Hierarchical text classi(cid:2)cation refers to assigning text documents to the categories in a given category tree based on their content. With large number of categories organized as a tree, hierarchical text classi(cid:2)cation helps users to (cid:2)nd information more quickly and accurately. Nevertheless, hierarchical text classi(cid:2)cation methods in the past have often been constructed in a proprietary manner. The construction steps often involve human efforts and are not completely automated. In this paper, we therefore propose a speci(cid:2)cation language known as H CL (Hierarchical Classi(cid:2)cation Lan-guage). H CL is designed to describe a hierarchical classi(cid:2)-cation method including the de(cid:2)nition of a category tree and training of classi(cid:2)ers associated with the categories. Using H CL , a hierarchical classi(cid:2)cation method can be material-ized easily with the help of a method generator system.
[1]
Yiming Yang,et al.
An Evaluation of Statistical Approaches to Text Categorization
,
1999,
Information Retrieval.
[2]
Fabrizio Sebastiani,et al.
Machine learning in automated text categorization
,
2001,
CSUR.
[3]
Ee-Peng Lim,et al.
Hierarchical text classification and evaluation
,
2001,
Proceedings 2001 IEEE International Conference on Data Mining.
[4]
Susan T. Dumais,et al.
Hierarchical classification of Web content
,
2000,
SIGIR '00.
[5]
Daphne Koller,et al.
Hierarchically Classifying Documents Using Very Few Words
,
1997,
ICML.
[6]
Giuseppe Psaila,et al.
A New SQL-like Operator for Mining Association Rules
,
1996,
VLDB.