Summary of the paper
| Title | Using Random Indexing to improve Singular Value Decomposition for Latent Semantic Analysis |
|---|---|
| Authors | Linus Sellberg and Arne Jönsson |
| Abstract | In this paper we present results from using Random indexing for Latent Semantic Analysis to handle Singular Value Decomposition tractability issues. In the paper we compare Latent Semantic Analysis, Random Indexing and Latent Semantic Analysis on Random Indexing reduced matrices. Our results show that Latent Semantic Analysis on Random Indexing reduced matrices provide better results on Precision and Recall than Random Indexing only. Furthermore, computation time for Singular Value Decomposition on a Random indexing reduced matrix is almost halved compared to Latent Semantic Analysis. |
| Language | Language-independent |
| Topics | Information Extraction, Information Retrieval, Question Answering, Text mining |
Full paper |
Using Random Indexing to improve Singular Value Decomposition for Latent Semantic Analysis |
Slides |
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| Bibtex | @InProceedings{SELLBERG08.586, author = {Linus Sellberg and Arne Jönsson}, title = {Using Random Indexing to improve Singular Value Decomposition for Latent Semantic Analysis}, booktitle = {Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)}, year = {2008}, month = {may}, date = {28-30}, address = {Marrakech, Morocco}, editor = {Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Daniel Tapias}, publisher = {European Language Resources Association (ELRA)}, isbn = {2-9517408-4-0}, note = {http://www.lrec-conf.org/proceedings/lrec2008/}, language = {english} } |