Information filtering using latent semantics
β Scribed by Takeru Yokoi; Hidekazu Yanagimoto; Sigeru Omatu
- Publisher
- John Wiley and Sons
- Year
- 2008
- Tongue
- English
- Weight
- 337 KB
- Volume
- 165
- Category
- Article
- ISSN
- 0424-7760
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
## Latent semantic indexing (LSI) is a statistical technique As described by Swanson, there are two basic literature for improving information retrieval effectiveness. Here, discovery processes. The first leads from the literature we use LSI to assist in literature-based discoveries. The (R) associ
New text categorization models using back-propagation neural network (BPNN) and modified back-propagation neural network (MBPNN) are proposed. An efficient feature selection method is used to reduce the dimensionality as well as improve the performance. The basic BPNN learning algorithm has the draw
## Abstract Latent semantic analysis has been used for several years to improve the performance of document library searches. We show that latent semantic analysis, augmented with a PartβofβSpeech Tagger, may be an effective algorithm for classifying a textual document as well. Using Brille's Partβ