Building the baseline approach

In this section, we will be building the baseline approach. We will use the scraped dataset. The main approach we will be using is TF-IDF (Term-frequency, Inverse Document Frequency) and cosine similarity. Both of these concepts have already been described in Chapter 4, Recommendation System for e-commerce. The name of the pertinent sections are Generating features using TF-IDF and Building the cosine similarity matrix.

As this application has more textual data, we can use TF-IDF, CountVectorizers, cosine similarity, and so on. There are no ratings available for any job. Because of this, we are not using other matrix decomposition methods, such as SVD, or correlation coefficient-based methods, such as Pearsons'R correlation. ...

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