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Abstract: A growing population of users want to extract a growing variety of information from on-line texts. Unfortunately, current information extraction systems typically require experts to hand-build dictionaries of extraction patterns for each new type of information to be extracted. This paper presents a system that can learn dictionaries of extraction patterns directly from user-provided examples of texts and events to be extracted from them. The system, called LIEP, learns patterns that recognize... (Update)
Context of citations to this paper: More
.... of the operationalized explanation) Other applications in automated software engineering [23] and information pattern extraction [28], while supporting explanation based views of scenario analysis, have not been connected to the partial evaluation aspect, which is...
.... of other systems that learn information extractions rules and do not use any logic programming formalism such as AutoSlog [11] LIEP [8], WHISK [13] and RAPIER [1] More complete and detailed overviews are given in [10] and in [13] 91 5 Summary We have proposed our...
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0.5: Learning Information Extraction Patterns From Examples - Huffman (1995) (Correct)
0.2: Information Extraction Using Hidden Markov Models - Leek (1997) (Correct)
0.2: Flexibly Instructable Agents - Huffman, Laird (1995) (Correct)
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0.2: Connectionist, Statistical and Symbolic Approaches to.. - Wermter, Riloff, Scheler (1996) (Correct)
0.2: Heuristic Joins to Integrate Structured Heterogeneous Data - Huffman, Steier (1995) (Correct)
0.1: Combining Learning From Instruction With Recovery From.. - Douglas Pearson (1995) (Correct)
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20: Automatically constructing a dictionary for information extraction tasks - Riloff - 1993
18: Crystal: Inducing a conceptual dictionary - Soderland, Fisher et al. - 1995
14: Automatically generating extraction patterns from untagged text - Riloff - 1996
BibTeX entry: (Update)
S. B. Huffman. Learning information extraction patterns from examples. In S. Wermter, G. Scheler, and E. Riloff, editors, Proceedings of the 1995 IJCAI Workshop on New Approaches to Learning for Natural Language Processing. 1995. http://citeseer.ist.psu.edu/huffman96learning.html More
@inproceedings{ huffman95learning,
author = "Scott B. Huffman",
title = "Learning information extraction patterns from examples",
booktitle = "Learning for Natural Language Processing",
pages = "246-260",
year = "1995",
url = "citeseer.ist.psu.edu/huffman96learning.html" }
Citations (may not include all citations):371 Explanationbased generalization: A unifying view (context) - Mitchell, Keller et al. - 1986
114 Five papers on WordNet (context) - Miller - 1990
106 Some advances in transformation-based part of speech tagging - Brill - 1994
77 Automatically constructing a dictionary for information extr.. - Riloff - 1993
36 The generic information extraction system (context) - Hobbs - 1993
26 Learning one subprocedure per lesson (context) - VanLehn - 1987
19 MUC-5 evaluation metrics (context) - Chinchor, Sundheim - 1993
19 Wrap-Up: A trainable discourse module for information extrac.. - Soderland, Lehnert - 1994
13 Learning by failing to explain (context) - Hall - 1988
11 Hughes: Description of the CIRCUS system used for MUC (context) - Lehnert, McCarthy et al. - 1993
10 Learning to predict and explain: An integration of similarit.. (context) - Pazzani - 1991
10 FASTUS: A system for extracting information from natural-lan.. (context) - Hobbs, Appelt et al. - 1992
The graph only includes citing articles where the year of publication is known.
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