Text classification using a small labeled set and a large unlabeled data is seen as a promising technique to reduce the labor-intensive and time consuming effort of labeling traini...
mes, abstracts and year of publication of all 853 papers published.1 We then applied Porter stemming and stopword removal to this text, represented terms from the elds with twice t...
Alan F. Smeaton, Gary Keogh, Cathal Gurrin, Kieran...
Background: High-throughput molecular biology provides new data at an incredible rate, so that the increase in the size of biological databanks is enormous and very rapid. This sc...
Every piece of textual data is generated as a method to convey its authors' opinion regarding specific topics. Authors deliberately organize their writings and create links, ...
Huajing Li, Zaiqing Nie, Wang-Chien Lee, C. Lee Gi...
This paper introduced the four tracks that WIM-Lab Fudan University had taken part in at TREC 2007. For spam track, a multi-centre model was proposed considering the characteristi...
Jun Xu, Jing Yao, Jiaqian Zheng, Qi Sun, Junyu Niu