We present results from using Random Indexing for Latent Semantic Analysis to handle Singular Value Decomposition tractability issues. We compare Latent Semantic Analysis, Random ...
In this paper we present a study on music mood classification using audio and lyrics information. The mood of a song is expressed by means of musical features but a relevant part ...
We describe an entirely statistics-based, unsupervised, and languageindependent approach to multilingual information retrieval, which we call Latent Morpho-Semantic Analysis (LMSA...
This study explores how Latent Semantic Analysis (LSA) can be used as a method to examine the lexical development of second language (L2) speakers. This year long longitudinal stu...
Scott A. Crossley, Thomas L. Salsbury, Philip M. M...
Abstract. Spectral co-clustering is a generic method of computing coclusters of relational data, such as sets of documents and their terms. Latent semantic analysis is a method of ...
Laurence A. F. Park, Christopher Leckie, Kotagiri ...
Three methods for the efficient downdating, composition and splitting of low rank singular value decompositions are proposed. They are formulated in a closed form, considering the ...
The paper describes the initial results of applying Latent Semantic Analysis (LSA) to program source code and associated documentation. Latent Semantic Analysis is a corpus-based ...
Models of learning and performing by exploration assume that the semantic distance between task descriptions and screen labels controls in part the usersÕ search strategies. Neve...
The paper introduces an approach that organizes retrieval results semantically and displays them spatially for browsing. Latent Semantic Analysis as well as cluster techniques are...
In this paper, we present the results of a project that seeks to transform low-level features to a higher level of meaning. This project concerns a technique, latent semantic anal...