Presents a literature review that covers the following topics related to Latent Semantic
Analysis (LSA):(1) LSA overview;(2) applications of LSA, including information retrieval (IR) …

A large number of clustering approaches have been proposed for the analysis of gene
expression data obtained from microarray experiments. However, the results from the …

Recently, recommender systems are widely used on various platforms in real world to
provide personalized recommendations. However, sparsity is a tough problem in a …

In this age of information overload, people use a variety of strategies to make choices about
what to buy, how to spend their leisure time, and even whom to date. Recommender …

As one of the most successful approaches to building recommender systems, collaborative
filtering (CF) uses the known preferences of a group of users to make recommendations or …

We have developed a method for recommending items that combines content and
collaborative data under a single probabilistic framework. We benchmark our algorithm …

Collaborative filtering aims at learning predictive models of user preferences, interests or
behavior from community data, that is, a database of available user preferences. In this …

Two-dimensional contingency or co-occurrence tables arise frequently in important
applications such as text, web-log and market-basket data analysis. A basic problem in …

Rating-based collaborative filtering is the process of predicting how a user would rate a
given item from other user ratings. We propose three related slope one schemes with …

Collaborative filtering systems predict a user's interest in new items based on the
recommendations of other people with similar interests. Instead of performing content …