Appelt, D. E., & Israel, D. J. (1999). Introduction to information extraction technology. A Tutorial Prepared for IJCAI-99.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....computational linguistics in this thesis. Instead, we would like to summarize the advantages and disadvantages of the two approaches, noting that, in general, one s weakness is the strength of the other s. Statistical models have the following advantages [Price, 1996; Young and Bloothooft, 1997; Appelt and Israel, 1999] They can be trained automatically (provided there is enough data) which facilitates their porting to new domains and uses. The probabilities can directly be used as scores, thus, they can provide a systematic and convenient mechanism for combining multiple knowledge sources. Weak and vague ....

Appelt, D. E. and Israel, D. J. 1999. Introduction to Information Extraction Technology. In Proceedings of the 16th International doint Conference on Artificial Intelligence.

....computational linguistics in this thesis. Instead, we would like to summarize the advantages and disadvantages of the two approaches, noting that, in general, one s weakness is the strength of the other s. Statistical models have the following advantages [Price, 1996; Young and Bloothooft, 1997; Appelt and Israel, 1999] They can be trained automatically (provided there is enough data) which facilitates their porting to new domains and uses. The probabilities can directly be used as scores, thus, they can provide a systematic and convenient mechanism for combining multiple knowledge sources. Weak and vague ....

Appelt, D. E. and Israel, D. J. 1999. Introduction to Information Extraction Technology. In Proceedings of the 16th International Joint Conference on Artificial Intelligence.

....performance. This training is effective but time consuming. In the second approach, once a training corpus has been annotated, a classifier is run so that the system learns how to analyze new texts. This is faster but requires sufficient volume of training data to achieve reasonable outcomes [2]. Most IE systems compromise by using rules that are manually created and classifier components that are automatically generated. To elaborate, IE systems use part or all of the following components: Firstly, Segmentation divides the document into segments, e.g. sentences, and the other ....

Appelt DE. and Israel DJ., Introduction to Information Extraction Technology, Tutorial for IJCAI-99, Stockholm, August 1999.

....IE systems at that time because they made the comparison of their performance possible (by deming a common task, a common data set and common scorers for all participants) They also eased the exchange and implementation of successful ideas and approaches between the participants. As mentioned in [Appelt99], one of the main benefits is that people tried to do things that without MUC they probably wouldn t try or maybe even think of . 1.4.2 Automatic Content Extraction (ACE) ACE is a program similar to MUC and its objective is to stimulate developments in automatic content extraction from ....

D. Appelt and D. Israel: "Introduction to Information Extraction Technology". Tutorial, LICAI-99, 1999.

....techniques and information retrieval. In this chapter, we outline a roadmap for future direction in building the next generation information access system. 8. 1 Information Extraction Many question answering systems ( 32, 29, 5, 10] just to name a few) today utilize information extraction (IE) [1] techniques as an important component of their architecture. In question answering, information extraction technology is used to match the semantic type expected by the user query with the semantic type of the answer. By analyzing the question, it is possible to anticipate the type of the answer, ....

Douglas E. Appelt and David Israel. Introduction to information extraction technology. In IJCAI-99 Tutorial, 1999.

....computational linguistics in this thesis. Instead, we would like to summarize the advantages and disadvantages of the two approaches, noting that, in general, one s weakness is the strength of the other s. Statistical models have the following advantages [Price, 1996; Young and Bloothooft, 1997; Appelt and Israel, 1999] ffl They can be trained automatically (provided there is enough data) which facilitates their porting to new domains and uses. ffl The probabilities can directly be used as scores, thus, they can provide a systematic and convenient mechanism for combining multiple knowledge sources. ffl ....

Appelt, D. E. and Israel, D. J. 1999. Introduction to Information Extraction Technology. In Proceedings of the 16th International Joint Conference on Artificial Intelligence.

....ressources a depuis t conteste [Mikheev et al. 1999] Pour les systmes fonds sur l apprentissage, BBN a montr que de larges corpus tiquets devaient tre utiliss pour obtenir un bon niveau de performance (un corpus de 1. 2 million de mot tiquet est ncessaire pour obtenir 0,91 P R, Bikel et al. 1997] [Appelt and Israel, 1999]) mais, depuis, Collins et Singer ont propos une exprience o l apprentissage portait sur un corpus non tiquet 1 [Collins et Singer, 1999] Nous proposons d valuer ici les diffrents lments constitutifs d un analyseur d entits nommes, notamment l intrt et l importance relative des dictionnaires, ....

....un corpus annot, d acqurir automatiquement une liste de noms propres sans connaissances a priori. Il est toutefois signaler que ces approches sont leur tour contestes dans la mesure o le cot de constitution d un corpus annot peut tre suprieur celui du dveloppement d un dictionnaire reprsentatif [Appelt and Israel, 1999]. De plus, des techniques d acquisition automatique aident leur tour la constitution de larges dictionnaires, tandis que l tiquetage de corpus a un cot de rvision non nul. La grammaire : son rle est de regrouper des squences d lments reconnus lors de la phase d analyse lexicale. Une rgle de ....

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Douglas E. Appelt and David Israel (1999). Introduction to Information Extraction Technology. International Joint Conference on Artificial Intelligence (IJCAI-99) Tutorial, Stockholm, Sweden (available at: http://www.ai.sri.com/~appelt/ie-tutorial/)

....Norwegian Computing Center, P.B. 114 Blindern, N 0314 Oslo, Norway Tel. 47) 22 85 25 00 Fax: 47) 22 69 76 60 8 2. 4 Approaches to IE There are two main approaches to the design of IE systems, which can be called the knowledge engineering approach and the automatic training approach [3]. In the knowledge engineering approach grammars expressing rules for the system are constructed by hand using knowledge of the application domain. The skill of the knowledge engineer plays a large role in the level of performance of the system, but the best performing systems are often hand ....

D. E. Appelt, D. J. Israel. Introduction to Information Extraction Technology. Tutorial for IJCAI-99, Stockholm, August 1999.

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Appelt, D. E., & Israel, D. J. (1999). Introduction to information extraction technology. A Tutorial Prepared for IJCAI-99.

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D. E. Appelt and D. Israel. Introduction to information extraction technology. In Proceedings of 16th International Joint Conference on Articial Intelligence IJCAI-99, Tutorial, 1999.

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