Perancangan Prototipe Sistem Temu Kembali Informasi Menggunakan Algoritma Fuzzy Clustering  

Oleh:

Irfani, Ahmad

Jenis: Article from Journal - ilmiah nasional
Dalam koleksi: Bina Widya: Majalah ilmiah UPN "Veteran" Jakarta vol. 23 no. 2 (Nov. 2011), page 116-121.
Topik: Information Retrieval; Fuzzy Clustering

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: BB24.3 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

Lihat Detail Induk

Isi artikel

This article analyzes the suitability of fuzzy clustering methods for the discovery of relevant document relationships. The performance evaluation of three fuzzy clustering algorithms (Fuzzy C-Means, Hyperspherical Fuzzy C-Means and Fuzzy Substractive Clustering) on document written in bahasa Indonesia and English. Comparison of three different document representation formula (Term Frequency, Term Frequency Inverse Document Frequency and Salton) using various reduction of matrix dimension are also carried out. Clustering precision and recall are applied as quantitative evaluation measures of the clustering results. The experiments using document sets with various topic have shown that Hyperspherical Fuzzy C-Means algorithm perform better than Fuzzy C-Means and Fuzzy Substractive Clustering Algorithm. Also found that Salton formula is able to give the 'right' document representation to the clustering algorithm as Tf and Tf-Idf are failed.

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