Topic modeling revisited:  New evidence on algorithm performance and quality metrics.

ABSTRACT: Topic modeling is a popular technique for exploring large document collections. It has proven useful for this task, but its application poses a number of challenges. First, the comparison of available algorithms is anything but simple, as researchers use many different datasets and criteria for their evaluation. A second challenge is the choice of a suitable metric for evaluating the calculated results. The metrics used so far provide a mixed picture, making it difficult to verify the accuracy of topic modeling outputs. Altogether, the choice of an appropriate algorithm and the evaluation of the results remain unresolved issues. Although many studies have reported promising performance by various topic models, prior research has not yet systematically investigated the validity of the outco

SUBMITTER: Rudiger M 

PROVIDER: S-EPMC9049322 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature