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关键词： 索尔仁尼琴   诺贝尔文学奖   持不同政见者   俄罗斯科学院   语言学   获得者   历史学  

摘要： 亚·伊·索尔仁尼琴(1918-2008),苏俄杰出作家,苏联时期最著名的持不同政见者之一,诺贝尔文学奖获得者,俄罗斯科学院院士,在文学、历史学、语言学等领域有较大成就。

关键词： 篇章语言学   关键词提取   过渡句   概要写作   主题句   关键字词   话语标记语   衔接与连贯  

摘要： 一、引言《普通高中英语课程标准(2017年版)》(教育部,2018)新增了对语篇的要求,具体包括:学生不仅要了解不同的语篇类型及其写作目的、结构特征、语言特点及语篇中的衔接与连贯手段,还要知晓语篇中段首句、主题句、过渡句的作用、位置及行文特征;同时,也要辨析语篇成分之间的语义逻辑关系,明晰语篇中话语标记语的语篇功能及常见用法,辨认关键字词和概念以迅速查找目标信息等。事实上,这些篇章语言学范畴知识皆是概要写作理解及表达的建基理念。

关键词： Sentiment analysis   Linguistics   Neural networks   Task analysis   Markov processes   Cognition   Analytical models   Deep neural networks   linguistic hints   aspect-level sentiment analysis  

摘要： The state-of-the-art techniques for aspect-level sentiment analysis focused on feature modeling using a variety of deep neural networks (DNN). Unfortunately, their performance may still fall short of expectation in real scenarios due to the semantic complexity of natural languages. Motivated by the observation that many linguistic hints (e.g., sentiment words and shift words) are reliable polarity indicators, we propose a joint framework, SenHint, which can seamlessly integrate the output of deep neural networks and the implications of linguistic hints in a unified model based on Markov logic network (MLN). SenHint leverages the linguistic hints for multiple purposes: (1) to identify the easy instances, whose polarities can be automatically determined by the machine with high accuracy;(2) to capture the influence of sentiment words on aspect polarities;(2) to capture the implicit relations between aspect polarities. We present the required techniques for extracting linguistic hints, encoding their implications as well as the output of DNN into the unified model, and joint inference. Finally, we have empirically evaluated the performance of SenHint on both English and Chinese benchmark datasets. Our extensive experiments have shown that compared to the state-of-the-art DNN techniques, SenHint can effectively improve polarity detection accuracy by considerable margins.

关键词： 社会语言学   网络热词   话语分析  

摘要： 近十年来网络热词如雨后春笋般涌现,反映着社会关注的热点。网络热词背后的不仅是当今社会的文化聚焦,更是人们精神思想的升华。本研究运用社会语言学理论来分析近十年(2009-2018年)高频出现的网络热词,探究这些词汇的内在特点,文化内涵,及其所反映的社会现实和舆论走向。

关键词： Bilingualism   Special issue   Introductory paper  

关键词： 英语   语言学   研究   应用语言学  

ISBN: (纸本)9787206180965

摘要： 本书介绍了英语语言学与应用语言学的形成与发展及二者的基本理论，并从英语语音学与英语词汇学入手，对英语语音学及英语词汇学的研究现状作了较全面的阐述；通过研究英语句法学的关系及功能，提出了句法学在英语语言中的应用；以英语语义学和语用学的区别与联系入手，介绍了语义学与语用学的应用；以语料库语言学的研究内容为基础，论述了语料库语言学在英语教学及应用语言学中的应用与意义；为英语语言学与应用语言学的实际运用提供了重要理论依据。

关键词： aggregation operator   evaluation of startup companies   fuzzy   multicriteria decision making   Pythagorean fuzzy sets  

摘要： Evaluating startup companies is an important management process for technology business incubators and it is also a typical multicriteria decision-making (MCDM) problem. There exist various methods that have proposed to solve MCDM problems, but these methods heavily depend on the exact criteria weight values. The decision results of these methods are unstable. Moreover, they cannot provide the improvement suggestions for the nonoptimal startup companies. To overcome these two drawbacks, we propose a novel hesitant fuzzy linguistic decision-making method to solve the problem of evaluating startup companies. To this end, a novel semantic comparison method based on the experts' psychology and the ratio of score value to deviation degree is proposed to compare the hesitant fuzzy linguistic term sets. Then, a novel definition of hesitant fuzzy linguistic information envelopment efficiency (HFLIEE) is proposed, based on which, a novel hesitant fuzzy linguistic information envelopment analysis (HFLIEA) model and a novel preference model are proposed. By solving these models, all the alternatives can be ranked and nonoptimal alternatives can be improved. Finally, the numerical analysis is given to illustrate the applicability of the proposed models and the robustness analyses of the proposed models are provided. At the same time, they are compared with the previous hesitant fuzzy linguistic decision-making methods.

