We address the issue of providing topic driven access to full text documents. The methodology we propose is a combination of topic segmentation and information retrieval techniques...
Caterina Caracciolo, Willem Robert van Hage, Maart...
In many topic identification applications, supervised training labels are indirectly related to the semantic content of the documents being classified. For example, many topical...
We have performed a set of experiments made to investigate the utility of morphological analysis to improve retrieval of documents written in languages with relatively large morph...
This paper presents an LDA-style topic model that captures not only the low-dimensional structure of data, but also how the structure changes over time. Unlike other recent work t...
Algorithms that enable the process of automatically mining distinct topics in document collections have become increasingly important due to their applications in many fields and ...