نتایج جستجو برای: topic model
تعداد نتایج: 2231604 فیلتر نتایج به سال:
This paper proposes a method to capture user’s characteristics in a topic model frame, where user characteristics act as a latent variable that does not depend on texts. As it is obvious that different people possess different characteristics, they may perform differently even when they are facing the same document. These different characteristics can be showed as different views or different w...
This paper proposes a new methodology to study sequential corpora by implementing two-stage algorithm that learns time-based topics with respect scale of document positions and introduces the concept Topic Scaling, which ranks learned within same scale. The first stage documents using Wordfish, Poisson-based document-scaling method, estimate serve, in second stage, as dependent variable learn r...
Purpose: This study investigates the automatic keyword extraction from the table of contents of Persian e-books in the field of science using LDA topic modeling, evaluating their similarity with golden standard, and users' viewpoints of the model keywords. Methodology: This is a mixed text-mining research in which LDA topic modeling is used to extract keywords from the table of contents of sci...
A probabilistic topic model assumes that documents are generated through a process involving topics and then tries to reverse this process, given the documents and extract topics. A topic is usually assumed to be a distribution over words. LDA is one of the first and most popular topic models introduced so far. In the document generation process assumed by LDA, each document is a distribution o...
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