Clustering: a new feature of the Curebot monitoring platform
Market watchers are tasked with collecting a vast amount of information and analyzing it to extract useful insights for their company.
To help users of our intelligence platform find the nuggets in their information streams, we are working on several approaches to improve the efficiency of intelligence processes and reduce the time needed to scour each informational territory. In this way, intelligence teams working on complex projects involving large bodies of resources can devote more time to analyzing, producing and disseminating information.
A clustering engine for navigating large amounts of data.
The Curebot intelligence platform offers a clustering solution to automatically sort the information collected, enabling users to identify emerging trends in their field of activity.
The principle of clustering is to find similarities between information, using algorithms to group it into relevant clusters. Clustering offers an essential advantage for an intelligence analyst, enabling structured analysis and facilitating the understanding and interpretation of information flows. With this in mind, we've integrated an interactive Voronoi diagram displaying the results, so you can browse through resources on the same subject with just a few clicks.
This feature is a real asset when it comes to tracking industry trends, technological innovations and consumer preferences... By using clustering, companies can more easily identify growth opportunities and potential threats.
Detect weak signals.
Informational nuggets may be hidden in resources that have not been clustered. These may present important weak signals. In fact, clustering makes it possible to identify and bring together resources based on their similarities. When a weak signal appears, few resources exist around it, and there's a risk that they won't be clustered. It was therefore essential to provide you with access to information that might be of interest to you.
A customized, controlled clustering experiment.
This new feature analyzes a wide range of resources: an invaluable tool for watchmakers. Nevertheless, as with all automatic processing techniques, it's important to understand how the algorithms process your information.
"We adopt an ethical posture and pursue the goal of protecting you from the biases of artificial intelligence. We want to guarantee that you will be able to understand, control and choose the flows and actions that take place in Curebot."
To guarantee complete control, the Curebot monitoring platform integrates a system of filters and advanced cluster parameters for customized results and high clustering quality.
Several algorithms to suit your needs.
The effectiveness of clustering depends on the right choice of algorithm and parameters. In Curebot, several clustering algorithms are available, each with its own characteristics. By default, the monitoring platform is configured to offer you the algorithm and combination of parameters that will reasonably meet your needs. Although we provide tips and tricks to guide you through cluster optimization, there's no universal method for achieving the "best" results. We encourage you to experiment, evaluate and choose one of the models according to your analysis objectives.
You'll soon be using Curebot clustering to highlight strategic data and improve your overall understanding of your monitored environments.
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Would you like to find out more about clustering and discover how this feature can help you improve your intelligence workflow?
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