Linguistic Terms Research Articles

Fuzzy Bayesian inference for under-five mortality data

Under-five mortality remains a significant global health challenge, with millions of children dying before their fifth birthday each year. This study explores the application of fuzzy Bayesian inference for under-five mortality data using Tanzania as a case study. Fuzzy Bayesian inference has emerged as a promising technique that combines the flexibility of fuzzy set theory with the probabilistic framework of Bayesian inference. The study employs fuzzy sets and membership functions to represent the linguistic terms and their degrees of membership, along with the Poisson distribution to model the mortality rate. The results demonstrate the potential of fuzzy Bayesian inference for analyzing under-five mortality rates. This approach provides a more nuanced understanding of the complex mortality patterns.

Multi-position two-phase person-position matching decision-making with intermediary participation

With the rapid development in society, intermediaries play an increasingly important role in person-position matching decision-making. To obtain reasonable enterprise-intermediary matching and enterprise-candidate matching schemes under multiple positions, preferences of enterprises, headhunting companies and candidates should be fully considered from a two-phase perspective. Thus, a two-sided matching decision-making method under the probabilistic linguistic environment is proposed to solve the multi-position two-phase person-position matching problem. First, related theories of probabilistic linguistic term sets and two-sided matching are given. On this basis, the problem of multi-position two-phase person-position matching under the probabilistic linguistic environment is described. The decision-making process is divided into the following two phases: In the first phase, satisfactions of enterprises and headhunting companies are calculated considering subject expectations based on prospect theory. Then, considering the maximization of satisfactions of two-sided subjects, the many-to-many two-sided matching model between enterprises and headhunting companies is established and solved to obtain the optimal many-to-many matching scheme. In the second phase, according to evaluation matrices and expectation matrices, satisfactions of enterprises and candidates under multiple positions are calculated considering intermediary evaluations. Then, considering the maximization of satisfactions of enterprises and candidates, one-to-many matching models and one-to-one stable matching models under multiple positions are developed and solved to obtain the optimal person-position matching schemes under multiple positions. Finally, an example of the person-position matching with intermediary participation is used to illustrate the feasibility and effectiveness of the proposed method.

Wine tasting notes as formulaic texts

The linguistic term “formulaic language” refers to fixed expressions or sequences of words that are often used as a single unit and are typically stored in memory and retrieved as complete units during communication, rather than being constructed or analyzed anew each time by the rules of grammar. Today, however, the concept of formulaicity has expanded beyond individual word combinations to include larger units as formulaic texts. In certain text genres such as abstracts and recipes, formulaicity is visible not only at the level of wording, but also in text content, structure, and layout. But it has not been examined in other text genres where professionals could benefit from this fixed structure in order to produce acceptable texts. In the present article we aim to analyze if wine tasting notes can be considered formulaic in nature. To meet our expectations, a corpus of wine tasting notes written originally in English will be used and collocations that help build up a text examined; by using Biel’s text-organizing patterns and term-embedding collocations, and by analyzing tasting notes in terms of Gülich’s criteria for formulaic texts, the present study will try to show if wine tasting notes are indeed formulaic. Our findings enhance dictionary entries by capturing the full spectrum of sensory experiences and professional terminology in oenology, improving lexical entries in both oenology and general monolingual dictionaries through the identification and categorization of formulaic language in wine tasting notes.

A novel distance measure for probabilistic linguistic term sets with application to emergency decision-making

A novel distance measure for probabilistic linguistic term sets with application to emergency decision-making

Framework for E-commerce Warehouse Site Selection Evaluation: The Impact of Consumer Repurchase Intention

Supply chains play a decisive role in the development of e-commerce. Although site selection problem for e-commerce warehouses is an important aspect of supply chain management, this topic has received insufficient research attention. This paper fills this research gap by proposing an evaluation framework for the e-commerce warehouse site selection. This framework incorporates consumer repurchase intention (CRI) as a key factor in the evaluation to analyze its impact. This study also employs the matter-element evaluation model to classify the levels of alternatives, and then adopts the probabilistic linguistic terms set to optimize the research results. The feasibility and effectiveness of the proposed evaluation framework is validated through a case study of e-commerce warehouse site selection in China. The results of the case study demonstrate the performance of the proposed framework and highlight the significant impact of CRI on the evaluation outcomes. The proposed framework makes full use of the evaluation information and significantly improves the differences between adjacent alternatives, which can enhance the credibility and accuracy of decision results to provide a more reliable alternative ranking for decision makers.

