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Annals of Emerging Technologies in Computing 2023年第5期7卷 11-24页

作者： Sainin, Mohd Shamrie Sintian, Minah Alias, Suraya Tahir, Asni Language Engineering and Application Development Faculty of Computing and Informatics Universiti Malaysia Sabah Malaysia Faculty of Languages and Communication Universiti Pendidikan Sultan Idris Malaysia

A computer-aided language translation using a Machine translation (MT) is an application performed by computers (machines) that translates one natural language to another. There are many online language translation tools, but thus far none offers a sequence of text translations for the under-resourced Kadazandusun language. Although there are web-based and mobile applications of Kadazandusun dictionaries available, the systems do not translate more than one word. Hence, this paper aims to present the discussion of the preliminary translation of Malay to Kadazandusun. The basic word-to-word with dictionary alignment translation based on Direct Machine Translation (DMT) is selected to begin the exploration of the translation domain where DMT is one of the earliest translation methods which relies on the word-to-word approach (sequence-to-sequence model). This paper aims to investigate the under-resourced language and the task of translating from the Malay language to the Kadazandusun language or vice versa. This paper presents the application and the process as well as the results of the system according to the basic Kadazandusun word arrangement (Verb-Subject-Object) and its translation quality using the Bilingual Evaluation Understudy (BLEU) score. Several phases are involved during the process, including data collection (word pair translation), preprocessing, text selection, translation procedures, and performance evaluation. The preliminary language translation approach is proven to be capable of producing up to 0.5 BLEU scores which indicate that the translation is readable, however, requires post-editing for better comprehension. The findings are significant for the quality of the under-resourced language translation and as a starting point for other machine translation methodologies such as statistical or deep learning-based translation. © 2023 by the author(s).

关键词： Computer aided language translation

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Multimodal language Data and Platform Construction for LCTLs Teaching 23

Multimodal Language Data and Platform Construction for LCTLs...

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15th International Conference on Machine Learning and Computing, ICMLC 2023

作者： Wang, Yuan Jin, Kai Liu, Wuying Shandong Key Laboratory of Language Resources Development and Application Ludong University China School of Foreign Languages Qilu University of Technology China Laboratory of Language Engineering and Computing Guangdong University of Foreign Studies China

ISBN: (纸本)9781450398411

The progress of artificial intelligence technology has brought great opportunities for the development of Less Commonly Taught languages (LCTLs) teaching. However, the scarcity of LCTLs resources still plagues the current teaching platform. This paper is committed to building multimodal language data including foreign language vocabulary and translation, bilingual example sentences, phonetic symbols and audio, morphological similarity recommendation, semantic similarity recommendation, etc., and using full-text index and Web Service technology to build a new LCTLs teaching platform. The detailed steps are: (1) acquiring and processing multimodal language data through web pages such as TED and Opensubtitles;(2) constructing the inverted indexes used the HashMap and storing the index files in the cache of the platform, which avoids the heavy database intervention;(3) using the classical Levenshtein distance in the morphological similar words and semantic similar words recommendation algorithm. The platform implemented based on the above data and technology finally supports Japanese, Italian, Indonesian, Malaysian, Vietnamese, Filipino, and Myanmar seven languages. © 2023 ACM.

关键词： Websites

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RETHINKING CNN'S GENERALIZATION TO BACKDOOR ATTACK FROM FREQUENCY DOMAIN 12

RETHINKING CNN'S GENERALIZATION TO BACKDOOR ATTACK FROM FREQ...

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12th International Conference on Learning Representations, ICLR 2024

作者： Rao, Quanrui Wang, Lin Liu, Wuying Shandong Key Laboratory of Language Resources Development and Application Ludong University China School of Information and Electrical Engineering Ludong University China Xianda College of Economics and Humanities Shanghai International Studies University China

