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The paper presents a new multiple feature fusion (MFF) based on latent semantic indexing (LSI) method to achieve an improved image retrieval performance. The proposed method extracts different physical features, which come from not the whole image but its main objects, and constructs a multi-modal semantic space, each dimension of which represents a different feature component of the image. Furthermore,...
Subjective question is capable of examining the adopting ability of knowledge of the student, but the assessment for it suffers from a number of questions such as trickiness, synonymy and polysemy. This reduces the advantage of subjective question for online exercise. In this paper we explore an approach to automated assessment system for subjective question based on latent semantic indexing. Chinese...
The latent semantic indexing (LSI) methodology for information retrieval applies the singular value decomposition to identify an eigensystem for a large matrix, in which cells represent the occurrence of terms (words) within documents. This methodology is used to rank text documents, such as Web pages or abstracts, based on their relevance to a topic. The LSI was introduced to address the issues of...
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