… Latent Semantic Indexing (LSI) is a conceptual indexing technique which uses the truncated
SVD to estimate the underlying latent semantic structure of word to document association. …

… Perhaps a more interesting approach is to employ Latent Semantic Indexing (LSI), another
computer-based enhancement being explored in our laboratory [5, 6]. Using LSI, it may be …

… semantics" analyses was Latent Semantic Indexing (LSI). Latent Semantic Indexing uses a
powerful … Latent semantic indexing seems to capture important aspects of human relevance …

A significant problem in many information filtering systems is the dependence on the user
for the creation and maintenance of a user profile, which describes the user's interests. …

… Unsupervised learning by probabilistic latent semantic analysis. Mach. Learn., vol. …
Learning object categories from google's image search. In Proceedings of the Tenth IEEE …

Schone P Jurafsky D (2000) Knowledge-free induction of morphology using latent semantic
analysis Proceedings of the 2nd workshop on Learning language in logic and the 4th …

… There is little or no coverage of some other important IR topics, such as clustering, NLP,
TREC, and latent semantic indexing. There is little emphasis on implementation techniques, …

… Google’s machine translation team also adopted the attention structure for the machine …
For each basic block, the convolution layer extracts the latent semantic features of the image, …

Publisher Summary Models are approximations to objects or processes that maintain some
essential aspects of the original. In cognitive psychology, mental models are usually …

Publisher Summary Computation provides the most plastic representational medium and for
that it can be employed to mimic successful mechanisms of earlier media and also enables …

This article extends earlier research concerning the relationship between corporate social
performance and corporate financial performance, with particular emphasis on …

… Google Research Scholar Award … Multi-relational latent semantic analysis. Conference on
Empirical Methods in … - Multi-Relational Latent Semantic Analysis by Tensor Decomposition …

Secondary growth of an oriented precursor film of zeolite A results in an intergrown, continuous,
thin (500 nm), and highly oriented film consisting of zeolite grains with the (h00) planes …

Using simple scaling arguments and a precursor film model, we show that the appropriate
macroscopic contact angle θ during the slow spreading of a completely or partially wetting …

The addition of enolates derived from indole-3-acetic esters 1−3 to pyridinium salts 4, 23,
and 24, followed by acid cyclization of the resulting 1,4-dihydropyridines, leads to tetrahydro-1,…

5-Aminolevulinate synthase (EC 2.3.1.37) is the first enzyme in the heme biosynthetic pathway
of animals, fungi and some bacteria. It functions as a homodimer and requires pyridoxal 5‘…

… Google Scholar … Indexing by latent semantic analysis … Information retrieval using a
singular value decomposition model of latent semantic structure …

… Garcia, E., SVD and LSI Tutorial 4: Latent Semantic Indexing (LSI) How-to Calculations, Mi
… Langville AN, CD Meyer, Google’s PageRank and Beyond: The Science of Search Engine …

One of the most important decisions that can be made in the use of factor analysis is the
number of factors to retain. Numerous studies have consistently shown that Horn's parallel …

Several researchers have demonstrated how complex action sequences can be learned
through neuroevolution (ie, evolving neural networks with genetic algorithms). However, …