Course title
1M9810001
Natural Language Processing Systems

 SUGIMOTO Tooru Click to show questionnaire result at 2019
Course content
In recent years, the application of natural language processing technologies is spreading into various fields. This course will explain the basics of the natural language processing system, and methods of realizing these systems and application cases will be studied through lectures, experiments and by having students read literature in turns.
Purpose of class
Students can learn basic theories and techniques of processing natural language.
Goals and objectives
  1. Be able to explain specifically basic theories and technologies for natural language processing systems
  2. Be able to explain characteristics of natural language processing technology in terms of its application
  3. Be able to explain clearly and discuss about natural language processing technology
Relationship between 'Goals and Objectives' and 'Course Outcomes'

 Presentation Report Total.
1. 20% 20% 40%
2. 20% 20% 40%
3. 20% 20%
Total. 60% 40% -
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 systems Textbook chap. 1 90minutes
review 90minutes
2． Morphological analysis Textbook chap. 9 90minutes
review 90minutes
3． Semantics of words and sentences Textbook chap. 5 and 6 90minutes
consult related matters and discuss about experiment 120minutes
4． Presentation of experiment plans prepare presentation 120minutes
review 90minutes
5． Information retrieval and document processing Textbook chap. 13 90minutes
consult related matters and conduct experiment 120minutes
6． Syntactic and semantic analysis Textbook chap. 10 and 11 90minutes
consult related matters and conduct experiment 120minutes
7． Deep learning models for natural language Textbook chap. 8 90minutes
consult related matters and conduct experiment 120minutes
8． Report of experiment results (1) Morphological analysis prepare presentation 90minutes
review 90minutes
9． Report of experiment results (2) Semantics of words and sentences prepare presentation 90minutes
review 90minutes
10． Report of experiment results (3) Document classification prepare presentation 90minutes
read research paper 90minutes
11． Natural language dialogue systems Textbook chap. 15 90minutes
read research paper 90minutes
12． Examples of natural language processing systems (1) Syntactic/semantic analysis prepare presentation 90minutes
write report 90minutes
13． Examples of natural language processing systems (2) Information retrieval prepare presentation 90minutes
write report 90minutes
14． Examples of natural language processing systems (3) Dialogue systems prepare presentation 90minutes
write report 90minutes
Total. - - 2670minutes
Evaluation method and criteria
Presentations 60% and reports 40% for a total possible score of 100.
You can get 60 or more points if you appropriately conduct all required presentations and submit all assignments.
Feedback on exams, assignments, etc.
ways of feedback specific contents about "Other"
Feedback in the class
Textbooks and reference materials
S. Kurohashi, "Natural Language Processing, 3rd edition", Open Universitiy of Japan, 2023.
C. Okazaki et al., "Basics of Natural Language Processing", Ohm-sha, 2022.
T. Sugimoto and S. Iwashita, "Natural Language Processing and Machine Learning in Java", Ohm-sha, 2018.
Prerequisites
Having knowledge about data structures, algorithms, and natural language processing is desirable.
Having basic programming skills is required.
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 a basic problem-solving skills
  • Course that cultivates a basic interpersonal skills
  • Course that cultivates an ability for utilizing knowledge
Active-learning course
About half of the classes are 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
  • 9.INDUSTRY, INNOVATION AND INFRASTRUCTURE
Last modified : Mon Feb 17 04:07:52 JST 2025