This post follow my previous post From general search engine to value-added vertical search services. Below, I'm discussing some of the technologies that are generally implemented in Web 3.0 services.

Semantic Search Engine Definition :

“A semantic search engine is a search engine that takes the sense of a word as a factor in its ranking algorithm or offers the user a choice as to the sense of a word or phrase.”

Taking care of the meaning of a text corpus, semantic analyses enable the pre-treatment and filtering of search results :

- Search results clustering into thematic categories (categorization)

- Automatically adds tags to document description

- Displays additional stories linked to the document, even when the same keywords are not present

Semantic technologies play a very important role into vertical search engines as it allow to precisely organise the information among a finished number of dimension.

For instance Farechase.com, the travel search engine, organise its result among the following dimension : - Prices - Airlines - Departure Time - Flight duration - Direct flight or not

A sharp management of document context is almost impossible in a general search engine as it would be necessary to create as many index as specific point of views users would like to have to analyse data (example : Webfountain Technology from IBM).

Thesaurus Semantic analyses are based on thesaurus, a structured organisation of keywords. Thesaurus building and management will allow the definition of a semantic dimension of a document.

This structured organisation is hierarchic, but also transversal. Link between concepts is established in thesaurus. That's how general sense of a document is understood by artificial intelligence.

Concept extraction Semantic technologies is able to automatically recognise and extract concepts, based on different elements of a sentence : syntax, grammar, meaning, context... Thus, it is able to recognise specific entities, such as : - date - place - people - company - ........