Hasil untuk "Bibliography"

S. Brams, Alan D. Taylor

L. Hörmander

F. W. Warner

R. Carter

U. Grenander, G. Szegő, M. Kac

C. Conley

A. Babin, M. Vishik

S. Campbell, C. D. Meyer

J. Gilbert, T. Royama

S. Murov

U. Beck, E. Beck-Gernsheim, M. Ritter et al.

A. H. Sayed

E. Mortimer, P. Scott

A. Galindo, P. Pascual

J. Lambek, P. Scott

Leela. Gandhi

1 Introduction: after colonialism..2 Thinking otherwise: a brief intellectual history..3 Postcolonialism and the new humanities..4 Edward Said and his critics..5 Postcolonialism and feminism..6 Imagining community: the question of nationalism..7 One world: the vision of postnationalism..8 Postcolonial literatures..9 Conclusion: the limits of postcolonial theory..Bibliography..Index

Steinþór Steingrímsson, Bjarki Ármannsson

We compare the performance of state-of-the-art Large Language Models on a recently released benchmarking set for automated question answering for Icelandic and compare it with performance on questions from an Icelandic trivia game. We find that the models perform worse for questions on Icelandic subjects, specifically Icelandic culture, but somewhat surprisingly do better on a trivia game for people than on the benchmark set meant for language models, built around data that the model has seen during training. We also call into question some aspects of the benchmarking set and discuss what  playing trivia games can tell us - if anything - about the capabilities of these models.

Mahboobeh Delpasand, Somayeh Sadat Akhshik, Siamak Mahboub

Objective: This study was conducted with the aim of investigating the level of readiness of librarians in Iranian public libraries to provide readers’ advisory services. Method: This study was conducted using a descriptive-survey method. The statistical population included all librarians working in public libraries under the supervision of the Public Libraries Institution of the country, and a sample of 365 people was selected by convenience sampling method. The research tool was a researcher-made questionnaire with 80 questions that measured readers' consulting competencies in three dimensions: personal characteristics, knowledge, and skills. The data were analyzed using a five-point Likert scale in SPSS. Results: Librarians are at an average level of overall readiness to provide consulting services. In the personal characteristics dimension, librarians were at the above-average level in the components of critical thinking, professional commitment, creative thinking, self-awareness, and non-judgment. In the knowledge dimension, the cultural, legal, evaluation, and development components were at the above-average level, but the process knowledge component was below-average. In the skill dimension, all components were evaluated to be at the above-average level. Conclusion: Based on the results, librarians need to improve their process knowledge and also more develop their skills to provide more effective consulting services.

Hamood ALshalabi, Sabrina Tiun, Nazlia Omar et al.

<p>Other languages have influenced Arabic because of several factors, such as geographical nearness, trade communication, past Islamic conquests, science and technology, new devices, brand names, models, and fashion. As a result of these factors, foreign words are used in Arabic text and are known as Arabised words. Arabised words affect the Arabic natural language processing (NLP) task because identifying a correct stem or root from an Arabic word becomes more difficult. Therefore, a more efficient Arabic NLP can be developed if Arabised word removal is part of a pre-processing task. In this paper, we propose an algorithm for detecting and extracting Arabised words as a pre-processing task for an Arabic stemming task. This algorithm is a combination of lexicon-based and rule-based approaches. The lexicon list has been developed based on various sources of Arabic text resources, and the rule-based algorithm has been designed to cater to Arabised words with definite articles and use pattern matching on prefixes and suffixes. To evaluate the effectiveness of the proposed Arabised word removal algorithm on the Arabic NLP task, we use Arabised word removal as part of pre-processing in Arabic stemmers. Three Arabic stemmers are used in our evaluation, namely, light stemming, condition light and ARLS, on three types of Arabic standard datasets. Comparisons were made by measuring the performance of precision, recall and IFC on the stemmers with or without our Arabised word removal pre-processing. Results show that the performance on all the stemmers improves if Arabised word removal is included as part of the stemming's pre-processing. Therefore, an efficient Arabic NLP application or task can be developed if Arabised word removal is included in the pre-processing stage for Arabic NLP application, mainly Arabic stemming.</p><p>https://dorl.net/dor/20.1001.1.20088302.2022.20.4.6.5</p>

Achim Oßwald, Martin Iordanidis