Clustering the results of a search can help a multi-document summarizer present a summary for evidence based medicine (EBM). In this work, we introduce a clustering technique that is based on multiobjective (MOO) optimization. MOO is a technique that shows promise in the areas of machine learning and natural language processing. In our approach we show how MOO based semi-supervised clustering technique can be effectively used for EBM.
|Title of host publication||ALTA 2013|
|Subtitle of host publication||Proceedings of the Australasian Language Technology Association Workshop|
|Editors||Sarvnaz Karimi, Karin Verspoor|
|Place of Publication||Brisbane|
|Publisher||Australasian Language Technology Association|
|Number of pages||9|
|Publication status||Published - 2013|
|Event||Australasian Language Technology Workshop (11th : 2013) - Brisbane|
Duration: 4 Dec 2013 → 6 Dec 2013
|Workshop||Australasian Language Technology Workshop (11th : 2013)|
|Period||4/12/13 → 6/12/13|
Ekbal, A., Saha, S., Mollá, D., & Ravikumar, K. (2013). Multi-objective optimization for clustering of medical publications. In S. Karimi, & K. Verspoor (Eds.), ALTA 2013: Proceedings of the Australasian Language Technology Association Workshop (pp. 53-61). Brisbane: Australasian Language Technology Association.