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June 24, 2014

Linguamatics Launches I2E Semantic Enrichment

Linguamatics, a company that offers natural language processing (NLP)-based text mining solutions, recently launched I2E Semantic Enrichment, a solution that enhances the experience of enterprise search users by allowing them to retrieve more relevant results faster.

I2E Semantic Enrichment allows client’s existing enterprise level search engines (e.g. Microsoft (News - Alert) SharePoint, Apache Solr/Lucene) to consume documents with semantically enriched metadata. The solution’s powerful and agile NLP-based text analytics capabilities are used as part of the enterprise search workflow, to identify domain-relevant concepts such as genes, diseases, drugs and organizations and tag (News - Alert) them in a way that makes the search engine aware of their presence in documents. 

"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,” said Linguamatics Executive Chairman John M. Brimacombe in a press release. “The I2E Semantic Enrichment solution brings the benefits of the power of the I2E platform to tens of thousands of users. Sitting in the background, the I2E platform can transform the value of the enterprise search engine and allow organizations to protect and develop the major investment made in their system."

Few months ago, Linguamatics unveiled a new version of its software platform, I2E. Version 4.1 provides enhancements in a number of key areas, including more streamlined access to content through linking enterprise servers with content servers in the cloud, and enhanced chemical querying capabilities.

I2E's new Linked Server functionality facilitates easier access to text mining across different content silos wherever they might be located, whether in-house data or content served from the cloud, including from Linguamatics' own I2E OnDemand platform. This federated approach enables faster linking of extracted information from diverse unstructured data sources such as scientific literature, clinical data, patents and in-house information, leading to increased speed to insight.




Edited by Maurice Nagle
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