Pemrosesan Bahasa Alami

Tahun Akademik:
Gasal 2024/2025
Kelas-Offr:
TE-DTE
Deskripsi:
Prinsip dan aplikasi Natural Language Processing (NLP), salah satu cabang ilmu AI yang berfokus pada pengolahan bahasa natural (Bahasa komunikasi manusia). Matakuliah ini menggunakan corpus untuk mengilustrasikan konsep dasar linguistic dan algoritma,antara lain language modeling, part of speech tagging, syntactic processing, syntax-semantics interface, dan aspects of semantic processing
Capaian Pembelajaran

• 1. Menganalisis konsep annotated corpora: markup; annotation; evaluation measures; corpora and the web.
• 2. Menganalisis konsep lexicon and lexical processing: language modeling; Hidden Markov Models; part of speech tagging; Viterbi algorithm; smoothing.
• 3. Menganalisis konsep syntax and syntactic processing: revision of context-free grammars and chart parsing; syntactic concepts: constituency, subcategorization, bounded and unbounded dependencies, feature representations; lexicalized grammar formalisms (e.g., TAG, CCG, dependency grammar); * treebanks: lexicalized grammars and corpus annotation.
• 4. Menganalisis konsep semantics and semantic processing: compositionality; argument structure; word sense disambiguation; anaphora resolution; treebanks: argument structure, WSD (e.g., Propbank, Semcor).

Daftar Pustaka:

• 1. Bird, S., Klein, E., & Loper, E. (2009). Natural language processing with Python: analyzing text with the natural language toolkit. " O'Reilly Media, Inc.".
• 2. Chopra, D., Joshi, N., & Mathur, I. (2016). Mastering Natural Language Processing with Python. Packt Publishing Ltd.
• 3. Hardeniya, N. (2015). NLTK essentials. Packt Publishing Ltd.
• 4. Kapetanios, E., Tatar, D., & Sacarea, C. (2013). Natural language processing: semantic aspects. CRC Press.
• 5. Kurdi, M. Z. (2016). Natural Language Processing and Computational Linguistics: Speech, Morphology and Syntax (Vol. 1). John Wiley & Sons.
• 6. Perkins, J. (2014). Python 3 Text Processing with NLTK 3 Cookbook. Packt Publishing Ltd.