The California Innocence Project (CIP), a clinical law school program aiming to free wrongfully convicted prisoners, evaluates thousands of mails containing new requests for assistance and corresponding case files. Processing interpreting this large amount information presents significant challenge CIP officials, which can be successfully aided by topic modeling techniques.In paper, we apply No...

Graph non-negative matrix factorization (GNMF) can discover the data’s intrinsic low-dimensional structure embedded in high-dimensional space. So, it has superior performance for data representation and clustering. Unfortunately, is sensitive to noise outliers. In this paper, improve robustness of GNMF, $$l_0$$ norm introduced enhance sparsity factorized matrices. As discontinuity minimizing a ...

Pemodelan topik merupakan teknik pembelajaran mesin yang digunakan untuk melihat dalam sekumpulan dokumen teks. Pada penelitian ini pemodelan adalah Non-Negative Matrix Factorization (NMF) dengan n-gram. Preprocessing seperti penghilangan tanda baca, angka dan stopword diimplementasikan pada ini. Proses dilakukan terlebih dahulu mengubah kata terdapat artikel menjadi berhuruf kecil. Penelitian ...

This paper proposes an acoustic event detection (AED) method using semi-supervised non-negative matrix factorization (NMF) with a mixture of local dictionaries (MLD). The proposed method based on semi-supervised NMF newly introduces a noise dictionary and a noise activation matrix both dedicated to unknown acoustic atoms which are not included in the MLD. Because unknown acoustic atoms are bett...

This paper proposes a novel method for separating harmonic and percussive sounds in single-channel music recordings. Standard non-negative matrix factorization (NMF) is used to obtain the activations of the most representative patterns active in the mixture. The basic idea is to classify automatically those activations that exhibit rhythmic and non-rhythmic patterns. We assume that percussive s...

In this paper, an adaptive noise estimation technique is proposed on the basis of non-negative matrix factorization (NMF). As an initial step of the proposed method, the noise basis matrix of NMF is estimated from a collection of noise signals. Then, the proposed method updates the initially estimated noise basis matrix on the fly by using an estimate of the noise spectrum from the noisy signal...