Entropy measures of multigranular unbalanced hesitant fuzzy linguistic term sets for multiple criteria decision making

The hesitant fuzzy linguistic term set (HFLTS) is an efficient tool for modeling linguistic information in multi-criteria decision making (MCDM), and the entropy measure of HFLTS, as a substantial representation of uncertainty, merits additional investigation. This article aims to exploit a general framework to facilitate the construction of entropy measure for multigranular unbalanced HFLTS. An axiomatic definition of the entropy for HFLTSs that considers both types of uncertainty (fuzziness and hesitation) is presented, with the entropy measure subsequently derived from distance-based mapping. From this definition, several deduced results have been developed for the mapping that depicts the entropy expression in order to get such functions with ease. Whereafter, a MCDM weight-determining model for multigranular unbalanced linguistic information without preset weights is devised, and an empirical application of the suggested model in MCDM is illustrated. Ultimately, comparisons and analyses with existing studies are conducted to demonstrate the advantages of the proposed work.

Fermatean fuzzy Linguistic term set based on linguistic scale function with Dombi aggregation operator and their application to multi criteria group decision –making problem

The selection of an industrial location is a challenging multiple-criteria decision-making (MCDM) problem that depends on taking a variety of locations as well as incompatible and inconsistent criteria. This paper proposed a comprehensive framework for the strategic selection of industrial locations, considering both quantitative and qualitative aspects. Decision-makers (DMs) have to deal with ambiguous information throughout this process due to a complex decision environment or their insufficient knowledge. We present a new Fermatean Fuzzy (FF) Linguistic term set based on the Dombi aggregation operators (AOs). By combining the FF set with Linguistic variables, the FF Linguistic (FFL) set is an effective approach for thoroughly representing uncertain evaluation information. We establish a basic operational principles and certain aggregation operator under FFL information, such as the FF Linguistic Dombi weighted averaging (FFLDWA) operator FF Linguistic Dombi weighted geometric (FFLDWG) operator and some fundamental properties of these operators with appropriated elaboration. Based on these operators, a multi-criteria group decision-making technique is developed. Finally, we used a numerical example to compare the flexibility of the suggested technique with other existing methods. Thus, by knowing priorities industries, the best site can be selected.

Hotel recommendation mechanism based on online reviews considering multi-attribute cooperative and interactive characteristics

Online reviews of hotels provide important information to consumers. The process of extracting useful information from diverse online reviews is crucial for making the best final decisions. To explore the hidden intrinsic information behind online reviews, this paper optimizes information extraction by integrating multiple sources, and gives the recommendation alternative. First, to meet quantitative requirements, the probabilistic linguistic term set is introduced to demonstrate the massive number of comments crawled. Second, considering preference and fluctuation, the relative importance of multiple attributes is determined. Because multiple attributes typically have cooperative or mutually exclusive relationships, a novel model is presented by introducing such relationship to modify relative importance. Third, inspired by the 2-additive Choquet integral operator and the Mahalanobis-Taguchi System, a bi-objective optimization model is proposed to illustrate the interactive effect of comments and develop an attribute correlation network. The specific relationships between attributes are reflected, including the positive and negative interactions. The relative importance, interactive imporantce and subgroup utility can be obtained. Fourth, to guarantee the operability and interpretability of the recommendation results, this paper presents a new information fusion operator and an probabilistic linguistic three-way recommendation process. Finally, a case study is used to demonstrate the complete procedures, and the parameter and comparative analyses highlight the effectiveness of the new operator and recommendation method.

