| 1. |
- Gawronska, Barbara
(författare)
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Arv och miljö grunden för språkutvecklingen
- 2005
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Ingår i: Perspektiv på Högskolan i Skövde. - Skövde : Högskolan i Skövde. - 1653-8242. ; 2:2, s. 8-9
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Tidskriftsartikel (populärvet., debatt m.m.)
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| 2. |
- Gawrońska, Barbara
(författare)
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Computational Linguistics in Sweden
- 2007
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Ingår i: Acta Sueco-Polonica. - : Wydawnictwo Academica SWPS Warszawa. - 1104-3431. ; 14, s. 29-40
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Tidskriftsartikel (refereegranskat)
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| 3. |
- Gawronska, Barbara
(författare)
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Information Extraction from Texts : Adapting a System for Summarization of News Reports to the Domain of Bioinformatics
- 2005
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Ingår i: Transactions on Advanced Research. - : IPSI BgD. - 1820-4511. ; 1:1, s. 20-28
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Tidskriftsartikel (refereegranskat)abstract
- Natural language serves as important information source in all areas of human activity. The presence of a huge amount of texts on the Internet actualizes the problem of efficient information search; visual scanning of all the textual information is difficult and time-consuming. There is a need for efficient, high-quality systems that extract the relevant information from texts. The paper presents the architecture of an experimental system for automatic text understanding and information extraction, which has originally been developed for the domain of news reports. The possibility of adapting the methodology for the purpose of bioinformatics is discussed, and the similarities and differences between texts in the two different domains are discussed and exemplified.
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| 4. |
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| 5. |
- Olsson, Björn, et al.
(författare)
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Deriving pathway maps from automated text analysis using a grammar-based approach
- 2006
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Ingår i: Journal of Bioinformatics and Computational Biology. - : World Scientific. - 0219-7200 .- 1757-6334. ; 4:2, s. 483-501
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Tidskriftsartikel (refereegranskat)abstract
- We demonstrate how automated text analysis can be used to support the large-scale analysis of metabolic and regulatory pathways by deriving pathway maps from textual descriptions found in the scientific literature. The main assumption is that correct syntactic analysis combined with domain-specific heuristics provides a good basis for relation extraction. Our method uses an algorithm that searches through the syntactic trees produced by a parser based on a Referent Grammar formalism, identifies relations mentioned in the sentence, and classifies them with respect to their semantic class and epistemic status (facts, counterfactuals, hypotheses). The semantic categories used in the classification are based on the relation set used in KEGG (Kyoto Encyclopedia of Genes and Genomes), so that pathway maps using KEGG notation can be automatically generated. We present the current version of the relation extraction algorithm and an evaluation based on a corpus of abstracts obtained from PubMed. The results indicate that the method is able to combine a reasonable coverage with high accuracy. We found that 61% of all sentences were parsed, and 97% of the parse trees were judged to be correct. The extraction algorithm was tested on a sample of 300 parse trees and was found to produce correct extractions in 90.5% of the cases.
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| 6. |
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| 7. |
- Sigurd, Bengt, et al.
(författare)
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The potential of Swetra - A multilanguage MT system
- 1988
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Ingår i: Computers and Translation. - 0884-0709. ; 3, s. 237-250
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Tidskriftsartikel (refereegranskat)abstract
- One may indicate the potentials of an MT system by stating what text genres it can process, e.g., weather reports and technical manuals. This approach is practical, but misleading, unless domain knowledge is highly integrated in the system. Another way to indicate which fragments of language the system can process is to state its grammatical potentials, or more formally, which languages the grammars of the system can generate. This approach is more technical and less understandable to the layman (customer), but it is less misleading, since it stresses the point that the fragments which can be translated by the grammars of a system need not necessarily coincide exactly with any particular genre. Generally, the syntactic and lexical rules of an MT system allow it to translate many sentences other than those belonging to a certain genre. On the other hand it probably cannot translate all the sentences of a particular genre. Swetra is a multilanguage MT system defined by the potentials of a formal grammar (standard referent grammar) and not by reference to a genre. Successful translation of sentences can be guaranteed if they are within a specified syntactic format based on a specified lexicon. The paper discusses the consequences of this approach (Grammatically Restricted Machine Translation, GRMT) and describes the limits set by a standard choice of grammatical rules for sentences and clauses, noun phrases, verb phrases, sentence adverbials, etc. Such rules have been set up for English, Swedish and Russian, mainly on the basis of familiarity (frequency) and computer efficiency, but restricting the grammar and making it suitable for several languages poses many problems for optimization. Sample texts — newspaper reports — illustrate the type of text that can be translated with reasonable success among Russian, English and Swedish.
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