Dialogue System using Long Short-Termed Memory
MUHAMMAD HUSAIN TODING BUNGA
Informasi Umum
Kode
21.04.3631
Klasifikasi
006.31 - Machine Learning
Jenis
Karya Ilmiah - Skripsi (S1) - Reference
Subjek
Machine - Learning
Dilihat
254 kali
Informasi Lainnya
Abstraksi
As the technology of natural language understanding and language generation improve, there is increasing human interest towards human-computer interaction, which can be used for various applications such as customer services, travel, and much more. Well known examples of conversational AI are Apple’s Siri, Amazon’s Alexa, Microsoft’s Cortana and Google’s Google Assistant. Most work related on this field are emphasizing on single sentence or speaker turn. While sometimes a conversation has their own context according to previous conversation. Designing this kind of conversational system is challenging, most of the time conversational agent are built based on knowledge based system and rule based system. By building a conversational agent with data driven approaches, which learn from a corpus we could improve the amount of time and effort needed to create a rule based system. Keywords : natural language understanding, dialogue system, conversational agent, LSTM
- CCH3F3 - KECERDASAN BUATAN
- CSG3G3 - KECERDASAN MESIN DAN ARTIFISIAL
- CSH4O3 - PEMROSESAN BAHASA ALAMI
- CSH4H3 - PENAMBANGAN TEKS
Koleksi & Sirkulasi
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Pengarang
| Nama | MUHAMMAD HUSAIN TODING BUNGA |
| Jenis | Perorangan |
| Penyunting | SUYANTO |
| Penerjemah |
Penerbit
| Nama | Universitas Telkom, S1 Informatika |
| Kota | Bandung |
| Tahun | 2021 |
Sirkulasi
| Harga sewa | IDR 0,00 |
| Denda harian | IDR 0,00 |
| Jenis | Non-Sirkulasi |
