Semantic Publishing – Relevant Recommendations Create a Unique User Experience

Semantic Publishing includes a number of techniques including semantic recommendations used to personalize the user experience by delivering contextual content based on natural language processing, search history, user profiles and semantically enriched data.

Finding things quickly is one of the things we all like about Google.  When we search using Google, we typically find what we are looking for.  What if your organization had the same powerful search and discovery capabilities?

Today more than ever, companies struggle with search and discovery.  Massive volumes of unstructured data contain meaning but it’s hard to find in all the noise?  Policy analysts search through compliance documents.  Authors search through historical content.  Clinical trials researchers cull through Mount-Everest-like text relating to drugs, adverse effects, research and more.   It never seems to end.  But what if you could find the exact document, the precise paragraph and the perfect reference to a specific topic instantly?  Better yet, what if your web site visitors could do that as well?

It’s all possible.  In fact, this is being done by some of the largest media, publishing, pharma and government organizations in the world.   The application of semantic technology to accomplish this goal manifests itself in many ways.   For internal users you gain access to relevant content enabling you to do your job faster.   External users find exactly what they need – relevant, contextual content personalized for them.

This is much more than simple content tagging.   When you decompose this process and technology, what you find is that semantic recommendation engines are analyzing a lot of data.  For starters, they know the web visitor profile and search history.  But operating behind the scenes is much deeper semantic technology that extracts concepts and entities from the articles viewed. Results (semantic triples or “RDF statements”) are stored in a high performance triplestore (graph database)  search, analysis and discovery purposes.  The magic happens when the profile and search history are matched to the newly structured semantic facts and the current search criteria.

At Ontotext we call this semantic recommendations (a subset of semantic publishing) because our customers are able to instantly deliver highly relevant, recommended articles.  At the same time hundreds of queries per second are taking place on your website, authors can be enriching new content which is committed to the database and available for the next search.  Simultaneously, text is being processed, entities are classified and the same person with different name spellings are being identified and stored.

This semantic wizardry is known as semantic annotation which has a series of techniques at its core.  Semantic enrichment allows users to enrich entities with valuable information used in identity resolution and search.  Dynamic semantic publishing assembles and delivers personalized web pages using a variety of unstructured data types and semantic facts about the people, places or organizations that the visitor is searching for.  Semantic curation prompts authors or researchers with relevant curated content as they write.   We could go on and on…

The bottom line on all of this is one word:  Productivity.   Everyone wins.  Researchers find content faster.   Decision makers are accurately informed using a combination of real world facts and their own data.  Writers produce more content. Web site visitors get recommendations they never thought were possible.   You can learn more about all of our semantic technology, semantic publishing and semantic recommendations at www.ontotext.com.

 

Milena Yankova

Milena Yankova

Director Global Marketing at Ontotext
A bright lady with a PhD in Computer Science, Milena's path started in the role of a developer, passed through project and quickly led her to product management.For her a constant source of miracles is how technology supports and alters our behaviour, engagement and social connections.
Milena Yankova

Related Posts

  • Featured Image

    Top 5 Semantic Technology Trends to Look for in 2017

    To help machines understand the meaning of concepts, which enables businesses to gain competitive advantage by turning raw data into knowledge, Ontotext has been developing and offering semantic technologies for years. Now that we’re rolling into 2017, we’ve identified these top 5 trends in which semantic technology helps enterprises make sense out of data and fine-tune offerings to customers.

  • Featured image Blogpost

    Ontotext’s 2016: What Did You Liked The Most On The Blog

    It’s been a busy year for Ontotext and a very successful one. As 2016 comes to an end we decided to have a re-cap. Since it is hard for us to choose only five best articles we…

  • Featured image

    The Knowledge Discovery Quest

    Surrounded by millions of bits of information, in today’s digital world we are on a knowledge discovery quest. On this quest semantic search is key. It helps us explore connections and gather information from seemingly disparate sources.…

Back to top