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The Cross-Language Evaluation Forum has encouraged research in text retrieval methods for numerous European languages and has developed durable test suites that allow language-specific techniques to be investigated and compared. The labor associated with crafting a retrieval system that takes advantage of sophisticated linguistic methods is daunting. We examine whether language-neutral methods can achieve accuracy comparable to language-specific methods with less concomitant software complexity. Using the CLEF 2002 test set we demonstrate empirically how overlapping character n-gram tokenization can provide retrieval accuracy that rivals the best current language-specific approaches for European languages. We show that n = 4 is a good choice for those languages, and document the increased storage and time requirements of the technique. We report on the benefits of and challenges posed by n-grams, and explain peculiarities attendant to bilingual retrieval. Our findings demonstrate clearly that accuracy using n-gram indexing rivals or exceeds accuracy using unnormalized words, for both monolingual and bilingual retrieval. 相似文献
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This article reports on a large‐scale international survey of authors' perception and experience of the journals system conducted by ciber in association with National Opinion Polls (NOP). It explores the factors that inform authors' decisions where to publish and, in particular, which groups of readers they perceive to be most important. It probes readership behaviour and the values that underlie authors' attitudes towards copyright and emerging business models, notably open access. It is concluded that many aspects of author behaviour are highly conservative and that a significant shift towards open access is, in the short to medium term, highly unlikely. 相似文献
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Dylan J.H.A. Henssen Loes van den Heuvel Guido De Jong Marc A.T.M. Vorstenbosch Anne-Marie van Cappellen van Walsum Marianne M. Van den Hurk Jan G.M. Kooloos Ronald H.M.A. Bartels 《Anatomical sciences education》2020,13(3):353-365
Neuroanatomy education is a challenging field which could benefit from modern innovations, such as augmented reality (AR) applications. This study investigates the differences on test scores, cognitive load, and motivation after neuroanatomy learning using AR applications or using cross-sections of the brain. Prior to two practical assignments, a pretest (extended matching questions, double-choice questions and a test on cross-sectional anatomy) and a mental rotation test (MRT) were completed. Sex and MRT scores were used to stratify students over the two groups. The two practical assignments were designed to study (1) general brain anatomy and (2) subcortical structures. Subsequently, participants completed a posttest similar to the pretest and a motivational questionnaire. Finally, a focus group interview was conducted to appraise participants’ perceptions. Medical and biomedical students (n = 31); 19 males (61.3%) and 12 females (38.7%), mean age 19.2 ± 1.7 years participated in this experiment. Students who worked with cross-sections (n = 16) showed significantly more improvement on test scores than students who worked with GreyMapp-AR (P = 0.035) (n = 15). Further analysis showed that this difference was primarily caused by significant improvement on the cross-sectional questions. Students in the cross-section group, moreover, experienced a significantly higher germane (P = 0.009) and extraneous cognitive load (P = 0.016) than students in the GreyMapp-AR group. No significant differences were found in motivational scores. To conclude, this study suggests that AR applications can play a role in future anatomy education as an add-on educational tool, especially in learning three-dimensional relations of anatomical structures. 相似文献
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