Latent semantic indexing is an optimal special case of multidimensional scaling
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Large-scale information retrieval with latent semantic indexing
Information Sciences: an International Journal
A semidiscrete matrix decomposition for latent semantic indexing information retrieval
ACM Transactions on Information Systems (TOIS)
A similarity-based probability model for latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Latent semantic space: iterative scaling improves precision of inter-document similarity measurement
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Emergent semantics and the multimedia semantic web
ACM SIGMOD Record
Information retrieval and filtering using the reimannian svd
Information retrieval and filtering using the reimannian svd
Techniques for improved lsi text retrieval
Techniques for improved lsi text retrieval
Narrowing the semantic gap - improved text-based web document retrieval using visual features
IEEE Transactions on Multimedia
Privacy-preserving similarity-based text retrieval
ACM Transactions on Internet Technology (TOIT)
A semantic-based P2P resource management system
CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 3
A comparative study of TF*IDF, LSI and multi-words for text classification
Expert Systems with Applications: An International Journal
Temporal Link Prediction Using Matrix and Tensor Factorizations
ACM Transactions on Knowledge Discovery from Data (TKDD)
Fast dimension reduction for document classification based on imprecise spectrum analysis
Information Sciences: an International Journal
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This paper presents an analysis of several different LSI (latent semantic indexing) query approaches and proposes a novel rescaling technique, namely singular value rescaling (SVR). Experiments on a standardized TREC data set confirmed the effectiveness of SVR, showing an improvement ratio of 5.9% over the best conventional LSI query approach. In addition, we also compared SVR with another scaling technique in text retrieval called iterative residual rescaling (IRR). Experiments on TREC data set show that SVR performs better than IRR.