In this paper we present a theoretical model for understanding the performance of LSI search and retrieval applications. Many models for understanding LSI have been proposed. Ours is the first to study the values produced by LSI in the term dimension vectors. The framework presented here is based on term co-occurrence data. We show a strong correlation between second order term co-occurrence an...

The task of Text Classification (TC) is to automatically assign natural language texts with thematic categories from a predefined category set. And Latent Semantic Indexing (LSI) is a well known technique in Information Retrieval, especially in dealing with polysemy (one word can have different meanings) and synonymy (different words are used to describe the same concept), but it is not an opti...

That the scalar field theories with no dimensional couplings possess local scale invariance (LSI) via the curvature gauging is utilized to show that the Goldstone boson, released by the spontaneous LSI breakdown, is swallowed by the spacetime curvature in order to generate Newton’s constant in the same spirit as the induction of vector boson masses via spontaneous gauge symmetry breaking. For E...

Current methods used to assess gingivitis are qualitative and subjective. We hypothesized that gingival perfusion measurements could provide a quantitative metric of disease severity. We constructed a compact laser speckle imaging (LSI) system that could be mounted in custom-made oral molds. Rigid fixation of the LSI system in the oral cavity enabled measurement of blood flow in the gingiva. In...

One of the main themes in text mining is text representation, which is fundamental and indispensable for text-based intellegent information processing. Generally, text representation inludes two tasks: indexing and weighting. This paper has comparatively studied TF IDF, LSI and multi-word for text representation. We used a Chinese and an English document collection to respectively evaluate the ...

Current research in Latent Semantic Indexing (LSI) shows improvements in performance for a wide variety of information retrieval systems. We propose the development of a theoretical foundation for understanding the values produced in the reduced form of the term-term matrix. We assert that LSI’s use of higher orders of co-occurrence is a critical component of this study. In this work we present...

The main purpose of this paper is to propose a novel latent semantic indexing (LSI), statistical approach to simultaneously mapping documents and terms into a latent semantic space. This approach can index documents more effectively than the vector space model (VSM). Latent semantic indexing (LSI), which is based on singular value decomposition (SVD), and probabilistic latent semantic indexing ...

In Latent Semantic Indexing (LSI) has been proven to be a valuable analysis tool with a wide range of applications. However choosing an appropriate number of dimensions for LSI is still a crucial challenge. This paper provides a document vector model, by using weighting technology, to deal with this problem. Our experimental results have demonstrated that this model can detect a dataset structu...

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Insufficient lesion depth and discontinuity lines are reasons for reconnections after point-by-point radiofrequency pulmonary vein isolation (PVI). Different technologies have shown to be useful prediction effective lesions. Measurement the magnitude local tissue impedance drop (LID) calculation size index (LSI) based...

Documents retrieved in response to a user’s query should reflect the intention of the user. Keyword searches are not sufficient to accomplish this task. This paper considers Latent Semantic Indexing (LSI) as possible solution. LSI is considered in the context of a large set of World Bank documents. LSI is shown to be useful in this regard, but not a complete solution. Additional, domain specifi...