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ICML
2000
IEEE
16 years 1 days 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...
COSIT
2003
Springer
145views GIS» more  COSIT 2003»
15 years 4 months ago
Extracting Landmarks with Data Mining Methods
Abstract. The navigation task is a very demanding application for mobile users. The algorithms of present software solutions are based on the established methods of car navigation ...
Birgit Elias
MM
2000
ACM
166views Multimedia» more  MM 2000»
15 years 3 months ago
Automatically extracting highlights for TV Baseball programs
In today’s fast-paced world, while the number of channels of television programming available is increasing rapidly, the time available to watch them remains the same or is decr...
Yong Rui, Anoop Gupta, Alex Acero
ICSE
1999
IEEE-ACM
15 years 3 months ago
Lightweight Extraction of Object Models from Bytecode
A program’s object model captures the essence of its design. For some programs, no object model was developed during design; for others, an object model exists but may be out-of...
Daniel Jackson, Allison Waingold
ICSE
1998
IEEE-ACM
15 years 3 months ago
Extracting Concepts from File Names: A New File Clustering Criterion
Decomposing complex software systems into conceptually independent subsystems is a significant software engineering activity which received considerable research attention. Most o...
Nicolas Anquetil, Timothy Lethbridge