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Abstract: Introduction 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 e#ciency and scalability. In other cases, the quantities of information may still be manageable, but the... (Update)
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BibTeX entry: (Update)
@misc{ kleinberg-temporal,
author = "Streams Jon Kleinberg",
title = "Temporal Dynamics of On-Line Information",
url = "citeseer.ist.psu.edu/766252.html" }
Citations (may not include all citations):1362 A tutorial on hidden Markov models and selected applications.. (context) - Rabiner - 1989 ACM
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116 Topic Detection and Tracking Pilot Study: Final Report - Allan, Carbonell et al. - 1998
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19 Bursty and Hierarchical Structure in Streams - Kleinberg - 2002 ACM DBLP
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14 Extracting significant time-varying features from text - Swan, Allan - 1999
14 Mining of Concurrent Text and Time Series - Lavrenko, Schmill et al. - 2000
12 Maximizing the Spread of Influence through a Social Network - Kempe, Kleinberg et al. - 2003
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11 the bursty evolution of Blogspace - Kumar, Novak et al. - 2003
10 TimeMines: Constructing Timelines with Statistical Models of.. - Swan, Jensen - 2000
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2 NewsJunkie: Providing Personalized Newsfeeds via Analysis of.. - Gabrilovich, Dumais et al. - 2004
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2 Lexical dynamics and conceptual change: Analyses and implica.. (context) - Liebscher, Belew - 2003
1 Identifying Similarities, Periodicities and Bursts for Onlin.. (context) - Vlachos, Meek et al. - 2004
1 Information Di#usion through Blogspace (context) - Gruhl, Guha et al. - 2004
1 Mapping topics and topic bursts in PNAS (context) - Mane, Borner - 2004
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