Certainly! Fuzzifying your data and implementing the fuzzy part and TF-IDF in Python can be done using several libraries and techniques. For fuzzification, you can utilize the scikit-fuzzy library, which provides various functions for fuzzy logic operations. You'll need to identify the variables and linguistic terms and design triangular membership functions accordingly. Then, using the fuzzy logic operators, you can fuzzify the data based on these membership functions. For TF-IDF, you can use the scikit-learn library, which offers a TF-IDF vectorizer to compute the TF-IDF scores for your textual data. You'll need to preprocess your text, tokenize it, and then apply the TF-IDF vectorizer to transform your data into numerical feature vectors. Once you have your fuzzy data and TF-IDF vectors, you can proceed with your querying using fuzzy TF-IDF. Implementing the entire code for your specific case is beyond the scope of a single paragraph, but I hope this guidance helps you get started on the right track.