Probabilistic Latent Semantic Analysis

@inproceedings{SIGIR:1999:hofmann, abstract = {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 filtering, 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-occurrence tables, the proposed method is based on a mixture decomposition derived from a latent class...}, address = {Stockholm}, author = {Hofmann, Thomas }, booktitle = {Proc. of Uncertainty in Artificial Intelligence, UAI'99}, citeulike-article-id = {437884}, keywords = {lsa, topic\_models}, posted-at = {2008-07-02 18:08:23}, priority = {2}, title = {Probabilistic Latent Semantic Analysis}, url = {http://citeseer.ist.psu.edu/hofmann99probabilistic.html}, year = {1999} }

TY - CONF ID - SIGIR:1999:hofmann L3 - citeulike-article-id:437884 TI - Probabilistic Latent Semantic Analysis T2 - Proc. of Uncertainty in Artificial Intelligence, UAI'99 AD - Stockholm N2 - 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 filtering, 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-occurrence tables, the proposed method is based on a mixture decomposition derived from a latent class... KW - lsa KW - topic_models AU - Hofmann, Thomas PY - 1999/// UR - http://citeseer.ist.psu.edu/hofmann99probabilistic.html ER -