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» Evaluating machine learning for information extraction
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ICAIL
2005
ACM
15 years 7 months ago
Automatic Legal Text Summarisation: Experiments with Summary Structuring
We describe a set of experiments using machine learning techniques for the task of extractive summarisation. The research is part of a summarisation project for which we use a cor...
Ben Hachey, Claire Grover
133
Voted
DL
1999
Springer
187views Digital Library» more  DL 1999»
15 years 6 months ago
KEA: Practical Automatic Keyphrase Extraction
Keyphrases provide semantic metadata that summarize and characterize documents. This paper describes Kea, an algorithm for automatically extracting keyphrases from text. Kea ident...
Ian H. Witten, Gordon W. Paynter, Eibe Frank, Carl...
WWW
2008
ACM
16 years 2 months ago
As we may perceive: finding the boundaries of compound documents on the web
This paper considers the problem of identifying on the Web compound documents (cDocs) ? groups of web pages that in aggregate constitute semantically coherent information entities...
Pavel Dmitriev
IR
2006
15 years 1 months ago
Table extraction for answer retrieval
The ability to find tables and extract information from them is a necessary component of many information retrieval tasks. Documents often contain tables in order to communicate d...
Xing Wei, W. Bruce Croft, Andrew McCallum
ICML
2005
IEEE
16 years 2 months ago
Q-learning of sequential attention for visual object recognition from informative local descriptors
This work provides a framework for learning sequential attention in real-world visual object recognition, using an architecture of three processing stages. The first stage rejects...
Lucas Paletta, Gerald Fritz, Christin Seifert