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SIGIR
2004
ACM

Polynomial filtering in latent semantic indexing for information retrieval

9 years 2 months ago
Polynomial filtering in latent semantic indexing for information retrieval
Latent Semantic Indexing (LSI) is a well established and effective framework for conceptual information retrieval. In traditional implementations of LSI the semantic structure of the collection is projected into the k-dimensional space derived from a rank-k approximation of the original term-by-document matrix. This paper discusses a new way to implement the LSI methodology, based on polynomial filtering. The new framework does not rely on any matrix decomposition and therefore its computational cost and storage requirements are low relative to traditional implementations of LSI. Additionally, it can be used as an effective information filtering technique when updating LSI models based on user feedback. Key words: Latent Semantic Indexing, Polynomial filtering
Effrosini Kokiopoulou, Yousef Saad
Added 30 Jun 2010
Updated 30 Jun 2010
Type Conference
Year 2004
Where SIGIR
Authors Effrosini Kokiopoulou, Yousef Saad
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