Acknowledgements
Table V.11: Variation of Kendall-Tau-M (τm) correlation with #reviews with MAmazon (SVM-Rank).
['[BOLD] Domain', '[ITALIC] τm [BOLD]  with #reviews per-item ≤5', '[ITALIC] τm [BOLD]  with #reviews per-item ≤10', '[ITALIC] τm [BOLD]  with #reviews per-item ≤20', '[ITALIC] τm [BOLD]  with #reviews per-item ≤30', '[ITALIC] τm [BOLD]  with #reviews per-item ≤40', '[ITALIC] τm [BOLD]  with #reviews per-item ≤50', '[ITALIC] τm [BOLD]  with #reviews per-item Overall']
Ch4S3SS4SSSx3 Ch4S4SS1SSSx2 -Ch5S3SS1SSSx4 Ch5S3SS1SSSx7 -Ch5S3SS2SSSx3 Ch5S3SS2SSSx6 Ch5S3SS3SSSx4 Ch5S3SS3SSSx5 Ch5S4SS2SSSx2 -Ch5S4SS3SSSx3 Ch5T13 We observe that our model performs substantially well even with items having as few as five reviews, with the performance progressively getting better with more reviews per-item. Nevertheless, we observe it to give a substantial Kendall-Tau correlation (τm) with the reference ranking, with as few as five reviews per-item, demonstrating the effectiveness of our model in dealing with “long-tail” items.