Railway Transportation Scheme Selection Based a CODAS-COPRAS Method in Triangular Dense Fuzzy Linguistic Term Lock Environment

Railway Transportation Scheme Selection Based a CODAS-COPRAS Method in Triangular Dense Fuzzy Linguistic Term Lock Environment

Managing flexible linguistic expressions with subjective preferences and objective information in group decision-making: A perspective based on personalized individual semantics

Flexible linguistic expression (FLE) is a complex linguistic representation that almost generalizes all distributed representations, posing the following challenges for the personalized individual semantics (PIS) issues in group decision-making (GDM) with FLEs. (1) The available measurement methods for FLEs are limited and suffer from some unreasonable or poorly discriminated deficiencies. (2) The existing research on FLEs has failed to fully utilize decision information incorporating subjective preferences and objective information, and the format of FLEs may be altered when optimizing PISs. To address these challenges, this paper focuses on the GDM problems under subjective preferences and objective information, both of which are characterized by FLEs, and introduces a novel FLE-based GDM method with PIS. Firstly, a new similarity measure for FLEs is proposed, considering both external and internal characteristics, namely semantics, elements, and symbolic proportions of linguistic term subsets. Secondly, by utilizing the similarity between the decision-maker's preference matrix and decision matrix, as well as the consistency of the preference matrix, a PIS optimization model is constructed to determine the personalized semantics of individual decision-makers. Subsequently, an optimization model is constructed, focused on maximizing the consensus level to determine the differentiated weights of decision-makers. Furthermore, individual evaluation information is aggregated into group evaluation information, a personalized semantic model is constructed to determine the personalized semantics of the group, and the selection process for alternatives is implemented. Finally, the effectiveness and advantages of our method are illustrated through its application in airline service quality assessment and by comparing it with alternative approaches.

Colloquialisation

Abstract Surveying a representative sample of studies of colloquialisation, a tendency for written norms to move closer to spoken usage, the chapter explores: the relationship between colloquialisation, operationalised in exclusively linguistic terms, and informalisation and democratisation, two processes primarily targeting wider sociocultural change, and complications arising when colloquialisation is extended beyond its original domain of application, standard written English of the ENL type. There are two major findings. Colloquialisation works less well in the study of ESL varieties than ENL ones. In addition, recent real-time analyses of change in spoken English suggest that the supposedly homogeneous baseline style of informal conversational English is more internally variable than is assumed in current work on colloquialisation.

Deploying the “Ordinary Wisdom” of Confucius: Khenpo Sodargye’s teaching on the Analects to Chinese practitioners

ABSTRACT Khenpo Sodargye is one of the key second-generation Tibetan Buddhist leaders at Larung Gar Buddhist Academy, who has been highly influential in transmitting the teachings of the Nyingma lineage to Chinese lay and monastic practitioners. Fundamental to this transmission is his ‘translation’ – in both linguistic and cultural terms – of the Tibetan tradition through the medium of both traditional and modern Chinese culture. Khenpo teaches Tibetan Buddhism to Chinese followers often using Chinese cultural terms and historiography, yet draws these into the Tibetan Buddhist, and specifically Nyingma lineage, normalising them with parallels already found in the Tibetan tradition. This cumulative ‘Eastern’ religiosity he sets up in oppositional terms to ‘Western’ modern influences which have led to a decline in values in modern China. One such example of using Chinese culture in this manner is his teaching on the Analects (Lunyu), which this paper seeks to explore.

F-KGQA: A fuzzy question answering system for knowledge graphs

The wide usage of large-scale knowledge graphs (KGs) motivates the development of user-friendly interfaces so that knowledge graphs become more readily accessible to a larger population. Natural language-based question answering (QA) systems are widely investigated and developed in the context of KGs, which can provide users with a natural means to retrieve the information they need from KGs without expecting them to know the query language. It is very common that natural language contains linguistic terms (fuzzy terms), and fuzzy (flexible) query has been widely investigated in the context of databases. This paper contributes a QA system with fuzzy terms over KGs called f-KGQA. f-KGQA can deal with different types of questions, including simple questions, complex questions, and questions with fuzzy terms. More importantly, users are provided with a channel to flexibly define their fuzzy terms based on their understanding. Our experimental results demonstrate the effectiveness and applicability of f-KGQA in handling questions with fuzzy terms.

