How to cluster text-based software requirements
I recommend using word2vec as feature vector of words and LSTM autoencoder to encode a sentence (or text) . After you get a vector for each sentence (or text), you can cluster your sentences (or texts) using a variety of clustering techniques like k-means or dbscan and represent them using t-sne or u-map. Start from here:
https://blog.myyellowroad.com/unsupervised-sentence-representation-with-deep-learning-104b90079a93