Year: 2003
Type: conference-abstract
Abstract: The University of Maryland submitted six topic tracking runs for the 2002 Topic Detection and Tracking evaluation. Two runs were produced using the Lemur language modeling toolkit, the remaining four were produced using a separate system coded in Perl. The Lemur runs outperformed the Perl runs on the required condition because term frequency information was better handled. Two of the Perl runs used native Arabic orthography with two-best translation based on a statistical lexicon, obtaining similar results to those obtained with the Arabic-to-English translations provided with the collection.
DOI: 10.21236/ada459303
Authors: Daqing He, Hyuk R. Park, G. C. Murray, Michael Subotin, Douglas W. Oard
Institution: University of Maryland, College Park
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W12299769