کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
515295 866979 2006 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Filtering search results using an optimal set of terms identified by an artificial neural network
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
Filtering search results using an optimal set of terms identified by an artificial neural network
چکیده انگلیسی

Information filtering (IF) systems usually filter data items by correlating a set of terms representing the user’s interest (a user profile) with similar sets of terms representing the data items. Many techniques can be employed for constructing user profiles automatically, but they usually yield large sets of term. Various dimensionality-reduction techniques can be applied in order to reduce the number of terms in a user profile. We describe a new terms selection technique including a dimensionality-reduction mechanism which is based on the analysis of a trained artificial neural network (ANN) model. Its novel feature is the identification of an optimal set of terms that can classify correctly data items that are relevant to a user. The proposed technique was compared with the classical Rocchio algorithm. We found that when using all the distinct terms in the training set to train an ANN, the Rocchio algorithm outperforms the ANN based filtering system, but after applying the new dimensionality-reduction technique, leaving only an optimal set of terms, the improved ANN technique outperformed both the original ANN and the Rocchio algorithm.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Processing & Management - Volume 42, Issue 2, March 2006, Pages 469–483
نویسندگان
, , ,