Text Classification for DAG-Structured Categories Export

@incollection{citeulike:2638542, abstract = {Hierarchical text classification concerning the relationship among categories has become an interesting problem recently. Most research has focused on tree-structured categories, but in reality directed acyclic graph (DAG) - structured categories, where a child category may have more than one parent category, appear more often. In this paper, we introduce three approaches, namely, flat, tree-based, and DAG-based, for solving the multi-label text classification problem in which categories are organized as a DAG, and documents are classified into both leaf and internal categories. We also present experimental results of the methods using SVMs as classifiers on the Reuters-21578 collection and our data set of research papers in Artificial Intelligence. Keywords: text classification, hierarchies, multi-labels, SVM.}, author = {Nguyen, Cao D. and Dung, Tran A. and Cao, Tru H.}, citeulike-article-id = {2638542}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/11430919_36}, doi = {10.1007/11430919_36}, journal = {Advances in Knowledge Discovery and Data Mining}, keywords = {classification, hierarchy, nlp}, pages = {290--300}, posted-at = {2008-06-27 02:15:52}, priority = {0}, title = {Text Classification for DAG-Structured Categories}, url = {http://dx.doi.org/10.1007/11430919_36}, year = {2005} }

TY - CHAP ID - citeulike:2638542 L3 - citeulike-article-id:2638542 N2 - Hierarchical text classification concerning the relationship among categories has become an interesting problem recently. Most research has focused on tree-structured categories, but in reality directed acyclic graph (DAG) - structured categories, where a child category may have more than one parent category, appear more often. In this paper, we introduce three approaches, namely, flat, tree-based, and DAG-based, for solving the multi-label text classification problem in which categories are organized as a DAG, and documents are classified into both leaf and internal categories. We also present experimental results of the methods using SVMs as classifiers on the Reuters-21578 collection and our data set of research papers in Artificial Intelligence. Keywords: text classification, hierarchies, multi-labels, SVM. JF - Advances in Knowledge Discovery and Data Mining EP - 300 TI - Text Classification for DAG-Structured Categories SP - 290 KW - classification KW - hierarchy KW - nlp AU - Nguyen, Cao AU - Dung, Tran AU - Cao, Tru PY - 2005/// UR - http://dx.doi.org/10.1007/11430919_36 ER -