification
Make use of context-sensitive analysis and classification for categorizing and organizing your unstructured content.
Content Recommendation
Suggest relevant related content based on the semantic fingerprint of your documents and the actions of your readers and their profiles.
Case Studies
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Increasing User Engagement in Publishing Platforms by Interlinking Ad Serving with Semantic Technology
Ontotext’s solution for smarter recommendations and ad serving enables a leading media publisher to know more about their content as well as their readers, improve its recommendation system, boost user engagement and adopt a sophisticated ad serving system that targets a more segmented audience.
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Ontotext’s GraphDB Powers a Leading STM Publisher’s Knowledge Platform
Ontotext helps a leading STM publisher to optimize the scientific data it provided for greater usability and to bridge the gap between isolated and fragmented information systems that hindered researchers from making new discoveries.
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Smart Adverse Media Monitoring Solution for Accelerating Negative News Disambiguation
Ontotext’s smart KYC Adverse Media Monitoring solution can ensure that multinational investment banks comply with regulatory requirements and are protected from reputational risk.
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Euromoney: Improving Content Production Through a Unified Semantic Publishing Platform
Euromoney’s BCA Research chose Ontotext technology in its quest to create a new publishing and information platform, which would include the latest authoring, storing, and display technologies including semantic search and an RDF triplestore.
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BBC Uses Semantic Publishing to Power the FIFA World Cup Website
In 2010, the BBC used Ontotext technology to bring a new approach to publishing and managing their content. In 2013, with Ontotext technology at its heart, the BBC went even further and developed its Linked Data Platform.
Our partnership with Ontotext has enabled a transformation of our business. The semantic enrichment of our large corpus of scientific data has enabled us, both to re-engineer our production operations for efficiency, but also to deliver new commercial opportunities for our customers. We have found working with the Ontotext team to be a stimulating and creative process that has helped to raise our skills and expertise.
Vincent Cassidy, Director of Academic Markets, The Institution of Engineering and Technology
Resource Center
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How We Do Text Analysis with Knowledge Graphs at Ontotext
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Human-computer Collaboration with Text Analysis for Content Management
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The Gold Standard – The Key to Information Extraction and Data Quality Control
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Metadata is Like Packaging: Seeing Beyond the Library Card Metaphor
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Texts Without Pages: Advancing Text Analytics with Content Enrichment
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Three’s Company Too: Metadata, Data and Text Analysis
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Text Analysis for Content Management: Demo, Offerings and Capabilities
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Analyzing Unstructured Data with GraphDB 9.8
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Turning a Taxonomy into a Recommendation Engine
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Smarter Content with a Dynamic Semantic Publishing Platform
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Best Practices for Large Scale Text Mining Process
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Adding Semantic Edge to Your Content – From Authoring to Delivery
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Do you want to explore how our Text Analysis for Content Management can be customized for your organization?