Convolutional neural network (CNN) is easily affected by backdoor injections, whose models perform normally on clean samples but produce specific outputs on poisoned ones. Most of the existing studies have focused on the effect of trigger feature changes of poisoned samples on model generalization in spatial domain. We focus on the mechanism of CNN memorize poisoned samples in frequency domain, and find that CNN generate generalization to poisoned samples by memorizing the frequency domain distribution of trigger changes. We also investigated the assistance provided by perturbations generated at different frequencies to the generalization, and explore the influence of trigger perturbations in different frequency domain components on the generalization of poisoned models from visible and invisible backdoor attacks. We prove that high-frequency components are more susceptible to perturbations than low-frequency components. Based on the above fundings, we propose a universal invisible strategy for visible triggers, which can achieve trigger invisibility while maintaining raw attack performance. We also design a novel frequency domain backdoor attack method based on low-frequency semantic information, which can achieve 100% attack accuracy on multiple models and multiple datasets, and can bypass multiple defenses. © 2024 12th International Conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Semantics

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Comparative Analysis of Para-social Interaction among Multiple Luxury Brands 4

Comparative Analysis of Para-social Interaction among Multip...

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4th International Conference on Natural language Processing, ICNLP 2022

作者： Yu, Dandan Liu, Wuying Ludong University Shandong Key Laboratory of Language Resources Development and Application Yantai264025 China Guangdong University of Foreign Studies Laboratory of Language Engineering and Computing Guangzhou510420 China

ISBN: (数字)9781665495448

ISBN: (纸本)9781665495448

The luxury industry is good at using the most advanced science and technology to promote product sales. With the recent rise of virtual spokespersons, more and more virtual spokespersons are widely used in luxury marketing. We studied the new advertising mode based on virtual spokespersons, and analyzed how luxury brands use virtual spokespersons to establish para-social interactions with their audiences. We also analyzed the data of likes, reposts and comments on the official Weibo of luxury brands such as Valentino, Dior, Ferragamo, Louis Vuitton, and March Jacobs that have published advertising Weibos which contain virtual spokespersons and do not include celebrity spokespersons and various marketing campaign. Finally, according to the conclusion of our analysis, we propose development suggestions for the promotion strategy of luxury brands' virtual spokespersons in Weibo or other media, and the way to establish para-social interaction between luxury brands and their audiences. © 2022 IEEE.

关键词： Marketing

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Externally-contracted multi-reference configuration interaction method using a DMRG reference wave function

arXiv

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arXiv 2018年

作者： Luo, Zhen Ma, Yingjin Wang, Xicun Ma, Haibo School of Chemistry and Chemical Engineering Nanjing University Nanjing210023 China Department of High Performance Computing Technology and Application Development Computer Network Information Center Chinese Academy of Sciences Beijing100190 China Center of Scientific Computing Applications & Research Chinese Academy of Sciences Beijing100190 China Nanjing Foreign Language School Nanjing210008 China

The recent development of the density matrix renormalization group (DMRG) method in multireference quantum chemistry makes it practical to evaluate static correlation in a large active space, while dynamic correlation provides a critical correction to the DMRG reference for strong-correlated systems and is usually obtained using multi-reference perturbation (MRPT) or configuration interaction (MRCI) methods with internal contraction (ic) approximation. These methods can use active space scalable to relatively larger size references than has previously been possible. However, they are still hardly applicable to systems with active space larger than 30 orbitals and/or large basis set because of high computation and storage costs of high-order reduced density matrices (RDMs) and the crucial dependence of the MRCI Hamiltonian dimension on the number of virtual orbitals. In this work, we propose a new effective implementation of DMRG-MRCI, in which we use re-constructed CASCI-type configurations from DMRG wave function via the entropy-driving genetic algorithm (EDGA) [Luo et. al., J. Chem. Theory Comput., 2017, 13, 4699-4710.], and integrate it with MRCI by an external contraction (ec) scheme. This bypasses the bottleneck of computing high-order RDMs in traditional DMRG dynamic correlation methods with ic approximation and the number of MRCI configurations is not dependent on the number of virtual orbitals. Therefore, DMRG-ec-MRCI method is promising for dealing with larger active space than 30 orbitals and large basis sets. We demonstrate the capability of our DMRG-ec-MRCI method in several benchmark applications, including the evaluation of potential energy curve of Cr2, single-triplet gaps of higher n-acene molecules and the energy of Eu-BTBP(NO3)3 complex. Copyright © 2018, The Authors. All rights reserved.

