As part of the artificial intelligence (AI) machine learning (DL) model, tech giant Google has invested considerable energy in data sets searches. As a dedicated search engine, it can combine millions of data sets. After about a year of effort, Google has finally completed the phase-testing of its data set search capabilities. It also brings many new features based on feedback from early testers.
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First, like most search engines, data set search is now available on mobile devices. Second, users can filter search results based on the type of data they want, such as displaying only images, text, tables, prices, and so on.
Third, the quality of search results has also been improved to show more information. For example, if the dataset in the search results belongs to a geographic area, the corresponding map is displayed in the description.
Finally, regardless of the stage at which Dataset Search has been developed, Google continuously improves its products based on user feedback. To date, the feature has indexed approximately 25 million datasets.
Interested data publishers and users who want their data to appear in search results can describe the properties of their datasets on a particular page (schema.org) through open standards.