Nstein Technologies has released a front-end, multi-index search engine Semantic Site Search (3S), which leverages the company’s text-mining technology to power a faceted site search which returns accurate results that are organised categorically.
The company said that the new offering can ingest content from many different indices from different web publishing platforms. It then applies Nstein’s semantic enrichment process to it.
The 3S embedded text mining engine (TME) identifies concepts, categories, proper names, places, organisations, sentiment and topics in particular content pieces and then annotates those documents, creating a semantic fingerprint that exposes underlying nuances and meaning in content, the company said.
According to Nstein, 3S is configurable and customisable, and boasts a visual interface that allows administrators to tweak search sensitivity algorithms without having to modify hard code. It comes bundled with front-end widgets designed to improve the search experience.
Widgets can be used to point users to similar content, most recent content, or virtually any other identifying characteristic of content that one wants to promote. Using widgets and the templating engine, integrators can build complex search-based mashups across indices, Nstein said.
Jean-Michel Texier, CTO of Nstein, said: When a user submits a search query to 3S they are returned highly accurate, faceted results organised by topics and entities. This has the effect of offering users very relevant related content, ensuring that they not only find what they’re looking for but also discover other valuable content.
Ultimately, 3S is more than just a perfect companion for our web-publishing platform WCM. Its embedded architecture and built-in crawler mean it’s ready to deploy, to index and search any web property, no matter how much content there is. We’re really quite proud of the teamwork that went into developing 3S.