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» Evaluating machine learning for information extraction
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157
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SIGSOFT
2008
ACM
16 years 5 months ago
Finding programming errors earlier by evaluating runtime monitors ahead-of-time
Runtime monitoring allows programmers to validate, for instance, the proper use of application interfaces. Given a property specification, a runtime monitor tracks appropriate run...
Eric Bodden, Patrick Lam, Laurie J. Hendren
MLMI
2007
Springer
15 years 10 months ago
Term-Weighting for Summarization of Multi-party Spoken Dialogues
This paper explores the issue of term-weighting in the genre of spontaneous, multi-party spoken dialogues, with the intent of using such term-weights in the creation of extractive ...
Gabriel Murray, Steve Renals
147
Voted
ICDCS
2002
IEEE
15 years 9 months ago
A Fully Distributed Framework for Cost-Sensitive Data Mining
Data mining systems aim to discover patterns and extract useful information from facts recorded in databases. A widely adopted approach is to apply machine learning algorithms to ...
Wei Fan, Haixun Wang, Philip S. Yu, Salvatore J. S...
118
Voted
AI
2005
Springer
15 years 4 months ago
Unsupervised named-entity extraction from the Web: An experimental study
The KNOWITALL system aims to automate the tedious process of extracting large collections of facts (e.g., names of scientists or politicians) from the Web in an unsupervised, doma...
Oren Etzioni, Michael J. Cafarella, Doug Downey, A...
MLMI
2005
Springer
15 years 10 months ago
Foreground Regions Extraction and Characterization Towards Real-Time Object Tracking
Abstract. Object localization and tracking are key issues in the analysis of scenes for video surveillance or scene understanding applications. This paper presents a contribution t...
José Luis Landabaso, Montse Pardàs