It is widely believed that Web search engines require immense resources to operate, making it impossible for small communities to build alternatives to the dominant players. The PeARS project (https://pearsproject.org/) aims at changing the status quo by providing open-source search tools that can be used by anyone, anywhere. To achieve this, our team designs algorithms that run on entry-level hardware, using both traditional and cutting-edge machine learning techniques.
This talk will focus on a specific use case for PeARS, showing how the framework can easily be deployed to provide regional search solutions: for instance for local governments, small business communities, or minority speaker groups. We will see how the system can be trained and populated on a home computer in a few clicks and how it can be tailored to the specific community it is addressed to.
The project has received funding from the European Union under the Next Generation Internet programme.
