SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
CGLS-GCV: a hybrid algorithm for low-rank-deficient problems
Applied Numerical Mathematics - Special issue: 2nd international workshop on numerical linear algebra, numerical methods for partial differential equations and optimization
Clustered SVD strategies in latent semantic indexing
Information Processing and Management: an International Journal
The uncovering of hidden structures by Latent Semantic Analysis
Information Sciences: an International Journal
Two uses for updating the partial singular value decomposition in latent semantic indexing
Applied Numerical Mathematics
Extracting Key Entities and Significant Events from Online Daily News
IDEAL '08 Proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning
Clustered SVD strategies in latent semantic indexing
Information Processing and Management: an International Journal
Subspace tracking for latent semantic analysis
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Recommender systems: from algorithms to user experience
User Modeling and User-Adapted Interaction
| Hi-index | 0.00 |
We present a detailed analysis of matrices satisfying the so-called low-rank-plus-shift property in connection with the computation of their partial singular value decomposition (SVD). The application we have in mind is latent semantic indexing for information retrieval, where the term-document matrices generated from a text corpus approximately satisfy this property. The analysis is motivated by developing more efficient methods for computing and updating partial SVD of large term-document matrices and gaining deeper understanding of the behavior of the methods in the presence of noise.