Vector space model or term vector model is an algebraic model for representing text documents (and any objects, in general) as vectors of identifiers (such as index terms). It is used in information filtering, information retrieval, indexing and relevancy rankings. Its first use was in the SMART Information Retrieval System.
- Removing Stop-words
- Lemmatization
- Tokenization
- Creating Term Frequency Matrix
- Creating Document Frequency
- Calculating Tf-idf scores
- Cosine Similarity (alpha = 0.005 document greater then this score will be displayed)
- Ranking of Documents
- GUI (using PyQt) based implementation