FAROO Real-time Search uses a crowd source approach to search.
Users are discovering and ranking new and relevant documents. Attention connectors to popular social services leverage a large base of attention data. FAROO deep crawls all discovered links and uses the number of votes, trust and reputation for ranking.
Social Noise Filter: Trust and reputation of the original source and the recommending middle man, the attention and popularity of information among the final consumer are analyzed in order to separate the relevant documents from noise.
Social Tagging: FAROO uses the collective intelligence and aggregates the tags from all users and all connected services for a specific document. Tags may be used as filters in the faceted search.
Rich Visual Preview: A teaser picture from the article is shown in front of the text summary. The author is displayed and can be used for filtering.
Sentiment Detection: FAROO detects and visualizes which kinds of sentiments have been triggered in the conversation.
RSS result feeds: Subscribing to the result streams allows applying any combination of the faceted search filters. The user is notified and browses through the news in his preferred feed reader.
Multi Language support: Due to the long tail most Internet users use different languages than English. FAROO provides language specific voting, ranking and searching together with a localized user interface.
Faceted Search: Various filters enable navigate a multi-dimensional information space by combining text search with a progressive narrowing of choices in each dimension. This allows narrowing, drill down, refining and filtering within large amounts of information.