关键词： Quantum chemistry

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Research of automatically generate mapping mechanism based on the semantic role

International Journal of Database Theory and Application

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International Journal of Database Theory and application 2016年第10期9卷 163-176页

作者： Wang, Feng Cui, Lei Wang, Yizhen Wei, Xinjiang School of Mathematics and Statistics Science Ludong University Yan Tai264025 China Key Laboratory of Language Resource Development and Application of Shandong Province Yan Tai China Information Engineering Department Yan Tai Vocational College Yan Tai264025 China Tilburg University Tilburg Netherlands

Role based access control (RBAC) has been widely adopted in industrial and government. However RBAC is only suitable for closed enterprise environment. With modern Internet based application, collaboration and sharing among multiple organizations become essential and RBAC is no longer sufficient. Role mapping has been the solutions to deal with multiple domains, where the roles in the hierarchy of one organization are mapped to the roles in the hierarchy of another organization. But role mapping can be a tedious task for the security officers if it is done fully manually. Yet, performing role mapping automatically incur security risks. In this paper, we introduce a semi-automated role mapping process, where promising role mappings are generated automatically and recommended to the security officer(s). The security officers then approve or modify the recommended role mappings. We present a method for automatically generate role mappings based on the similarities of the roles in two role hierarchies. We use an example to illustrate our approach and show its feasibility. 2016 SERSC.

关键词： Mapping

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System of automatic Chinese webpage summarization based on the random walk algorithm of dynamic programming

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Open Cybernetics and Systemics Journal 2015年第1期9卷 1315-1322页

作者： Wang, Feng Qin, Xiaoming Wang, Yizhen Wei, Xinjiang School of Mathermatics and Statistics Science Ludong University Yantai264025 China Key Laboratory of Language Resource Development and Application of Shandong Province Yantai264025 China College of Computer and Information Engineering Jiaozuo Teachers College Jiaozuo454000 China Institute of Computer Application Technology Jiaozuo Teachers College Jiaozuo454000 China Tilburg University Tilburg Netherlands

As the Internet becomes more and more deeply connected with our life, the Internet has brought together mass text material, and it is still in explosive growth. In order to quickly and accurately to help users find the required content, the traditional solution is to use a search engine. However, the results of existing automatic webpage summarization systems for search engine are of low quality. Because they just based on statistical method, gather some sentences in the web document beside the search phrases. Neither symbolizes the subject of the document, nor take into account the user search phrases. According to the shortages, An automatic webpage summarization systems is realized. On the basis of the work done, this paper proposed an automatic text summarization method based on relation graph and text structure analysis. This method firstly segment text into semantic paragraphs. For each semantic paragraph, a subject term discover method based on relation graph analysis is proposed. At last, both search phrase and document subject are take into account, it extracts summary according to the guidance of the subject terms. © Wang et al.

关键词： Semantics

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Research on intelligent semantic search base on HowNet

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Open Cybernetics and Systemics Journal 2015年第1期9卷 1358-1364页

作者： Wang, Feng Zhang, Hui Wang, Yizhen Zhang, Guanghua School of Mathermatics and Statistics Science Ludong University Yantai264025 China Key Laboratory of Language Resource Development and Application of Shandong Province Yantai264025 China College of Information Science and Engineering Hebei University of Science and Technology Shijiazhuang China Tilburg University Tilburg Netherlands

The HDWiki is same as the famous Wikipedia but major in Chinese include vase investment of manual effort and judgment, we divided this structured information into three categories: concept, relationship and entity. This paper describe a novel symbol oriented search that facilitate user to format unambiguous query, especially to format complex logical query which need several query to get answer on traditional search but just once here, it is building a bridge between what user know and what user wished, between the intent of user query and the understanding of search engine. This facilitation and understanding base on the ternary relationships what are everywhere in the HDWiki and HowNet powered semantic similarity measure for knowledge matching. We realize a logical semantic oriented search system and conducted a detailed user study with users, and found that this logical semantic oriented search and its underlying knowledge base provides significant advantages over conventional search. It offers assistance to almost every query especially complex logical queries, making the query entry more clear and efficient for user as well as for search engine, broadening the processing scope of complex logical query in the search, improving the relevance of the searched documents, and increased the probability of getting what user wished. © Wang et al.

关键词： Search engines

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