Data analytics involving text

author: Dunja Mladenić, Artificial Intelligence Laboratory, Jožef Stefan Institute
published: Oct. 29, 2015,   recorded: October 2015,   views: 3835


Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.


Data available in electronic form provides great opportunities and challenges for the field of data analytics. In addition to the growing amount of traditional data organized in databases, we are facing large amounts of data provided in different forms, such as texts, sensor measurements, digital traces of users, images and video. In science there are massive data stream of astronomy, high-energy physics, ecology, genetics and molecular biology. Moreover, accessibility of technology is enabling collection of data on various aspects of life including fine-grained human behavior, streams of media text and video, records from social media interactions. Data analytics is thus becoming ever more integrated in different fields of science and life in general. Related to text data, there are two sides of challenges - one when we deal with millions of documents and other when we deal with a single document. The latter may be even more demanding as it relates to the true gist of dealing with text, namely 'text understanding'. The talk will address several related issues focusing on data analytics that involve text with practical examples of applications.

"This is the Information Age - everybody can be informed about anything and everything. There is no secret, therefore there is no sacredness."

See Also:

Download slides icon Download slides: single_mladenic_data_analytics_01.pdf (3.7 MB)

Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Reviews and comments:

Comment1 RANJIT J. SILVA MD.CPE, October 11, 2017 at 4:21 a.m.:

VERY INFORMATIVE. ML and NLP will enable the convergence of "OMIC" Data, Bio-Medical Informatics and Population Health in time to come; and improve patient outcomes.

Write your own review or comment:

make sure you have javascript enabled or clear this field: