latent semantic analysis
Monocular 3D Human Motion Tracking Using Dynamic Probabilistic Latent Semantic Analysis
... We have proposed a novel method for learning models from sequential dyadic data called the Dynamic Probabilistic Latent Semantic Analysis (DPLSA). DPLSA extends the successful PLSA formalism to a ...
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FLSA: Extending Latent Semantic Analysis with Features for Dialogue Act Classification
... Feature Latent Semantic Analysis (FLSA) as an extension to Latent Seman- tic Analysis ...a semantic space where words and passages are represented as ...the semantic space ...
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Text Summarization of Turkish Texts using Latent Semantic Analysis
... Text summarization solves the problem of extracting important information from huge amount of text data. There are vari- ous methods in the literature that aim to find out well-formed summaries. One of the most commonly ...
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Enhancing Multilingual Latent Semantic Analysis with Term Alignment Information
... Latent Semantic Analysis (LSA) is based on the Singular Value Decompo- sition (SVD) of a term-by-document matrix for identifying relationships among terms and documents from co- occurrence ...
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Automated Essay Scoring Using Generalized Latent Semantic Analysis
... technology. Latent Semantic Analysis (LSA) is an Information Retrieval (IR) technique used for automated essay ...Generalized Latent Semantic Analysis (GLSA) which makes n-gram ...
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Unsupervised Activity Recognition using Latent Semantic Analysis on a Mobile Robot
... use Latent Semantic Analysis (LSA) [13] to recover latent con- cepts, effectively semantically clustering qualitative features which commonly co-occur ...
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Topic-based Multi-Document Summarization with Probabilistic Latent Semantic Analysis
... probabilistic latent semantic analysis, which allows us to represent sentences and queries as probability distributions over la- tent ...the latent topic space to estimate the summary- ...
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Category fluency, latent semantic analysis and schizophrenia: a candidate gene approach
... Latent Semantic Analysis (LSA) is a statistical approach to the acquisition and representation of meaning, which allows similarities among the elements of a language ...dimension semantic ...
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Text Summarization within the Latent Semantic Analysis Framework: Comparative Study
... Latent Semantic Analysis (LSA) is used in many applications ...space semantic representation from a large corpus of data[3], which doesn't need any training or external ...
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Image Classification Based on Effective Probabilistic Latent Semantic Analysis Model
... In this paper, a novel method for classification of rock images has been proposed. The features of the rock images are very well extracted by Tamura features. These features are applied to probabilistic latent ...
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Positioning for Conceptual Development using Latent Semantic Analysis
... 2007). Latent semantic analysis is one of many possible techniques that can be facilitated to sup- port or even partially automate the analysis of in- formal ...
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Term Categorization Using Latent Semantic Analysis for Intelligent Query Processing
... A system for competent unsupervised example for population count proposed by Theerayut Thongkrau et al., 2010[12], the new instances are classified according to their equivalent lexical ontology concept. In relation to ...
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An Evaluation of Projection Techniques for Document Clustering: Latent Semantic Analysis and Independent Component Analysis.
... are Latent Semantic Analysis (LSA) and Independent Component Analysis ...of latent semantic structure inaccessible in the original document representations (Deerwester et ...This ...
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Application of latent semantic analysis for open-ended responses in a large, epidemiologic study
... [6,10,13-20]. Latent Semantic Analysis is a techni- que to transform qualitative data into quantitative information, but it has limitations, including situations where meaning is determined ...
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Learning Comparable Corpora from Latent Semantic Analysis Simplified Document Space
... the Latent Semantic Analysis tech- nique, which matches concepts, or information units, from one document to another instead of approximating word ...the latent rela- tionships between the ...
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Refining Search Queries From Examples Using Boolean Expressions and Latent Semantic Analysis
... To evaluate the success of this approach, some sample search-based tasks were identified. A query with a single term (a naïve query) was initially generated to retrieve links to documents which may be of interest. The ...
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Practical use of a latent semantic analysis (LSA) model for automatic evaluation of written answers
... This paper presents research of an application of a latent semantic analysis (LSA) model for the automatic evaluation of short answers (25 to 70 words) to open-ended questions. In order to reach a ...
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Image classification based on sparse coding multi-scale spatial latent semantic analysis
... different semantic categories have become a key issue in image semantic ...spatial latent semantic analysis method based on sparse coding has higher average classification accuracy than ...
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Summarizing Health Review using Latent Semantic Analysis
... The amount of reviews is written by health consumer for health service supplier is growing every day. Text summarization reduces info as a shot to alter users to seek out and perceive relevant services of a health ...
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Multi Relational Latent Semantic Analysis
... Tensor decomposition generalizes matrix factor- ization and has been applied to several NLP applica- tions recently. For example, Cohen et al. (2013) pro- posed an approximation algorithm for PCFG pars- ing that relies ...
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