The traditional term weighting methods borrowed from information retrieval(IR), such as binary, term frequency (tf), tf:idf, and its various variants, belong to the unsupervised term weighting methods as the calculation of these weighting methods do not make use of the information on the ...
To the best of our knowledge, our research is among the very few successful work that aims to enhance both the semantic coherence and the interpretability of LDA-based topic modeling methods. The experimental results show that the proposed framework improves the effectiveness of LDA as well as ...
frequency (rf) to weight terms in a supervised way. Our cross-classifier and cross-corpus experi- ments have shown that our proposed approaches are superior or comparable to six super- vised term weighting schemes and three traditional schemes in terms of macro-F1 and micro-F1. Keywords: ...
Supervised and Traditional Term Weighting Methods for Automatic Text Categorization In vector space model (VSM), text representation is the task of transforming the content of a textual document into a vector in the term space so that the ... M Lan,CL Tan,J Su,... - 《IEEE Transactions on...
This paper presents term-weighting schemes that have been evolved using genetic programming in an adhoc Information Retrieval model. We create an entire term-weighting scheme by firstly assuming that term-weighting schemes contain a global part, a term-frequency influence part and a normalisati...
We provide efficient solution methods for these optimization problems. The effectiveness and robustness of the proposed approaches are demonstrated on several benchmark document datasets, significantly outperforming the existing term weighting methods. 展开 ...
An integrated level analysis and entropy values to be calculated to the weight combination methods to determine the weight of the various indicators, on the basis of this, and build a partnership the static fuzzy evaluation systems. Taking into account the long-term cooperation partner should focus...
We use this new method, latent semantic analysis (LSA), and latent Dirichlet allocation (LDA) to give three term-weighting methods for multi-document multi-lingual summarization. Results on DUC and TAC data, as well as on the MultiLing 2013 data, demonstrate that these methods are very ...
The proposed approach outperformed the Okapi BM25 and TF-ATO with DA weighting schemes methods in terms of Mean Average Precision (MAP), Average Precision (AP) and Normalized Discounted Cumulative Gain (NDCG). 展开 关键词: Evolutionary Gradient Strategy Information Retrieval ...
These methods break down the data into 6 to 8 frequency components, which are subsequently fed either individually or collectively (alongside residuals) into different Convolutional Neural Networks (CNNs). The output from these CNNs is then directed to LSTM components, or in some cases, directly ...