ARTM vs. LDA: an SVD Extension Case Study
نویسنده
چکیده
In this work, we compare two extensions of two different topic models for the same problem of recommending full-text items: previously developed SVD-LDA and its counterpart SVD-ARTM based on additive regularization. We show that ARTM naturally leads to the inference algorithm that has to be painstakingly developed for LDA.
منابع مشابه
Mining Ethnic Content Online with Additively Regularized Topic Models
Social studies of the Internet have adopted large-scale text mining for unsupervised discovery of topics related to specific subjects. A recently developed approach to topic modeling, additive regularization of topic models (ARTM), provides fast inference and more control over the topics with a wide variety of possible regularizers than developing LDA extensions. We apply ARTM to mining ethnic-...
متن کاملStudy on the effect of left displacement of abomasum (LDA) on serum minerals and biochemical changes in dairy cows
Minerals and some biochemical parameters determined from blood serum analyses in left displacement abomasum (LDA) affected and healthy dairy cows to evaluate the effect of displacement abomasum on mineral status, energy metabolism and liver function. Samples were collected from 60 affected cows and 60 healthy control cows matched with cases, based on herd, parity, and stage of lactation. Concen...
متن کاملRobust Kernel Fisher Discriminant Analysis
Kernel methods have become standard tools for solving classification and regression problems in statistics. An example of a kernel based classification method is Kernel Fisher discriminant analysis (KFDA), a kernel based extension of linear discriminant analysis (LDA), which was proposed by Mika et al. (1999). As in the case of LDA, the classification performance of KFDA deteriorates in the pre...
متن کاملSmart nanocrystals of artemether: fabrication, characterization, and comparative in vitro and in vivo antimalarial evaluation
Artemether (ARTM) is a very effective antimalarial drug with poor solubility and consequently low bioavailability. Smart nanocrystals of ARTM with particle size of 161±1.5 nm and polydispersity index of 0.172±0.01 were produced in <1 hour using a wet milling technology, Dena® DM-100. The crystallinity of the processed ARTM was confirmed using differential scanning calorimetry and powder X-ray d...
متن کاملMatrix Rank Reduction for
Numerical techniques for data analysis and feature extraction are discussed using the framework of matrix rank reduction. The singular value decomposition (SVD) and its properties are reviewed, and the relation to Latent Semantic Indexing (LSI) and Principal Component Analysis (PCA) is described. Methods that approximate the SVD are reviewed. A few basic methods for linear regression, in partic...
متن کامل