Q-Sensei 2.0

April 27, 2012

Q-Sensei adds features to its ontology-based search system, we learn in MarketWatch’s “Q-Sensei Enterprise V2.0 Unveiled to Rapidly Develop Tailored Search applications for Big Data.” Prominently featured are an ontology-based data processing/ configuration and a new API to more efficiently handle big data.

What’s an ontology? We keep forgetting. The dictionary says it’s “the branch of metaphysics that studies the nature of existence or being as such.” Wait, that can’t be right. . . . Ok, in information system lingo, ontology “formally represents knowledge as a set of concepts within a domain, and the relationships between those concepts.” That’s better.

The press release says the newest version of Q-Sensei’s enterprise search platform is designed to tailor search-based applications quickly and flexibly to the needs of its clients, using data from Intranets, social media, third parties, and the Internet. We learn from the write up:

“With Q-Sensei Enterprise’s new ontology-based data processing, businesses can rapidly develop new, tailored search-based applications by using existing RDF and OWL resources such as database models, industry or domain-specific ontologies, process definitions and project configurations. This new processing approach also enables harmonization of semantics, components and functionality across business applications. It also improves the speed and efficiency of data process and indexing, increasing platform performance.”

Version 2.0 also boasts a semi-automatic, guided configuration and a new API that makes it easier to integrate Q-Sensei into other applications.

Q-Sensei was created in 2007 with the merger of the German Lalisio and the American QUASM, and now has offices in both Brooklyn and Erfurt, Germany. Q-Sensei focuses on multi-dimensional search, which it defines as combining full-text and dynamic faceted search with real-time content analysis. The company maintains that its solutions make it easy to find what you need, even if you don’t have the appropriate keywords on hand.

Cynthia Murrell, April 27, 2012

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Stephen E. Arnold monitors search, content processing, text mining and related topics from his high-tech nerve center in rural Kentucky. He tries to winnow the goose feathers from the giblets. He works with colleagues worldwide to make this Web log useful to those who want to go "beyond search". Contact him at sa [at] arnoldit.com. His Web site with additional information about search is arnoldit.com.