Item-to-item recommendation

Hi All,

I am new to DNN still learning, have a need to build item-to-item content-based recommendation using DNN. For example, say I have a column of strings where each row represents a document I need to compute the cosine similarity of this column and recommend similar documents.

id. document

1 “hi this document is about science”
2 “hi this document is about wars”
3 “This document is about peace”

now need to train based only on document column and recommend all the documents similar to a given document. I have solved this problem by using cosine similarity in ML now wanted to achieve the same in DNN (Deep Neural Nets).

The lessons 08 collaborative filter expects the dataset to have userID, title, ratings but I only have the document. How can I fix this problem?