Impact of Distance Measures on Urdu Document Clustering
Impact of Distance Measures on Urdu Document Clustering
Zarmeen Nasim,Sajjad Haider
2022 · DBLP: conf/paclic/NasimH22
Pacific Asia Conference on Language, Information and Computation · 2 Citations
TLDR
Empirically evaluates four distance measures: Euclidean, Manhattan, Cosine, and Pearson Correlation, on Urdu news headlines, and the stemming technique was identified to be more useful in contrast to lemmatization for clustering news.