Blog

(Cambridge, UK and Boston, USA- 18 March 2014) Linguamatics’ sales showed strong growth and exceeded ten million dollars in 2013, it was announced today - outperforming the company’s targeted growth and expected sales figures.  The increased sales came from a boost in new customers and increased software licenses to existing customers in the pharmaceutical and healthcare sectors. This included 130 per cent growth in healthcare sales plus increased sales in professional services.

Access to the right knowledge at the right time is crucial for knowledge driven organizations such as those in healthcare and pharmaceuticals. Linguamatics software platform, I2E, uses natural language processing (NLP) to go beyond conventional search methods and understand the meaning of text.

I2E identifies and extracts facts, assertions and relationships from unstructured text such as scientific literature, patents, clinical trials data, electronic health records (EHR), news feeds, social media and proprietary content in real-time and puts them into a structured format for further analysis to support key decision-making.

I2E delivers dramatically improved speed to actionable insight, using computer algorithms to automatically mine, analyze and connect relevant knowledge buried in vast amounts of textual data and generate higher quality, targeted results.

Linguamatics' customers include 16 of the top 20 global pharmaceutical companies, the US Food and Drug Administration (FDA), leading US hospitals, cancer institutes and academic research centers.


Although I2E Queries and Multi Queries are binary objects, the I2E Web Services API provides an interface to a subset of the properties of those items, including some that can be modified when running a query programmatically.

Query properties that are read-only and that can be retrieved using the API include title, creator, comments and column headers. Query properties that can be modified before query submissions include number of hits, time limit and smart query parameters.

I2E has two, related, query resources: Saved Queries (that represent the binary files on disk, stored in the Repository) and Published Queries (that represent the Published location of the Saved Queries). To ensure that Users have permissions to see Query Properties, it is recommended that you only expose access to Published Queries.

Retrieving (by GET) a Published Query provides a “handle” to the Saved Query:

HTTP Header = X-Version: *, Accept: application/json GET http://i2e.company.com:8334/api;type=published_query/QueryTree/Query1.i2q Success 200

The response should look something like:

{
“shared”: true,
“valid”: true,
“handle”: “/api;type=saved_query/4.1/Query1.i2q”,
“error”: null,
“editable”: true
}

 

If you then retrieve that handle, you will receive an error because the server is trying to represent the query itself as JSON

HTTP Header = X-Version: *, Accept: application/json GET http://i2e.company.com:8334/api;type=saved_query/4.1/Query1.i2q Error 406
 


Linguamatics, the market-leader in natural language processing (NLP)-based text mining and analytics, today announced that it has been named in KMWorld’s list of “100 Companies That Matter in Knowledge Management”.

(Cambridge, England and Boston, USA – February 25, 2014) Now in its 14th year, the KMWorld 100 Companies That Matter list is compiled by KM practitioners, theorists, analysts, vendors and their customers and colleagues.

The annual list is a collaborative snapshot of the evolving and expanding knowledge management industry.

Linguamatics’ agile NLP text mining software, I2E, provides rapid knowledge discovery from unstructured text. In this era of “Big Data”, organizations face the challenge of filtering ever-increasing volumes of text information to gain actionable insights for key decision-making.

Using I2E, knowledge can be extracted from a wide range of content sources such as scientific literature, patents, clinical trials data, electronic health records (EHRs), news feeds and proprietary content. This knowledge can then be used to answer high-value questions in real time.

“Linguamatics has proven to define the spirit of practical innovation by blending a best-in-breed natural language processing (NLP) text mining platform with a deep, fundamental commitment to customer success" says Hugh McKellar, KMWorld editor-in-Chief.

“It is an honour to be recognized by KMWorld as one of the 100 companies that matter in knowledge management,” explained John M. Brimacombe, Executive Chairman, Linguamatics.


More than 35,000 healthcare industry professionals are expected to attend the 2014 Annual HIMSS Conference & Exhibition in Orlando to discuss health IT issues and view innovative solutions designed to transform healthcare.

Linguamatics is proud to be an exhibitor at this annual event that helps health IT professionals find the right solutions for their organizations.

Hillary Clinton, 67th Secretary of State of the United States, leads a keynote roster that also includes Mark Bertolini, chairman, CEO and president of AETNA, and Erik Weihenmayer, a world-class blind adventurer.

On the exhibit floor, the enhanced HIMSS Interoperability Showcase will feature an interactive environment where health IT solution providers can collaborate to maximize the collective impact of their technologies and connect with decision makers.

Linguamatics will showcase its leading clinical Natural Language Processing platform, which transforms the unstructured text from electronic health records into patient insights. Demonstrations include information extraction from pathology reports and patient narratives, and matching patients to clinical trials based on inclusion and exclusion criteria.

To learn more about Linguamatics, visit us at booth #1794 during HIMSS14, February 23-27, 2014, at the Orange County Convention or take a look through our website.

For more information about HIMSS14 and to register, visit www.himssconference.org.


I saw this comment in a recent article by Seth Grimes, where he discusses the terms Text Analysis and Text Analytics.

Within the article Mr. Grimes states that text mining and text analytics are largely interchangeable terms:

“The terms “text analytics” and “text mining” are largely interchangeable. They name the same set of methods, software tools, and applications. Their distinction stems primarily from the background of the person using each — “text mining” seems most used by data miners, and “text analytics” by individuals and organizations in domains where the road to insight was paved by business intelligence tools and methods — so that the difference is largely a matter of dialect.”

Ref: Seth Grimes at the Huffington Post.

I asked Linguamatics CTO, David Milward, for his thoughts:

"There is certainly overlap, but I think there are cases of analytics that would not be classed as text mining and vice versa. Text analytics tends to be more about processing a document collection as a whole, text mining traditionally has more of the needle in a haystack connotation.

"For example, word clouds might be classified as text analytics, but not text mining. Use of natural language processing (NLP) for advanced searching is not so naturally classified under text analytics.