Latent semantic indexing (LSI) is commonly used to match queries to documents in
information retrieval applications. LSI has been shown to improve retrieval performance for …

Some previous studies (eg that carried out by Van Bruggen et al. in 2004) have pointed to a
need for additional research in order to firmly establish the usefulness of LSA (latent …

Plagiarism is growing increasingly for the last few years due to the rapid proliferation of
information through the World Wide Web (WWW). In this paper, we present an integrated …

潜在语义索引被广泛应用于信息检索, 文本分类, 自动问答等领域中. 潜在语义索引是一种降维
方法, 它把共现特征映射到同一维空间上, 而非共现特征映射到不同的空间上 …

To overcome the limitations of traditional text classification approaches based on bag-of-
words representation and to effectively incorporate linguistic knowledge and conceptual …

This thesis investigates the capacities of adaptive methods for word prediction. We present
and evaluate several adaptation methods: First, we consider strategies enabling to adapt to …

The stability of sample based algorithms is a concept commonly used for parameter tuning
and validity assessment. In this paper we focus on two well studied algorithms, LSI and PCA …

We describe the latent semantic indexing subspace signature model (LSISSM) for semantic
content representation of unstructured text. Grounded on singular value decomposition, the …

Semantic relation extraction is a significant topic in semantic web and natural language
processing with various important applications such as knowledge acquisition, web and text …

Latent Semantic Analysis (LSA) is a technology which is used to analyze the latent concepts.
LSA is based on the Vector Space Model (VSM) and statistics, and it usually takes the …