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关键词： Demonstratives   Pointing   Visibility   Space   Linguistic diversity  

摘要： In all spoken languages, speakers use demonstratives - words like this and that e to refer to entities in their immediate environment. But which factors determine whether they use one demonstrative (this) or another (that)? Here we report the results of an experiment examining the effects of referent visibility, referent distance, and addressee location on the production of demonstratives by speakers of Ticuna (isolate;Brazil, Colombia, Peru), an Amazonian language with four demonstratives, and speakers of Dutch (Indo-European;Netherlands, Belgium), which has two demonstratives. We found that Ticuna speakers' use of demonstratives displayed effects of addressee location and referent distance, but not referent visibility. By contrast, under comparable conditions, Dutch speakers displayed sensitivity only to referent distance. Interestingly, we also observed that Ticuna speakers consistently used demonstratives in all referential utterances in our experimental paradigm, while Dutch speakers strongly preferred to use definite articles. Taken together, these findings shed light on the significant diversity found in demonstrative systems across languages. Additionally, they invite researchers studying exophoric demonstratives to broaden their horizons by cross-linguistically investigating the factors involved in speakers' choice of demonstratives over other types of referring expressions, especially articles. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Fuzzy-set theory   Fuzzy data mining   Fuzzy-list structure   Pruning strategies  

摘要： Traditional association-rule mining (ARM) considers only the frequency of items in a binary database, which provides insufficient knowledge for making efficient decisions and strategies. The mining of useful information from quantitative databases is not a trivial task compared to conventional algorithms in ARM. Fuzzy-set theory was invented to represent a more valuable form of knowledge for human reasoning, which can also be applied and utilized for quantitative databases. Many approaches have adopted fuzzy-set theory to transform the quantitative value into linguistic terms with its corresponding degree based on defined membership functions for the discovery of FFIs, also known as fuzzy frequent itemsets. Only linguistic terms with maximal scalar cardinality are considered in traditional fuzzy frequent itemset mining, but the uncertainty factor is not involved in past approaches. In this paper, an efficient fuzzy mining (EFM) algorithm is presented to quickly discover multiple FFIs from quantitative databases under type-2 fuzzy-set theory. A compressed fuzzy-list (CFL)-structure is developed to maintain complete information for rule generation. Two pruning techniques are developed for reducing the search space and speeding up the mining process. Several experiments are carried out to verify the efficiency and effectiveness of the designed approach in terms of runtime, the number of examined nodes, memory usage, and scalability under different minimum support thresholds and different linguistic terms used in the membership functions.

关键词： Natural language processing   Linguistic analysis   Knowledge graphs   Embeddings  

摘要： In essence, embedding algorithms work by optimizing the distance between a word and its usual context in order to generate an embedding space that encodes the distributional representation of words. In addition to single words or word pieces, other features which result from the linguistic analysis of text, including lexical, grammatical and semantic information, can be used to improve the quality of embedding spaces. However, until now we did not have a precise understanding of the impact that such individual annotations and their possible combinations may have in the quality of the embeddings. In this paper, we conduct a comprehensive study on the use of explicit linguistic annotations to generate embeddings from a scientific corpus and quantify their impact in the resulting representations. Our results show how the effect of such annotations in the embeddings varies depending on the evaluation task. In general, we observe that learning embeddings using linguistic annotations contributes to achieve better evaluation results. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Twitter   Linguistic tone   Event study   Stock price reaction   Investor sentiment  

摘要： We investigate U.S. presidential candidates' unprecedented use of Twitter to compliment on specific firms during election campaigns. We examine the linguistic tone used in presidential candidates' tweets and we find that it significantly affects stock market reaction. Trump's tweets bearing positive linguistic tone about specific firms shows daily CAR of 0.20%, whereas the positive tone from all Republican yields a CAR of 0.24%. Linguistic tone effects are particularly significant when media firms are excluded from the sample. Our results suggest that investors recognize the importance for firm value of information transmitted on social media by an influential source. (C) 2021 Elsevier B.V. All rights reserved.

