Global Initiatives of Academic Networks (GIAN)

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Course Code : 151013K03 : Introduction to Natural Language Processing

Faculty members:
Prof. Sadao Kurohashi Prof. Pushpak Bhattacharyya Dr. Asif Ekbal Dr. Sriparna Saha
  • Duration: 02/05/2016 - 07/05/2016
  • Brochure on GIAN website is available here : Click here

Course Outline

  • Overview of Natural Language Processing
  • Formal Language Theory
  • Markov Model and N-gram Model
  • Part-of-Speech Tagging
  • Word Sense Disambiguation
  • Probabilistic Parsing
  • Machine Learning Approaches in NLP
  • Information Retrieval
  • Dialogue System
  • Machine Translation
  • Knowledge Acquisition for NLP
Day --1
Day --2
  • Lecture 1 : 9:30 AM to 10:30 AM
    Overview of Natural Language Processing
  • Lecture 2: 10:45 AM to 11:45 AM
    Formal Language Theory
  • Lecture 3. 2:00 PM to 3:00 PM
    N-gram Models
  • Lecture 1: 9:30 AM to 10:30 AM
    Word Sense Disambiguation
  • Lecture 2: 10:45 AM to 11:45 AM
    Markov Model I
  • Lecture 3: 2:00 PM to 3:00 PM
    Markov Model II
Day --3
Day --4
  • Lecture 1: 9:30 AM to 10:30 AM
    Part-of-Speech Tagging
  • Lecture 2: 10:45 AM to 11:45 AM
    Probabilistic Parsing
  • Lecture 3: 2:00 PM to 3:00 PM
    Machine Learning Approaches in NLPI
  • Lecture 1: 9:30 AM to 10:30 AM
    Machine Learning Approaches in NLP II
  • Lecture 2: 10:45 AM to 11:45 AM
    Information Retrieval I
  • Tutorial: 2:00 PM to 3:00 PM
    Some problem solving using machine learning approaches in NLP
Day --5
Day --6
  • Lecture 1: 9:30 AM to 10:30 AM
    Information Retrieval II
  • Tutorial: 10:45 AM to 11:45 AM
    Some real-life problem solving of information retrieval
  • Lecture 2: 2:00 PM to 3:00 PM
    Machine Translation
  • Lecture 1: 9:30 AM to 10:30 AM
    Knowledge Acquisition for NLP
  • Tutorial 1: 10:45 AM to 11:45 AM
    Problem solving session with examples: Parsing, Machine Translation, Information Retrieval
  • Tutorial 2: 2:00 PM to 3:00 PM
    Problem solving session with examples: Parsing, Machine Translation, Information Retrieval
Break for two days Examination for students
How to apply: Click here
Selected candidates : To be updated
Waitlisted candidates : To be updated
Other Information:
Introduction

Natural Language processing (NLP) is a field of computer science and linguistics concerned with the interactions between computers and human (natural) languages. In theory, natural-language processing is a very attractive method of human-computer interaction. Natural-language understanding is sometimes referred to as an artificial intelligence-complete problem, because natural-language recognition seems to require extensive knowledge about the outside world and the ability to manipulate it. NLP has significant overlap with the field of computational linguistics, and is often considered a sub-field of artificial intelligence. Modern NLP algorithms are grounded in machine learning, especially statistical machine learning. Research into modern statistical NLP algorithms requires an understanding of a number of disparate fields, including linguistics, computer science, statistics, linear algebra and optimization theory.

Introduction to natural language processing is the study of human language from a computational perspective. This course will discuss about some basics of NLP. Different topics of NLP like N-gram models, word sense disambiguation, parsing, part-of-speech tagging etc. will be discussed in detail.

The course will also cover a number of standard algorithms that are used throughout language processing. The course will also put light on the Information Retrieval and Machine Translation. Application areas within Language Information Processing include automatic (machine) translation between languages; dialogue systems, which allow a human to interact with a machine using natural language; and information extraction, where the goal is to transform unstructured text into structured (database) representations that can be searched and browsed in flexible ways. The subject qualifies as an Artificial Intelligence and Application concentration subject. Thus overall this course would be useful for the academicians, students and industry people to get introduced to the fundamentals of NLP.

Prof. Sadao Kurohashi, an internationally acclaimed academician, researcher and practitioner with proven knowledge, experience, and demonstrable ability in teaching, consultancy, research, and training in the field of Natural Language Processing will deliver lectures and discuss cases in the course. The course will be planned and offered as per the norms set by IIT Patna for GIAN project.

Objectives

The primary objectives of the course are as follows :

  • Exposing participants to the fundamentals of natural language processing
  • Providing knowledge to analyse sentences algorithmically, using hand-crafted and automatically induced treebank grammars and to provide light on various machine learning approaches
  • Building in confidence and capability amongst the participants in the application of language information processing tools and techniques and solving some of the real-life problems.
  • Providing exposure to practical problems and their solutions, through different projects in language information processing
  • Enhancing the capability of the participants to understand the concepts related to machine translation, information retrieval etc.

Teaching Faculty

Prof. Sadao Kurohashi received the B.S., M.S., and PhD in Electrical Engineering from Kyoto University in the years 1989, 1991 and 1994, respectively. He has been a visiting researcher of IRCS, University of Pennsylvania in 1994. He is currently a professor of the Graduate School of Informatics at Kyoto University, Japan. His webpage: http://nlp.ist.i.kyoto-u.ac.jp/member/kuro/.
He has presented scientific papers in many national and international conferences and published in various journals and books in the field of Natural Language Processing. His current interests include machine translation, information retrieval (a principal member of New IT Infrastructure for the Information-explosion Era by MEXT), and knowledge engineering. He is and has been a regular reviewer for several journals and conferences, and has served in program committees of many conferences. He was an editorial board member of the Journal of Computation Linguistics during the years 2001-2003. He received the 10th anniversary best paper award from Journal of Natural Language Processing in the year 2004, 2009 Funai IT promotion award, and 2009 IBM faculty award. He has been doing pioneer work in the domain of Machine Translation and Information Extraction. Among numerous other awards Prof. Sadao Kurohashi has recently received 2014 Best Paper Award of the Journal of Natural Language Processing.

Who can attend?
  • Executives, engineers and researchers from manufacturing, service and government organizations including R&D laboratories.
  • Students at all levels (BTech/MSc/MTech/PhD) or Faculty from reputed academic institutions and technical institutions.

Registration Fees
Participants from abroad: yet to be decided
Industry/ Research Organizations: yet to be decided
Academic Institutions: yet to be decided
Students : Rs. 1000/-

The above fee includes all instructional materials, computer use for tutorials, 24 hr free internet facility. The participants will be provided accommodation on payment basis.

Course Coordinators
Professor Pushpak Bhattacharya

Director, Indian Institute of Technology Patna
Vijay and Sita Vashee Chair Professor
Department of Computer Science and Engineering
Indian Institute of Technology Bombay
Ph: 91-22-25764729 (o), 25721955(h)
Email: pb[at]cse.iitb.ac.in
Webpage:Click here

Dr. Asif Ekbal
Assistant Professor
Department of Computer Science and Engineering
Indian Institute of Technology Patna
Patna, India-800013
Email: asif[at]iitp.ac.in
Ph: +91-612-2552090(o), 08521274830 (h)
Webpage : Click here

Dr. Sriparna Saha
Assistant Professor
Department of Computer Science and Engineering
Indian Institute of Technology Patna
Patna, India-800013
Ph: +91-612-22552128 (o), 08809559190(m)
Email: sriparna[at]iitp.ac.in
Webpage: Click here