Extending latent semantic analysis to manage its syntactic blindness

Query expansion based on relevance feedback and latent semantic analysis

Web search engines are one of the most popular tools on the Internet which are widely-used by expert and novice users. Constructing an adequate query which represents the best specification of users’ information need to the search engine is an important concern of web users. Query expansion is a way to reduce this concern and increase user satisfaction. In this paper, a new method of query expa...

Towards Extending Syntactic Valence Dictionary for Polish with Semantic Categories

Probabilistic Latent Semantic Analysis

Probabilistic Latent Semantic Analysis is a novel statistical technique for the analysis of two{mode and co-occurrence data, which has applications in information retrieval and ltering, natural language processing, machine learning from text, and in related areas. Compared to standard Latent Semantic Analysis which stems from linear algebra and performs a Singular Value Decomposition of co-occu...

Latent Semantic Analysis (Tutorial)

We will see that the number of eigenvalues is n for an n× n matrix. Regarding eigenvectors, if x is an eigenvector then so is ax for any scalar a. However, if we consider only one eigenvector for each ax family, then there is a 1-1 correspondence of such eigenvectors to eigenvalues. Typically, we consider eigenvectors of unit length. Diagonal matrices are simple, the eigenvalues are the entries...

Latent Semantic Analysis

Latent Semantic Analysis (LSA) is a technique for comparing texts using a vector-based representation that is learned from a corpus. This article begins with a description of the history of LSA and its basic functionality. LSA enjoys both theoretical support and empirical results that show how it matches human behavior. A number of the experiments that compare LSA with humans are described here...