Name
Abstract | ||
|---|---|---|
We will present a new algorithm for improving the retrieval performance using query expansion, based on a hierarchy of clusters. In order to create this hierarchical data structure, a clustering algorithm is executed multiple times with different initial conditions. With the aid of this hierarchical data structure, we have achieved significant improvement in retrieval performance over previously known methods in terms of both recall and precision. In our experiments with Japanese patent data, we have employed a co-clustering algorithm as a clustering method. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11562382_37 | AIRS |
Keywords | Field | DocType |
retrieval performance,different initial condition,clustering method,japanese patent data,new algorithm,hierarchical data structure,clustering algorithm,multiple time,query expansion,co-clustering algorithm,initial condition | Hierarchical clustering,Data mining,Canopy clustering algorithm,CURE data clustering algorithm,Query expansion,Computer science,Hierarchical clustering of networks,Precision and recall,Cluster analysis,Hierarchical database model | Conference |
Volume | ISSN | ISBN |
3689 | 0302-9743 | 3-540-29186-5 |
Citations | PageRank | References |
3 | 0.58 | 5 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. Aono | 1 | 643 | 60.79 |
| Hironori Doi | 2 | 45 | 3.34 |