-
Wenzel, F.: Semantische Eingrenzung im Freitext-Retrieval auf der Basis morphologischer Segmentierungen (1980)
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Chibout, K.; Vilnat, A.: Primitive sémantiques, classification des verbes et polysémie (1999)
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- Language
- f
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Rosemblat, G.; Tse, T.; Gemoets, D.: Adapting a monolingual consumer health system for Spanish cross-language information retrieval (2004)
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- Abstract
- This preliminary study applies a bilingual term list (BTL) approach to cross-language information retrieval (CLIR) in the consumer health domain and compares it to a machine translation (MT) approach. We compiled a Spanish-English BTL of 34,980 medical and general terms. We collected a training set of 466 general health queries from MedlinePlus en espaiiol and 488 domainspecific queries from ClinicalTrials.gov translated into Spanish. We submitted the training set queries in English against a test bed of 7,170 ClinicalTrials.gov English documents, and compared MT and BTL against this English monolingual standard. The BTL approach was less effective (F = 0.420) than the MT approach (F = 0.578). A failure analysis of the results led to substitution of BTL dictionary sources and the addition of rudimentary normalisation of plural forms. These changes improved the CLIR effectiveness of the same training set queries (F = 0.474), and yielded comparable results for a test set of new 954 queries (F= 0.484). These results will shape our efforts to support Spanishspeakers' needs for consumer health information currently only available in English.
-
Liu, S.; Liu, F.; Yu, C.; Meng, W.: ¬An effective approach to document retrieval via utilizing WordNet and recognizing phrases (2004)
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Rettinger, A.; Schumilin, A.; Thoma, S.; Ell, B.: Learning a cross-lingual semantic representation of relations expressed in text (2015)
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- Source
- The Semantic Web: latest advances and new domains. 12th European Semantic Web Conference, ESWC 2015 Portoroz, Slovenia, May 31 -- June 4, 2015. Proceedings. Eds.: F. Gandon u.a
-
Kocijan, K.: Visualizing natural language resources (2015)
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- Re:inventing information science in the networked society: Proceedings of the 14th International Symposium on Information Science, Zadar/Croatia, 19th-21st May 2015. Eds.: F. Pehar, C. Schloegl u. C. Wolff
-
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)
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- Date
- 15. 3.2000 10:22:37
-
Boleda, G.; Evert, S.: Multiword expressions : a pain in the neck of lexical semantics (2009)
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- Date
- 1. 3.2013 14:56:22
-
Monnerjahn, P.: Vorsprung ohne Technik : Übersetzen: Computer und Qualität (2000)
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- c't. 2000, H.22, S.230-231
-
Cruz Díaz, N.P.; Maña López, M.J.; Mata Vázquez, J.; Pachón Álvarez, V.: ¬A machine-learning approach to negation and speculation detection in clinical texts (2012)
0.02
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- Abstract
- Detecting negative and speculative information is essential in most biomedical text-mining tasks where these language forms are used to express impressions, hypotheses, or explanations of experimental results. Our research is focused on developing a system based on machine-learning techniques that identifies negation and speculation signals and their scope in clinical texts. The proposed system works in two consecutive phases: first, a classifier decides whether each token in a sentence is a negation/speculation signal or not. Then another classifier determines, at sentence level, the tokens which are affected by the signals previously identified. The system was trained and evaluated on the clinical texts of the BioScope corpus, a freely available resource consisting of medical and biological texts: full-length articles, scientific abstracts, and clinical reports. The results obtained by our system were compared with those of two different systems, one based on regular expressions and the other based on machine learning. Our system's results outperformed the results obtained by these two systems. In the signal detection task, the F-score value was 97.3% in negation and 94.9% in speculation. In the scope-finding task, a token was correctly classified if it had been properly identified as being inside or outside the scope of all the negation signals present in the sentence. Our proposal showed an F score of 93.2% in negation and 80.9% in speculation. Additionally, the percentage of correct scopes (those with all their tokens correctly classified) was evaluated obtaining F scores of 90.9% in negation and 71.9% in speculation.
-
Polity, Y.: Vers une ergonomie linguistique (1994)
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Ahmad, F.; Yusoff, M.; Sembok, T.M.T.: Experiments with a stemming algorithm for Malay words (1996)
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-
Vazov, N.: Identification des differentes structures temporelles dans des textes et leur rôles dans le raisonnement temporel (1999)
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- f
-
Ferret, O.; Grau, B.; Masson, N.: Utilisation d'un réseau de cooccurences lexikales pour a méliorer une analyse thématique fondée sur la distribution des mots (1999)
0.02
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- f
-
Hutchins, J.: From first conception to first demonstration : the nascent years of machine translation, 1947-1954. A chronology (1997)
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- Date
- 31. 7.1996 9:22:19
-
Kuhlmann, U.; Monnerjahn, P.: Sprache auf Knopfdruck : Sieben automatische Übersetzungsprogramme im Test (2000)
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- Source
- c't. 2000, H.22, S.220-229
-
Lezius, W.; Rapp, R.; Wettler, M.: ¬A morphology-system and part-of-speech tagger for German (1996)
0.02
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- Date
- 22. 3.2015 9:37:18
-
Fattah, M. Abdel; Ren, F.: English-Arabic proper-noun transliteration-pairs creation (2008)
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- Abstract
- Proper nouns may be considered the most important query words in information retrieval. If the two languages use the same alphabet, the same proper nouns can be found in either language. However, if the two languages use different alphabets, the names must be transliterated. Short vowels are not usually marked on Arabic words in almost all Arabic documents (except very important documents like the Muslim and Christian holy books). Moreover, most Arabic words have a syllable consisting of a consonant-vowel combination (CV), which means that most Arabic words contain a short or long vowel between two successive consonant letters. That makes it difficult to create English-Arabic transliteration pairs, since some English letters may not be matched with any romanized Arabic letter. In the present study, we present different approaches for extraction of transliteration proper-noun pairs from parallel corpora based on different similarity measures between the English and romanized Arabic proper nouns under consideration. The strength of our new system is that it works well for low-frequency proper noun pairs. We evaluate the new approaches presented using two different English-Arabic parallel corpora. Most of our results outperform previously published results in terms of precision, recall, and F-Measure.
-
Gomez, F.: Learning word syntactic subcategorizations interactively (1995)
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Szpakowicz, S.; Bond, F.; Nakov, P.; Kim, S.N.: On the semantics of noun compounds (2013)
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