In this paper we present some results in the domain of doc- ument categorization. We use the well-known PageRank algorithm to perform a random-walk through the ...

Abstract. Feature selection is an important task in data mining because it al- lows to reduce the data dimensionality and eliminates the noisy variables.

Abstract. Feature selection is an important task in data mining because it al- lows to reduce the data dimensionality and eliminates the noisy variables.

This paper uses the well-known PageRank algorithm to perform a random-walk through the feature space of the documents and allows classifiers to obtain good ...

Dec 5, 2021 · In this paper, a novel ensemble of feature selection based on weighted PageRank and fuzzy logic, named EFSPF, is proposed to overcome these drawbacks.

Mar 15, 2020 · In this paper, we have designed a fast algorithm for feature selection on the multi-label data using the PageRank algorithm.

This paper suggests a new semisupervised feature selection algorithm based on the PageRank centrality concept for the partially labeled data.

In this paper, a novel filter-based approach is proposed using the PageRank algorithm to select the optimal subset of features as well as to compute their ...

He is the one who came up with the idea of using the PageRank algorithm for feature selection. Thanks to him, I have learned a lot during the development of ...

Mar 25, 2022 · Calculate the rank of each node by using the Google PageRank algorithm [14] and compute the highest scored node (dummy column/feature from ...