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  • × theme_ss:"Computerlinguistik"
  1. Proszeky, G.: Language technology tools in the translator's practice (1999) 0.00 
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    Date
    30. 3.2002 18:29:40
  2. McMahon, J.G.; Smith, F.J.: Improved statistical language model performance with automatic generated word hierarchies (1996) 0.00 
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    Source
    Computational linguistics. 22(1996) no.2, S.217-248
  3. Ruge, G.: ¬A spreading activation network for automatic generation of thesaurus relationships (1991) 0.00 
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    Date
    8.10.2000 11:52:22
  4. Somers, H.: Example-based machine translation : Review article (1999) 0.00 
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    Date
    31. 7.1996 9:22:19
  5. New tools for human translators (1997) 0.00 
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    Date
    31. 7.1996 9:22:19
  6. Baayen, R.H.; Lieber, H.: Word frequency distributions and lexical semantics (1997) 0.00 
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    Date
    28. 2.1999 10:48:22
  7. ¬Der Student aus dem Computer (2023) 0.00 
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    Date
    27. 1.2023 16:22:55
  8. Fang, L.; Tuan, L.A.; Hui, S.C.; Wu, L.: Syntactic based approach for grammar question retrieval (2018) 0.00 
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    Abstract
    With the popularity of online educational platforms, English learners can learn and practice no matter where they are and what they do. English grammar is one of the important components in learning English. To learn English grammar effectively, it requires students to practice questions containing focused grammar knowledge. In this paper, we study a novel problem of retrieving English grammar questions with similar grammatical focus. Since the grammatical focus similarity is different from textual similarity or sentence syntactic similarity, existing approaches cannot be applied directly to our problem. To address this problem, we propose a syntactic based approach for English grammar question retrieval which can retrieve related grammar questions with similar grammatical focus effectively. In the proposed syntactic based approach, we first propose a new syntactic tree, namely parse-key tree, to capture English grammar questions' grammatical focus. Next, we propose two kernel functions, namely relaxed tree kernel and part-of-speech order kernel, to compute the similarity between two parse-key trees of the query and grammar questions in the collection. Then, the retrieved grammar questions are ranked according to the similarity between the parse-key trees. In addition, if a query is submitted together with answer choices, conceptual similarity and textual similarity are also incorporated to further improve the retrieval accuracy. The performance results have shown that our proposed approach outperforms the state-of-the-art methods based on statistical analysis and syntactic analysis.
  9. Rahmstorf, G.: Information retrieval using conceptual representations of phrases (1994) 0.00 
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    Abstract
    The information retrieval problem is described starting from an analysis of the concepts 'user's information request' and 'information offerings of texts'. It is shown that natural language phrases are a more adequate medium for expressing information requests and information offerings than character string based query and indexing languages complemented by Boolean oprators. The phrases must be represented as concepts to reach a language invariant level for rule based relevance analysis. The special type of representation called advanced thesaurus is used for the semantic representation of natural language phrases and for relevance processing. The analysis of the retrieval problem leads to a symmetric system structure
  10. Zue, V.: Dein Computer spricht mir dir (1999) 0.00 
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    Date
    31.12.1996 19:29:41
  11. Mustafa El Hadi, W.: Evaluating human language technology : general applications to information access and management (2002) 0.00 
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    Source
    Knowledge organization. 29(2002) nos.3/4, S.124-134
  12. Müller, P.: Text-Automat mit Tücken (2023) 0.00 
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    Source
    Pirmasenser Zeitung. Nr. 29 vom 03.02.2023, S.2
  13. Byrne, C.C.; McCracken, S.A.: ¬An adaptive thesaurus employing semantic distance, relational inheritance and nominal compound interpretation for linguistic support of information retrieval (1999) 0.00 
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    Date
    15. 3.2000 10:22:37
  14. Boleda, G.; Evert, S.: Multiword expressions : a pain in the neck of lexical semantics (2009) 0.00 
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    Date
    1. 3.2013 14:56:22
  15. Monnerjahn, P.: Vorsprung ohne Technik : Übersetzen: Computer und Qualität (2000) 0.00 
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    Source
    c't. 2000, H.22, S.230-231
  16. Stede, M.: Lexicalization in natural language generation : a survey (1994/95) 0.00 
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    Abstract
    In natural language generation, a meaning representation of some kind is successively transformed into a sentence or a text. Naturally, a central subtask of this problem is the choice of words, or lexicalization. Proposes 4 major issues that determine how a generator tackles lexicalization, and surveys the contributions that research have made to them. Identifies open problems, and sketches a possible direction for research
  17. Kurz, C.: Womit sich Strafverfolger bald befassen müssen : ChatGPT (2023) 0.00 
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    Abstract
    Ein Europol-Bericht widmet sich den Folgen von ChatGPT, wenn Kriminelle die Fähigkeiten des Chatbots für sich ausnutzen: Es drohe vermehrt Phishing und noch mehr Desinformation. Ein Problem für die Strafverfolgung könne auch automatisiert erzeugter bösartiger Quellcode sein.
  18. Griffiths, T.L.; Steyvers, M.: ¬A probabilistic approach to semantic representation (2002) 0.00 
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    Date
    29. 6.2015 14:55:01
    29. 6.2015 16:09:05
  19. Ahlgren, P.; Kekäläinen, J.: Indexing strategies for Swedish full text retrieval under different user scenarios (2007) 0.00 
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    Abstract
    This paper deals with Swedish full text retrieval and the problem of morphological variation of query terms in the document database. The effects of combination of indexing strategies with query terms on retrieval effectiveness were studied. Three of five tested combinations involved indexing strategies that used conflation, in the form of normalization. Further, two of these three combinations used indexing strategies that employed compound splitting. Normalization and compound splitting were performed by SWETWOL, a morphological analyzer for the Swedish language. A fourth combination attempted to group related terms by right hand truncation of query terms. The four combinations were compared to each other and to a baseline combination, where no attempt was made to counteract the problem of morphological variation of query terms in the document database. The five combinations were evaluated under six different user scenarios, where each scenario simulated a certain user type. The four alternative combinations outperformed the baseline, for each user scenario. The truncation combination had the best performance under each user scenario. The main conclusion of the paper is that normalization and right hand truncation (performed by a search expert) enhanced retrieval effectiveness in comparison to the baseline. The performance of the three combinations of indexing strategies with query terms based on normalization was not far below the performance of the truncation combination.
  20. Hodgson, J.P.E.: Knowledge representation and language in AI (1991) 0.00 
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    Abstract
    The aim of this book is to highlight the relationship between knowledge representation and language in artificial intelligence, and in particular on the way in which the choice of representation influences the language used to discuss a problem - and vice versa. Opening with a discussion of knowledge representation methods, and following this with a look at reasoning methods, the author begins to make his case for the intimate relationship between language and representation. He shows how each representation method fits particularly well with some reasoning methods and less so with others, using specific languages as examples. The question of representation change, an important and complex issue about which very little is known, is addressed. Dr Hodgson gathers together recent work on problem solving, showing how, in some cases, it has been possible to use representation changes to recast problems into a language that makes them easier to solve. The author maintains throughout that the relationships that this book explores lie at the heart of the construction of large systems, examining a number of the current large AI systems from the viewpoint of representation and language to prove his point.

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  • d 39
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  • a 123
  • el 17
  • m 10
  • s 4
  • x 4
  • p 2
  • d 1
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