ISBN: (纸本)9787030689948

关键词： Cognitive animacy   Japanese   Persian   Existential verb constructions   Number agreement  

摘要： Animacy, commonly defined as the distinction between living and non-living entities, is a useful notion in cognitive science and linguistics employed to describe and predict variation in psychological and linguistic behaviour. In the (psycho)linguistics literature we find linguistic animacy dichotomies which are (implicitly) assumed to correspond to biological dichotomies. We argue this is problematic, as it leaves us without a cognitively grounded, universal description for non-prototypical cases. We show that 'animacy' in language can be better understood as universally emerging from a gradual, cognitive property by collecting animacy ratings for a great range of nouns from Japanese and Persian. We used these cognitive ratings in turn to predict linguistic variation in these languages traditionally explained through dichotomous distinctions. We show that whilst (speakers of) languages may subtly differ in their conceptualisation of animacy, universality may be found in the process of mapping conceptual animacy to linguistic variation. (c) 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： Dynamic multi-attribute decision making   Probabilistic linguistic term set   Bayesian network   Dominance degree   Prospect theory  

摘要： In the evolution of an emergency, Internet public opinions usually catalyze escalation and spread of the emergency, and even affect the evolution of public opinions. Therefore, how to effectively manage Internet public opinions has become urgent. As an essential part of the Internet public opinion management, assessing the heat degree of Internet public opinions is necessary. Being problemoriented, this paper analyzes the development and evolution of Internet public opinions, and identifies the characteristics of the heat degree assessment of Internet public opinions. Taking into account the continuously changing exterior environment, the dynamic nature of Internet public opinions, and the inadequacy and uncertainty of decision-making information, assessing the heat degree of Internet public opinions is regarded as a dynamic multi-attribute decision making problem under the probabilistic linguistic environment. Thus, this paper aims to develop a dynamic decision-making framework to assess the heat degrees of Internet public opinions under the probabilistic linguistic environment. First, the probabilistic linguistic Bayesian network (PLBN) is constructed, in which the nodes denote attributes and related factors, and the hierarchical network structure shows the relationship among attributes. Then, the probability information obtained by PLBN in the form of PLTS is converted into attribute weight information. Moreover, this paper starts from the nature of PLTS, discusses PLTSs in terms of the probability distribution, and then gives the concept of the dominance degree of PLTS, based on which, a dynamic decision-making model based on the idea of prospect theory that considers DMs' bounded rationality is developed. Finally, five emergency events happened

关键词： Order evaluation model   Nested probabilistic-numerical linguistic information   AHP   Order grabbing mode  

摘要： With the popularization of information technology and the acceleration of the people's pace of life, the takeout food industry is prevailing. The choice of order allocation mode plays an important role in order delivery efficiencies. This paper firstly reviews the whole process of the order grabbing mode and its internal logic, and then analyzes the qualitative and quantitative factors that influence the order distribution efficiency. Next, the order evaluation model is established based on the nested probabilistic-numerical linguistic information. After that, influencing factors of the order allocation modes are established, and the weights of the factors are determined by the AHP method. Finally, the order distribution results are obtained by traditional mode and the novel mode respectively. The comparative analysis and further analysis verify the validity and operability of the novel mode. By comparing the final values of multi-criteria functions between two modes, we conclude that the novel mode improves the allocation efficiency of order grabbing mode. In addition, the proposed mode significantly reduces the service distance and the standard deviation of service distance. The completion rate of delivery orders and the consistency of service level are also greatly improved. The takeout order allocation problem is optimized through the order evaluation model based on the nested probabilistic-numerical linguistic information. The proposed method has guiding effect on similar platforms.

关键词： Decision making   Non-reciprocal probabilistic linguistic   preference relation   Partially consistent   Consistency repairing   Social donation   COVID-19 outbreaks  

摘要： A non-reciprocal fuzzy preference relation (NrFPR) can express partial relations of alternatives, including indifference relations, preference relations and incomparability relations, but cannot depict linguistic preference intensities. A probabilistic linguistic preference relation (PLPR) can represent preference intensities in forms of probabilities and linguistic terms, but the incomparability relations of alternatives were not defined in a PLPR. Given that the NrFPR and PLPR can overcome each other's drawbacks, this study proposes the non-reciprocal probabilistic linguistic preference relation (NrPLPR). Six conditions are given to express the partial relations of alternatives. Since the P-cut of probabilistic linguistic term sets (PLTSs) is effective in the operations of PLTSs without information loss, we construct the P-cut matrix of an NrPLPR by an adaptive P-determination method. Afterwards, nine rules are provided to define the partially consistent NrPLPR. To repair the inconsistent NrPLPR, a two-stage consistency repairing process, containing the linguistic information and probability repairing stages, is introduced. In addition, a non-reciprocal probabilistic linguistic nondominated selection procedure is proposed to rank alternatives. A case study on selecting social donation channels under the COVID-19 outbreaks is given to demonstrate the applicability of the proposed method. A comparative analysis is done to show the effectiveness of the proposed method. (c) 2021 Elsevier Inc. All rights reserved.