Natural Language Processing

Course title

L0036000

Course description

Basic technology to deal with natural language text, in particular, analyze method of natural language sentences, information retrieval and machine translation is explained.

Purpose of class

Students can learn basic theories and technologies to deal with natural language data.

Goals and objectives

To understand grammatical features of Japanese and regularities for text construction
To understand basic technology, e.g., morphological and syntactic analyses
To learn application technology of information retrieval and machine translation

Relationship between 'Goals and Objectives' and 'Course Outcomes'

	Report	Total.
1.	20%	20%
2.	40%	40%
3.	40%	40%
Total.	100%	-

Evaluation method and criteria

Report (100%)

Language

Japanese

Class schedule

	Class schedule	HW assignments (Including preparation and review of the class.)	Amount of Time Required
1.	Overview of natural language processing	Textbook chap. 1	90minutes
1.	Overview of natural language processing	Review	100minutes
2.	Japanese grammar and corpus	Textbook chap. 1	90minutes
2.	Japanese grammar and corpus	Exercises	100minutes
3.	Machine learning	Textbook chap. 2	90minutes
3.	Machine learning	Exercises	100minutes
4.	Morphological analysis (1) analysis method	Textbook chap. 3	90minutes
4.	Morphological analysis (1) analysis method	Exercises	100minutes
5.	Morphological analysis (2) cost estimation	Textbook chap. 3	90minutes
5.	Morphological analysis (2) cost estimation	Exercises	100minutes
6.	Syntactic analysis	Textbook chap. 3	90minutes
6.	Syntactic analysis	Exercises	100minutes
7.	Semantic analysis (1) semantic representation	Textbook chap. 4	90minutes
7.	Semantic analysis (1) semantic representation	Exercises	100minutes
8.	Semantic analysis (2) analysis method	Textbook chap. 4	90minutes
8.	Semantic analysis (2) analysis method	Exercises	100minutes
9.	Deep learning models for natural language	Read materials	90minutes
9.	Deep learning models for natural language	Exercises	100minutes
10.	Application (1) machine translation	Read materials	90minutes
10.	Application (1) machine translation	Exercises	100minutes
11.	Application (2) text classification	Textbook chap. 5	90minutes
11.	Application (2) text classification	Exercises	100minutes
12.	Application (3) information retrieval	Textbook chap. 5	90minutes
12.	Application (3) information retrieval	Exercises	100minutes
13.	Application (4) dialogue systems	Textbook chap. 5	90minutes
13.	Application (4) dialogue systems	Exercises	100minutes
14.	Summary and future directions	Review all	90minutes
14.	Summary and future directions	Exercises	100minutes
Total.	-	-	2660minutes

Feedback on exams, assignments, etc.

ways of feedback	specific contents about "Other"
Feedback in the class

Textbooks and reference materials

Textbook:
T. Sugimoto and S. Iwashita, "Natural Language Processing and Machine Learning in Java", Ohm-sha, 2018.

Reference materials are:
C. Okazaki et. al., "Basics of Natural Language Processing", Ohm-sha, 2022
S. Kurohashi, "Natural Language Processing, 3rd edition", Open University of Japan, 2023

Prerequisites

Knowledge about Python and Java language, Data Structures and Algorithms, and Artificial Intelligence.

Office hours and How to contact professors for questions

Thursday, lunch break

Regionally-oriented

Non-regionally-oriented course

Development of social and professional independence

Course that cultivates an ability for utilizing knowledge
Course that cultivates a basic problem-solving skills

Active-learning course

More than one class is interactive

Course by professor with work experience

Work experience	Work experience and relevance to the course content if applicable
N/A	N/A

Education related SDGs:the Sustainable Development Goals

4.QUALITY EDUCATION
9.INDUSTRY, INNOVATION AND INFRASTRUCTURE

Last modified : Thu Mar 06 10:20:44 JST 2025