In this paper, we propose a web document ranking method using topic modeling for effective information collection and classification. The proposed is applied to the technique avoid duplicated crawling when at high speed. Through technique, it feasible remove redundant documents, classify documents efficiently, confirm that crawler service running. enables rapid of many documents; user can searc...

Online legal document libraries, such as WorldLII, are indispensable tools for professionals to conduct research. We study how topic modeling techniques can be applied platforms facilitate searching of court judgments. Specifically, we improve search effectiveness by matching judgments queries at semantics level rather than keyword level. Also, design a system that summarizes retrieved judgment...

Topic modeling has become a ubiquitous topic analysis tool for text exploration. Most of the existing works on topic modeling focus on fitting topic models to input data. They however ignore an important usability issue that is closely related to the end user experience: stability. In this study, we investigate the stability problem in topic modeling. We first report on the experiments conducte...

Topic modeling is a probabilistic model that identifies topics covered in text(s). In this paper, were loaded from two implementations of topic modeling, namely, Latent Semantic Indexing (LSI) and Dirichlet Allocation (LDA). This analysis was performed corpus 1000 academic papers written English, obtained PLOS ONE website, the areas Biology, Medicine, Physics Social Sciences. The objective to v...