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151
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ICML
2000
IEEE
16 years 4 months ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
125
Voted
SIGMETRICS
2003
ACM
136views Hardware» more  SIGMETRICS 2003»
15 years 9 months ago
Internet intrusions: global characteristics and prevalence
Network intrusions have been a fact of life in the Internet for many years. However, as is the case with many other types of Internet-wide phenomena, gaining insight into the glob...
Vinod Yegneswaran, Paul Barford, Johannes Ullrich
143
Voted
SIGIR
2009
ACM
15 years 10 months ago
Extracting structured information from user queries with semi-supervised conditional random fields
When search is against structured documents, it is beneficial to extract information from user queries in a format that is consistent with the backend data structure. As one step...
Xiao Li, Ye-Yi Wang, Alex Acero
140
Voted
AICOM
2004
118views more  AICOM 2004»
15 years 3 months ago
Qualitative pattern matching with linguistic terms
Abstract. In the framework of possibility theory, a tool named `fuzzy pattern matching' (FPM) has been proposed in the eighties and since successfully used in flexible queryin...
Yannick Loiseau, Henri Prade, Mohand Boughanem
139
Voted
SIGSOFT
2008
ACM
16 years 4 months ago
Javert: fully automatic mining of general temporal properties from dynamic traces
Program specifications are important for many tasks during software design, development, and maintenance. Among these, temporal specifications are particularly useful. They expres...
Mark Gabel, Zhendong Su