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The Trend Detection service can now be used with the Squirro client. The Trend Detection analysis can be used to detect unusual trends in the time series generated by the number-of-items per time-unit in a particular project for a particular query. The detection of unusual trends is done by learning from the historical/old data to auto-compute a reasonable threshold. So, in order for it to work properly it is important that we have historical data.
As an example scenario, consider a project `News` with a feed of all the news-items from a few of the major news publications. Now, a query like `Facebook AND Whatsapp` will filter the list of all the documents to a sub-list of documents/news-items containing both the words Facebook and Whatsapp. For the project `News` with query `Facebook AND Whatsapp`, we define a time-series as the number of items matching `Facebook AND Whatsapp` per time-unit, where time-unit can be hourly, weekly, daily, monthly and or yearly.
How to set up Trend Detection?
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