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ICML
2000
IEEE
16 years 7 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...
SPAA
2009
ACM
16 years 7 months ago
A DoS-resilient information system for dynamic data management
Denial of service (DoS) attacks are arguably one of the most cumbersome problems in the Internet. This paper presents a distributed information system (over a set of completely co...
Matthias Baumgart, Christian Scheideler, Stefan Sc...
VLDB
2007
ACM
153views Database» more  VLDB 2007»
16 years 6 months ago
Declarative Information Extraction Using Datalog with Embedded Extraction Predicates
In this paper we argue that developing information extraction (IE) programs using Datalog with embedded procedural extraction predicates is a good way to proceed. First, compared ...
Warren Shen, AnHai Doan, Jeffrey F. Naughton, Ragh...
ICDT
2007
ACM
107views Database» more  ICDT 2007»
16 years 20 days ago
Privacy in GLAV Information Integration
Abstract. We define and study formal privacy guarantees for information integration systems, where sources are related to a public schema by mappings given by source-to-target dep...
Alan Nash, Alin Deutsch
PSIVT
2007
Springer
170views Multimedia» more  PSIVT 2007»
16 years 19 days ago
Markov Random Fields and Spatial Information to Improve Automatic Image Annotation
Content-based image retrieval (CBIR) is currently limited because of the lack of representational power of the low-level image features, which fail to properly represent the actual...
Carlos Hernández-Gracidas, Luis Enrique Suc...