关键词： Noncooperative behaviors   Large-scale group decision-making   Linguistic preference orderings   Consensus   Venture capital  

摘要： In Internet venture capital (VC), it is very important to fully analyze and evaluate the influential factors. Because this activity usually involves amounts of experts, it makes sense to incorporate it into large-scale group decisionmaking (LSGDM). In this process, how to deal with the noncooperative behaviors and express the preference information are two important issues that need to be addressed. Given this, this paper is committed to evaluating the influential factors of Internet VC by managing noncooperative behaviors in LSGDM. Firstly, the preference information can be expressed by linguistic preference orderings (LPOs) which can be used to express unbalanced relationship between any two adjacent alternatives. Then, three kinds of noncooperative behaviors are taken into consideration, and we can identify the group who belongs to one of the three noncooperative behaviors, and then develop methods to manage them respectively. Furthermore, a consensus reaching model is established to manage these noncooperative behaviors. Moreover, we apply the proposed model to solve a practical LSGDM problem involving the evaluations of the influential factors in Internet VC. Finally, comparative analyses between the proposed model and some existing methods are made to show the validity and applicability of the proposed consensus reaching model.

关键词： Central Andes   Archaeological cultures   Pre-Hispanic languages   Linguistics-archaeology interface  

摘要： Interdisciplinary research at the interface of linguistics and archaeology is often concerned with relationships between archaeological cultures and language families, their subgroups, or their proto-languages. This often makes the problematic assumption of a one-to-one correspondence between groupings from the two disciplines. Here, I show how evidence from Northern Peru, a region which once hosted a myriad of well-differentiated local languages and an equally multifaceted sequence of more or less localized preHispanic cultures, can contribute complementary perspectives to existing models. After providing some summary background information, I discuss two regions of Northern Peru -the North Coast and the cloud forests of Chachapoyas- which both exhibit linguistic divisions that correspond to differences in the archaeological record within what has (traditionally) been taken to constitute overarching archaeological cultures;differences in language and cultural expression may both be interpretable as indexes of different preHispanic social, ethnic, or political identities and allegiances. These cases underscore that one-to-one mappings between languages and archaeological cultures (or their expansions) may in some cases be inadequate. (c) 2020 The Author. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Large scale group decision making   Consensus reaching process   Cohesion   Restricted equivalence functions   Hesitant fuzzy linguistic term set  

摘要： Large-scale group decision-making (LSGDM) under uncertainty modelled by comparative linguistic expressions based on a hesitant fuzzy linguistic term set (HFLTS) has recently attracted the interest of many researchers and research, due to the necessity of its function in LSGDM, and the challenges it faces such as the managing of the scalability problem, uncertainty of experts' opinions and dealing with polarized conflicting opinions. To smooth out such discrepancies and obtain agreed solutions Consensus Reaching Processes (CRPs) for LSGDM have been applied, in which experts are grouped into sub-groups according to the closeness of their opinions to deal with scalability. However, most CRPs for LSGDM are driven by a majority rule, in which larger sub-groups, where there might be internal disagreements, lead the consensus. In such processes, the internal disagreements can produce unsatisfactory solutions. Consequently, the majority view should be complemented by additional mechanisms that also measure the strength of the sub-groups' opinions. A good measurement of such strength is the cohesion among the sub-group members. Therefore, in this paper, a new cohesion measure for HFLTS based on restricted equivalence functions for measuring the experts' sub-group cohesiveness is introduced to drive the consensus process together the majority and thus reduce the impact of internal disagreements risen in majority driven CRPs. It is then integrated in a new cohesion-driven CRP approach based on LSGDM to deal with comparative linguistic expressions based on HFLTS. An experimental analysis on different large scale scenarios will show the performance and importance of cohesion in consensus based LSGDM.