Applications of clustering in NLP.
mediumAnswer
- (1) Topic modeling / document grouping (LDA, NMF, BERTopic).
- (2) Word sense discovery: cluster contextualized embeddings of ambiguous words.
- (3) Sentence deduplication in training data (embed + cluster + keep centroids).
- (4) User intent discovery in chatbot logs.
- (5) Named entity clustering across languages.
- (6) Query intent clustering for search.
- All exploit unsupervised structure discovery.
Check yourself — multiple choice
- Random
- Topic modeling / word sense discovery / training data dedup / user intent discovery / query intent clustering — unsupervised structure in text
- Same as classification
- Not real
NLP clustering: topics / senses / dedup / intent / query clusters.
#nlp#applications#clustering
Practise Unsupervised Learning
214 interview questions in this topic.