I am looking for a machine learning algorithm for my problem.
I have a set of sentences like,
["The cat in the hat disabled", "A cat is a fine pet ponies.", "Dogs and cats make good pets.","I haven't got a hat."]
and the search-words like,
I want to convert my sentence list and search-words to a vector space and find matching score between my sentence list and search-word list.
the type of output I am expecting is,
[("The cat in the hat disabled",0.9), ("A cat is a fine pet ponies.",0.5), "(Dogs and cats make good pets.",0.6),("I haven't got a hat.",0.49)]
Please suggest a machine learning algorithm for my task, if possible please share a reference link.
let me know if you have any queries or need more information. I am currently using semanticpy for this https://github.com/josephwilk/semanticpy
I am getting key-error for many search-words. its not performing stemming and lemmatization for the sentence list but only performing for the search-words list.
Please help on this.