Keyword selection method for characterizing text document maps Export

@inproceedings{citeulike:2966717, abstract = {Characterization of subsets of data is a recurring problem in data mining. We propose a keyword selection method that can be used for obtaining characterizations of clusters of data whenever textual descriptions can be associated with the data. Several methods that cluster data sets or form projections of data provide an order or distance measure of the clusters. If such an ordering of the clusters exists or can be deduced, the method utilizes the order to improve the characterizations. The proposed method may be applied, for example, to characterizing graphical displays of collections of data ordered (e.g. with SOM algorithm). The method is validated using a collection of 10000 scientific abstracts from the INSPEC database organized on a WEBSOM document map}, author = {Lagus, K. and Kaski, S.}, booktitle = {Artificial Neural Networks, 1999. ICANN 99. Ninth International Conference on (Conf. Publ. No. 470)}, citeulike-article-id = {2966717}, citeulike-linkout-0 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=819749}, journal = {Artificial Neural Networks, 1999. ICANN 99. Ninth International Conference on (Conf. Publ. No. 470)}, keywords = {kohonengroup, som, textmining}, pages = {371--376 vol.1}, posted-at = {2008-07-09 03:27:08}, priority = {2}, title = {Keyword selection method for characterizing text document maps}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=819749}, volume = {1}, year = {1999} }

TY - CONF ID - citeulike:2966717 L3 - citeulike-article-id:2966717 N2 - Characterization of subsets of data is a recurring problem in data mining. We propose a keyword selection method that can be used for obtaining characterizations of clusters of data whenever textual descriptions can be associated with the data. Several methods that cluster data sets or form projections of data provide an order or distance measure of the clusters. If such an ordering of the clusters exists or can be deduced, the method utilizes the order to improve the characterizations. The proposed method may be applied, for example, to characterizing graphical displays of collections of data ordered (e.g. with SOM algorithm). The method is validated using a collection of 10000 scientific abstracts from the INSPEC database organized on a WEBSOM document map JF - Artificial Neural Networks, 1999. ICANN 99. Ninth International Conference on (Conf. Publ. No. 470) EP - 376 vol.1 TI - Keyword selection method for characterizing text document maps VL - 1 T2 - Artificial Neural Networks, 1999. ICANN 99. Ninth International Conference on (Conf. Publ. No. 470) SP - 371 KW - kohonengroup KW - som KW - textmining AU - Lagus, K AU - Kaski, S PY - 1999/// UR - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=819749 ER -