Summary of the paper
| Title | Measures for Term and Sentence Relevances: an Evaluation for German |
|---|---|
| Authors | Heike Bieler and Stefanie Dipper |
| Abstract | Terms, term relevances, and sentence relevances are concepts that figure in many NLP applications, such as Text Summarization. These concepts are implemented in various ways, though. In this paper, we want to shed light on the impact that different implementations can have on the overall performance of the systems. In particular, we examine the interplay between term definitions and sentence-scoring functions. For this, we define a gold standard that ranks sentences according to their significance and evaluate a range of relevant parameters with respect to the gold standard. |
| Language | Single language |
| Topics | Summarisation, Statistical methods, Information Extraction, Information Retrieval |
Full paper |
Measures for Term and Sentence Relevances: an Evaluation for German |
Slides |
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| Bibtex | @InProceedings{BIELER08.272, author = {Heike Bieler and Stefanie Dipper}, title = {Measures for Term and Sentence Relevances: an Evaluation for German}, 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} } |