Sinequa enhances with Machine Learning

Sinequa has announced a new release of its Search & Analytics platform, Sinequa ES Version 10, featuring new machine learning capabilities.

The Machine Learning algorithms continually analyse and enrich the content of the Sinequa Logical Data Warehouse. The new Cognitive Search & Analytics platform offers better insights and more relevant information to meet users' expectations.

"This new version is a leap forward into the era of 'cognitive computing' or 'insight engines,' to use the terminology coined by leading market analysts", stated Alexandre Bilger, CEO, Sinequa.

"In dealing with Big Data and its rapid growth, leading data-driven organizations need to rely on intelligent and self-learning systems to analyse data and find valuable information for their employees, thus increasing their productivity and job satisfaction, and the company's competitiveness. Our Machine Learning capabilities achieve these goals by including Collaborative Filtering and Recommendations, Classification by Example, Clusterisation and Similarity calculations for unstructured contents, and Predictive Analysis."

Industry specific dictionaries and ontologies from partners like Scibite and Linguamatics have been integrated for users in Life Science and Health Care. Google Vision and Microsoft Azure Media Services are also leveraged in order to deal more effectively with images as well as videos. Google Translate is used for automated translation between over 100 languages.