Title |
Modeling Document Dynamics: an Evolutionary Approach |
Authors |
Jahna Otterbacher and Dragomir Radev |
Abstract |
News articles about the same event published over time have properties that challenge NLP and IR applications. A cluster of such texts typically exhibits instances of paraphrase and contradiction, as sources update the facts surrounding the story, often due to an ongoing investigation. The current hypothesis is that the stories evolve over time, beginning with the first text published on a given topic. This is tested using a phylogenetic approach as well as one based on language modeling. The fit of the evolutionary models is evaluated with respect to how well they facilitate the recovery of chronological relationships between the documents. Over all data clusters, the language modeling approach consistently outperforms the phylogenetics model. However, on manually collected clusters in which the documents are published within short time spans of one another, both have a similar performance, and produce statistically significant results on the document chronology recovery evaluation. |
Language |
Language-independent |
Topics |
Document Classification, Text categorisation, Tools, systems, applications |
Full paper |
Modeling Document Dynamics: an Evolutionary Approach |
Slides |
Modeling Document Dynamics: an Evolutionary Approach |
Bibtex |
@InProceedings{OTTERBACHER08.115,
author = {Jahna Otterbacher and Dragomir Radev},
title = {Modeling Document Dynamics: an Evolutionary Approach},
booktitle = {Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)},
year = {2008},
month = {may},
date = {28-30},
address = {Marrakech, Morocco},
editor = {Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Daniel Tapias},
publisher = {European Language Resources Association (ELRA)},
isbn = {2-9517408-4-0},
note = {http://www.lrec-conf.org/proceedings/lrec2008/},
language = {english}
} |