NTU Course
Overview

NLP and Information Retrieval with Applications in Social Networks

Offered in 112-2

  • Serial Number

    43320

  • Course Number

    Data5014

  • Course Identifier

    946 U0140

  • No Class

  • 3 Credits

  • Elective

    Data Science Degree Program / Taiwan International Graduate Program On Artificial Intelligence of Things

      Elective

    • Data Science Degree Program

    • Taiwan International Graduate Program On Artificial Intelligence of Things

  • DE-NIAN YANG
  • Thu 7, 8, 9

  • Please contact the department office for more information

  • Type 2

  • 20 Student Quota

    NTU 20

  • No Specialization Program

  • English
  • Core Capabilities and Curriculum Planning
  • Notes

    The course is conducted in English。Schedule Classroom: Auditorium, Institute of Information Science (IIS), Academia Sinica.

  • Limits on Course Adding / Dropping

    • Restriction: MA students and beyond and Restriction: within this department (including students taking minor and dual degree program)

  • NTU Enrollment Status

    Enrolled
    0/20
    Other Depts
    0/0
    Remaining
    0
    Registered
    0
  • Course Description
    待補
  • Course Objective
    This course first goes through the common background required in studying various NLP and IR techniques. Afterwards, algorithms for performing IR and NLP are introduced, and their associated applications then follow each of them respectively. Last, this course is concluded with some selected topics on social networks and deep learning for NLP.
  • Course Requirement
    1.Kindly refer to the TIGP-SNHCC website for the latest syllabus: https://tigpsnhcc.iis.sinica.edu.tw/course.html 2. If there are any questions, please contact the program assistant: tigp.snhcc@gmail.com.
  • Expected weekly study hours before and/or after class
  • Office Hour
  • Designated Reading
    待補
  • References
    待補
  • Grading
    40%

    Exam

    10%

    Class

    50%

    Project

    1. NTU has not set an upper limit on the percentage of A+ grades.
    2. NTU uses a letter grade system for assessment. The grade percentage ranges and the single-subject grade conversion table in the NATIONAL TAIWAN UNIVERSITY Regulations Governing Academic Grading are for reference only. Instructors may adjust the percentage ranges according to the grade definitions. For more information, see the Assessment for Learning Section。
  • Adjustment methods for students
  • Make-up Class Information
  • Course Schedule
    2/22Week 1Course Introduction and Overview, and Basic Text Processing
    2/29Week 2N-gram Language Modeling
    3/07Week 3Text Classification and Clustering
    3/14Week 4Introduction to Spoken Language Processing
    3/21Week 5IE & IR Modeling
    3/28Week 6Evaluation, Relevance Feedback, Query Expansion
    4/04Week 7Sentiment Analysis and Opinion Mining
    4/11Week 8Midterm Exam
    4/18Week 9Final Project Proposal
    4/25Week 10Tokenization and POS Tagging
    5/02Week 11Discourse Relation Analysis
    5/09Week 12Semi-supervised Learning for NLP Tasks
    5/16Week 13FSA, Syntax and Parsing
    5/23Week 14Lexical Semantics
    5/30Week 15Chatbots: Theory and Practice
    6/6Week 16Final Exam