Temporal Keyword Extraction from Indonesian News Articles: The Topic-based Recommender System - Dalam bentuk buku karya ilmiah
SOFI NURHAYATI LATIFAH
Informasi Umum
Kode
25.04.486
Klasifikasi
000 - General Works
Jenis
Karya Ilmiah - Skripsi (S1) - Reference
Subjek
Recommender Systems
Dilihat
81 kali
Informasi Lainnya
Abstraksi
The rapid development of news in the digital era has led to significant growth in news volume. Finding key information in the news efficiently is becoming increasingly important. Although previous studies have succeeded in developing a news-topic recommender system using keyword selection and topic extraction, there is still an area for improvement in the dataset, which is still limited to a specific topic. Therefore, we propose the use of RAKE algorithm and compare it with TF-IDF for keyword extraction in multi-topic Indonesian News data based on a specific period in the news topic recommender system. RAKE algorithm breaks text into phrases based on specific delimiters, assesses each phrase based on frequency and relevancy, and then selects the phrase with the highest score as the main keyword. Meanwhile, TF-IDF identifies single keywords based on their frequency of appearance in documents and their inverse frequency in documents. Based on the performance comparison evaluation results, the proposed system ha
Koleksi & Sirkulasi
Tersedia 1 dari total 1 Koleksi
Anda harus log in untuk mengakses flippingbook
Pengarang
| Nama | SOFI NURHAYATI LATIFAH |
| Jenis | Perorangan |
| Penyunting | Z. K. Abdurahman Baizal |
| Penerjemah |
Penerbit
| Nama | Universitas Telkom, S1 Informatika |
| Kota | Bandung |
| Tahun | 2025 |
Sirkulasi
| Harga sewa | IDR 0,00 |
| Denda harian | IDR 0,00 |
| Jenis | Non-Sirkulasi |
