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Most Viewed Text Mining Lectures


View some of the most popular text mining lectures from videolectures.net and learn about topics including mining web data and building large-scale information retrieval systems.



VideoLectures.NET By Grant Marshall, Sept 2014

Today, we look at the top 25 most viewed text mining lectures on videolectures.net

The way popularity is determined is by looking at the “popular” sort on the text mining video listing. These are the videos, including authors, length, and venue, sorted by views:

  1. Challenges in Building Large-Scale Information Retrieval Systems, Jeffrey Dean, 13694 views, 1:05:00 (March 12, 2009, at Second ACM International Conference on Web Search and Data Mining - WSDM 2009)
  2. Text Classification, William Cohen, 11193 views, 0:55:47 (February 25, 2007, at Autumn School 2006: Machine Learning over Text and Images - Pittsburgh)
  3. Učenje povzemanja besedil s pretvorbo v semantično mrežo, Jure Leskovec, 8265 views, 0:34:50 (February 25, 2007, at VideoLectures.NET - Single Lectures Series)
  4. Information Retrieval and Text Mining, Thomas Hofmann, 4831 views, 1:32:51 (February 25, 2007, at Machine Learning Summer School (MLSS), Berder Island 2004)
  5. Text Mining and Link Analysis for Web and Semantic Web, Marko Grobelnik, Dunja Mladenić, Blaž Fortuna, 4157 views, 2:36:52 (August 12, 2007, at Tutorials)
  6. Text and web data mining, Marko Grobelnik, 3684 views, 3:04:27 (October 17, 2007, at 2nd ECOLEAD Summer School, Prague 2007)
  7. Latent Semantic Variable Models, Thomas Hofmann, 3623 views, 0:58:41 (February 25, 2007, at Workshop on Subspace, Latent Structure and Feature Selection Techniques: Statistical and Optimisation Perspectives, Bohinj 2005)
  8. Large Scale Learning at Twitter, Aleksander Kołcz, Marko Grobelnik, 2618 views, 1:04:02 (August 13, 2012, at 9th Extended Semantic Web Conference (ESWC), Heraklion 2012)
  9. Introduction to the Machine Learning over Text & Images - Autumn School by Eric Xing, Eric P. Xing, 2498 views, 0:16:07 (February 25, 2007, at Autumn School 2006: Machine Learning over Text and Images - Pittsburgh)
  10. Text Mining, Information and Fact Extraction (TMIFE), Marie-Francine Moens, 2091 views, 7:44:46 (November 4, 2008, at 2nd Russian Summer School in Information Retrieval (RuSSIR), Taganrog 2008)
  11. Information Retrieval and Text Mining, Thomas Hofmann, 1889 views, 3:24:32 (February 25, 2007, at Machine Learning Summer School (MLSS), Canberra 2006)
  12. Active, Semi-Supervised Learning for Textual Information Access, Anastasia Krithara, 1813 views, 0:18:28 (February 25, 2007, at Workshop on Intelligent Information Access (IIA), Helsinki 2006)
  13. A Holistic Lexicon-Based Approach to Opinion Mining, Bing Liu, 1602 views, 0:24:21 (February 25, 2008, at First ACM International Conference on Web Search and Data Mining - WSDM 2008)
  14. Explanation of SVM's behaviour in text classification, Fabrice Colas, 1426 views, 0:58:35 (October 24, 2007, at Solomon seminar)
  15. Automated Text Summarization using MEAD: Experience with the IMF Staff Reports, Shuhua Liu, 1407 views, 0:29:51 (February 25, 2007, at Workshop on Intelligent Information Access (IIA), Helsinki 2006)
  16. Text mining, Marko Grobelnik, 1219 views, 1:05:19 (February 25, 2007, at Advanced Course on AI (ACAI), Ljubljana 2005)
  17. Personalized Web Search Engine for Mobile Devices, Vasudeva Varma, 1202 views, 0:22:27 (February 25, 2007, at Workshop on Intelligent Information Access (IIA), Helsinki 2006)
  18. Java library for support of text mining and retrieval, Peter Bednar, 1179 views, 0:23:50 (February 25, 2007, at 6th IFIP International Conference on Information Technology for for Balanced Automation Systems in Manufacturing and Services (BASYS), Vienna 2004)
  19. Link Analysis and Text Mining : Current State of the Art and Applications for Counter Terrorism, Ronen Feldman, 1167 views, 2:09:14 (December 3, 2007, at NATO Advanced Study Institute on Mining Massive Data Sets for Security)
  20. Semi-supervised Learning for Text Classification, Anastasia Krithara, 1167 views, 0:17:36 (November 9, 2007, at Students Session)
  21. Latent Variable Models for Document Analysis, Wray Buntine, 976 views, 0:50:56 (March 11, 2008, at Machine Learning Summer School (MLSS), Kioloa 2008)
  22. Never Ending Language Learning, Tom Mitchell, 930 views, 0:55:55 (July 13, 2012, at Joint Workshop on Automatic Knowledge Base Construction and Web-scale Knowledge Extraction (AKBC-WEKEX), Montreal 2012)
  23. Automatic Discovery of Patterns in News Content, Nello Cristianini, 513 views, 0:41:53 (April 25, 2012, at Cognitive Systems Workshop & Thematic Programmes and Pump Priming Workshops, Cumberland Lodge 2012)
  24. Open Information Extraction from the Web, Oren Etzioni, 377 views, 0:49:50 (July 13, 2012, at Joint Workshop on Automatic Knowledge Base Construction and Web-scale Knowledge Extraction (AKBC-WEKEX), Montreal 2012)
  25. Analyzing Text and Social Network Data with Probabilistic Models, Padhraic Smyth, 362 views, 1:10:19 (October 29, 2012, at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Bristol 2012)

First, we will look at the contents of the titles of these lectures to get a feel for the important topics covered.

Top Text Mining Lecture Words

Looking at this visualization, it is clear how prominent the web is in these text analytics lectures. It is also clear that many text analytics lectures cover the information retrieval and machine learning aspects of the problem as well.

Now we will look at how the length of the videos correlates with popularity.

Top Text Mining post length vs. views

As with all other topics covered thus far, text analytics lectures correlate longer length with higher popularity. This is the case whether we measure popularity by videolectures’s metric or by pure view counts.

One notable thing about the text analytics lectures, though, is the number of lectures under one hour. Sixty percent of these top 25 lectures were under one hour in length, which compared to the Data Mining (36%) and Machine Learning (44%) lectures is very high, and is only beat by the Big Data lectures, which has 64% of its lectures under one hour. This could indicate that text analytics lectures tend to be focused on more specific topics that don’t demand longer lectures.

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