کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
396604 | 670413 | 2008 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Mining relational data from text: From strictly supervised to weakly supervised learning
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
This paper approaches the relation classification problem in information extraction framework with different machine learning strategies, from strictly supervised to weakly supervised. A number of learning algorithms are presented and empirically evaluated on a standard data set. We show that a supervised SVM classifier using various lexical and syntactic features can achieve competitive classification accuracy. Furthermore, a variety of weakly supervised learning algorithms can be applied to take advantage of large amount of unlabeled data when labeling is expensive. Newly introduced random-subspace-based algorithms demonstrate their empirical advantage over competitors in the context of both active learning and bootstrapping.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Systems - Volume 33, Issue 3, May 2008, Pages 300–314
Journal: Information Systems - Volume 33, Issue 3, May 2008, Pages 300–314
نویسندگان
Zhu Zhang,