Temporal Dynamics of On-Line Information Streams View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2016-07-12

AUTHORS

Jon Kleinberg

ABSTRACT

A number of recent computing applications involve information arriving continuously over time in the form of a data stream, and this has led to new ways of thinking about traditional problems in a variety of areas. In some cases, the rate and overall volume of data in the stream may be so great that it cannot all be stored for processing, and this leads to new requirements for efficiency and scalability. In other cases, the quantities of information may still be manageable, but the data stream perspective takes what has generally been a static view of a problem and adds a strong temporal dimension to it. Our focus here is on some of the challenges that this latter issue raises in the settings of text mining, on-line information, and information retrieval. More... »

PAGES

221-238

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-540-28608-0_11

DOI

http://dx.doi.org/10.1007/978-3-540-28608-0_11

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1025345274


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