Name
Abstract | ||
|---|---|---|
The high cardinality and sparsity of a collaborative recommender's dataset is a challenge to its efficiency. We generalise an existing clustering technique and apply it to a collaborative recommender's dataset to reduce cardinality and sparsity. We systematically test several variations, exploring the value of partitioning and grouping the data. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1007/3-540-45750-X_18 | AICS |
Keywords | Field | DocType |
sparsity reduction,collaborative recommenders,existing clustering technique,high cardinality,collaborative recommender | Data mining,Collaborative filtering,Computer science,Cardinality,Cluster analysis | Conference |
Volume | ISSN | ISBN |
2464 | 0302-9743 | 3-540-44184-0 |
Citations | PageRank | References |
5 | 0.84 | 1 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Derek G. Bridge | 1 | 850 | 73.07 |
| Jerome Kelleher | 2 | 44 | 6.91 |