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Today, Linguamatics launches I2E Semantic Enrichment to provide increased return on investment in enterprise search systems and radically improve speed to insight.

I2E Semantic Enrichment is used within an existing enterprise search deployment to enrich the current data, make it more discoverable and provide more relevant search results.

The software scans millions of documents to identify and mark-up semantic entities such as genes, drugs, diseases, organizations, authors and other relevant concepts and relationships. Enterprise search engines consume this enriched metadata to provide a faster, more effective search for users.

I2E uses natural language processing (NLP) technology to find concepts in the right context, combined with a range of other strategies including application of ontologies, taxonomies, thesauri, rule-based pattern matching and disambiguation based on context. This allows enterprise search engines to gain a better understanding of documents in order to provide a richer search experience and increase findability, which enables users to spend less time on search.

Synonyms allow the user to find all relevant results, not just those containing the exact word. I2E also provides rich, multi-level facets for the search engine to help the user filter down to the most relevant results across the areas of interest (e.g. disease, drug class, etc).

Linguamatics Executive Chairman John M. Brimacombe commented "It's no secret that enterprise search hasn’t quite lived up to expectations, with users struggling to find the information they need and organizations dissatisfied with their search solutions.


It’s always good to see NLP being used in a clinical care, a recent story about Microsoft and Washington University in Seattle using NLP in pneumonia detection in the ICU is a good example of this.

The project, called deCIPHER, uses a combination of Microsoft linguistics and machine learning to assess clinical information from electronic medical records and derive a diagnosis.

The system was trained against a cohort of 100 patients who had already been diagnosed with pneumonia and used a machine learning framework to build a predictive model based on extracted clinical factors. The system accurately predicted 84% of positive patients and the team are assessing incorporating the model into an ICU dashboard.

Last year Kaiser Permanente also published a paper on pneumonia diagnosis in relation to the ICU and using chest radiograph reports, using Linguamatics I2E for information extraction and also applying machine learning to the resulting clinical factors.

From a total of 194,615 ICU reports, Kaiser Permanente empirically developed a lexicon to categorize pneumonia-relevant terms and uncertainty profiles.


New product release allows tens of thousands of enterprise search users to benefit from the power of Linguamatics’ market-leading technology.

(Cambridge, England and Boston, USA – June 19, 2014) Today, Linguamatics launches I2E Semantic Enrichment to provide increased return on investment in enterprise search systems and radically improve speed to insight.

I2E Semantic Enrichment is used within an existing enterprise search deployment to enrich the current data, make it more discoverable and provide more relevant search results.

The software scans millions of documents to identify and mark-up semantic entities such as genes, drugs, diseases, organizations, authors and other relevant concepts and relationships. Enterprise search engines consume this enriched metadata to provide a faster, more effective search for users.

I2E uses natural language processing (NLP) technology to find concepts in the right context, combined with a range of other strategies including application of ontologies, taxonomies, thesauri, rule-based pattern matching and disambiguation based on context.

This allows enterprise search engines to gain a better understanding of documents in order to provide a richer search experience and increase findability, which enables users to spend less time on search.

Synonyms allow the user to find all relevant results, not just those containing the exact word. I2E also provides rich, multi-level facets for the search engine to help the user filter down to the most relevant results across the areas of interest (e.g. disease, drug class, etc).


You can read the article, here.


I2E 4.2 introduces integrated visualization for improved analysis and semantic enrichment capabilities for integration with enterprise search engines.

(Cambridge, UK and Boston, USA – 19 May 2014) Linguamatics announces the latest release of its award-winning natural language processing (NLP)-based text mining and analytics platform I2E. I2E 4.2 further enhances users' experience by introducing integrated charting and graphing to provide visual analytics for results extracted from large volumes of unstructured data.

I2E 4.2 includes new capabilities to support the integration of semantically enriched data into enterprise search engines to enhance the search experience for a wider audience.

The integrated visualization capabilities in I2E 4.2 will allow users to gain a comprehensive view of large or complex data sets with the ability to filter down to the information of most interest, making it easier to access the most important information faster and share results throughout the organization thus enabling more rapid decision support and increased speed to insight.

The new semantic enrichment functionality enables I2E to automatically identify and mark up concepts and relationships within data already used by enterprise search engines and link these to I2E's powerful domain knowledge to provide dramatically improved search results.

David Milward, Linguamatics CTO, commented "We are now working to a shorter release cycle, allowing us to respond in a more agile way to customer requirements.

We’re excited about the increasing demand for I2E in semantic enrichment for enterprise search platforms such as Microsoft SharePoint, and have delivered dedicated functionality to support that".