Tapping into academic content using the Academic API

Microsoft Academic Graph (MAG) is a knowledge base for web-scale, heterogeneous entity graphs. Entities model scholarly activities, containing information such as field of study, author(s), institution, and more.

Data contained in MAG is indexed from the Bing web index. As this is continuously indexed, the data is always up to date.

Using the Academic API, we can tap into this knowledge base. Combining search suggestions, research paper graph search results, and histogram distributions, the API enables a knowledge-driven and interactive dialog.

When a user searches for research papers, the API can provide query completion. It may suggest queries based on the input. With a complete query, we can evaluate a query expression. This will retrieve a set of matching paper entities from the knowledge base.

Setting up an example project

To be able to test the Academic API, we want to create a new example project. Create this from the MVVM template created...