Changes between Version 1 and Version 2 of private/NlpInPracticeCourse/TopicModelling


Ignore:
Timestamp:
Jun 18, 2015, 9:54:27 AM (9 years ago)
Author:
ymaterna
Comment:

--

Legend:

Unmodified
Added
Removed
Modified

  • private/NlpInPracticeCourse/TopicModelling

    v1 v2  
    44
    55Prepared by: Jirka Materna
    6 
    7 == TODO til 31.5.2015 ==
    8 
    9  1. choose particular papers for [[#References|References]] below (that will serve as input for the lecture later on)
    10  1. prepare the [[#PracticalSession|Practical Session]]
    116
    127== State of the Art ==
    … …  
    1611Approx 3 current papers (preferably from best NLP conferences/journals, eg. [[https://www.aclweb.org/anthology/|ACL Anthology]]) that will be used as a source for the one-hour lecture:
    1712
    18  1. paper1
    19  1. paper2
    20  1. paper3
     13 1. David M. Blei, Andrew Y. Ng, and Michael I. Jordan. Latent Dirichlet Allocation. Journal of Machine Learning Research, 3:993 – 1022, 2003.
     14 1. Yee W. Teh, Michael I. Jordan, Matthew J. Beal, and David M. Blei. Hierarchical Dirichlet processes . Journal of the American Statistical Association, 101:1566 – 1581, 2006.
     15 1. S. T. Dumais, G. W. Furnas, T. K. Landauer, S. Deerwester, and R. Harshman. Using Latent Semantic Analysis to Improve Access to Textual Information. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI ’88, pages 281–285, New York, NY, USA, 1988. ACM. ISBN 0-201-14237-6.
    2116
    2217== Practical Session ==
    2318
    24 Concrete description of work assignment for students for the second one-hour part of the lecture. The work will consist of tasks connected with practical implementations of algorithms connected with the current topic (probably not the state-of-the-art algorithms mentioned in the first part) and with real data. Students can test the algorithms, evaluate them and possibly try some short adaptations for various subtasks.
     19In this session we will use [[http://radimrehurek.com/gensim/|Gensim]] to model latent topics of various texts. We will focus on Latent Semantic Analysis and Latent Dirichlet Allocation models.
    2520
    26 Students can also be required to generate some results of their work and hand them in to prove completing the tasks.
     21Students will also be required to generate some results of their work and hand them in to prove completing the tasks.