Graph-based search emerged in 2012, when Google announced its new graph-based search algorithm. It promised more accurate search results, that were closer to a human response to a human question than before. In this section, we are going to talk about the different search methods to understand how graph-based search can be a big improvement for a search engine. We will then discuss the different ways to implement a graph-based search using Neo4j and machine learning.
Search methods
Several search methods have been used since search engines exist in web applications. We can, for instance, think of tags assigned to a blog article that help in classifying the articles and allow to search for articles with a given tag. This method is also used when you assign keywords to a given document. This method is quite simple to implement, but is also very limited: what if you forget an important keyword?
Fortunately, one can also use full-text search, which consists of matching...