Sequential three-way group decision-making for double hierarchy hesitant fuzzy linguistic term set

Group decision-making (GDM) characterized by complexity and uncertainty is an essential part of various life scenarios. Most existing researches lack tools to fuse information quickly and interpret decision results for partially formed decisions. This limitation is particularly noticeable when there is a need to improve the efficiency of GDM. To address this issue, a novel multi-level sequential three-way decision for group decision-making (S3W-GDM) method is constructed from the perspective of granular computing. This method simultaneously considers the vagueness, hesitation, and variation of GDM problems under double hierarchy hesitant fuzzy linguistic term sets (DHHFLTS) environment. First, for fusing information efficiently, a novel multi-level expert information fusion method is proposed, and the concepts of expert decision table and the extraction/aggregation of decision-leveled information based on the multi-level granularity are defined. Second, the neighborhood theory, outranking relation and regret theory (RT) are utilized to redesign the calculations of conditional probability and relative loss function. Then, the granular structure of DHHFLTS based on the sequential three-way decision (S3WD) is defined to improve the decision-making efficiency, and the decision-making strategy and interpretation of each decision-level are proposed. Furthermore, the algorithm of S3W-GDM is given. Finally, an illustrative example of diagnosis is presented, and the comparative and sensitivity analysis with other methods are performed to verify the efficiency and rationality of the proposed method.

TRANSLATION OF ENGLISH INDIAN ISLAMIC MARRIAGE CONTRACTS INTO ARABIC

The translation of Islamic marriage contracts from English into Arabic is an actual issue for an ordinary translator and even for a legal translator. Almost all translators in such a field of translation face the difficulty of grasping the straight and accurate equivalence in Arabic for specific linguistic terms. This problematic issue lies in the differences between the English legal system and the Arabic legal system. Another essential problem that legal translators usually face is the translating of items that are related directly to Islamic shariah and Islamic culture. The present research evaluates and inquiries about three translations for a sample of an English International Islamic marriage contract that is officially utilized by Muslims of India and translated by three MA Students who have master's degrees in translation. It is noteworthy to note that the assessment of these sample translations is defended on Peter Newmark's (1981) approach of Semantic and Communicative translation which is widely used in translating texts of languages from two different families such as English and Arabic. In closing, following the communicative procedure is the most equivalent option according to the context on one hand. On the other hand, the Semantic procedure is only acceptable when there is already a direct rendition for the items of ST into TT, So, Communicative is usually used in case of absence of equivalence. Or semantic procedure leads to translation non-identical from that of the source languages

Social network group decision-making method based on stochastic multi-criteria acceptability analysis for probabilistic linguistic term sets

In social network group decision-making (SNGDM) problems, decision-makers (DMs) often express their opinions or preferences using probabilistic linguistic term sets (PLTSs). In this paper, a novel SNGDM method for probabilistic linguistic information is proposed. Firstly, to obtain the prioritization of DMs in the clustering process, a DM clustering method for SNGDM is developed considering the influence of trust relationships and opinions similarity among DMs. Then, to satisfy the requirements of the consensus reaching process in SNGDM, a dynamic consensus threshold calculation method based on an optimization model is introduced. Furthermore, in the consensus measure stage, a novel consensus measure method for both DMs and subgroups is proposed, using a stochastic multi-criteria acceptability analysis (SMAA) method. Based on the consensus measure method, a novel SNGDM method based on SMAA for PLTSs is proposed. Finally, a case study of service quality evaluation in institutional pensions is used to illustrate the effectiveness of the proposed method. The results of case show that the proposed method can adjust consensus thresholds dynamically based on each round of collective opinions, and can solve the SNGDM problems when DMs can not provide their preferences for criteria weights.

Chinese Family Farm Business Risk Assessment Using a Hierarchical Hesitant Fuzzy Linguistic Model

Chinese family farms are continuously expanding; they are also facing various business risks that lead to a shorter lifespan. This paper constructed a family farm business risk assessment model that combined a hesitant fuzzy linguistic term sets (HFLTS) model with a hesitant fuzzy weighted average (HFWA) operator. On the basis of the factor analysis, this study built a family farm indicator system that included the natural, technical, market, policy, society, and management risk. The HFLTS was used for the assessment of weights in pairwise comparison matrices, and the HFWA operator was used as an aggregation operator to calculate the business risk score of family farms. For our case study, a method comparison analysis was also performed to check the validity of the results obtained by our risk assessment model.

SUBSTANTİVLƏŞMƏ MÜASİR AZƏRBAYCAN DİLİNDƏ AKTİV PROSES KİMİ

Substantivization as an Active Process in Modern Azerbaijani Summary This article delas with the study of substantivization, which is evaluated as a result of compression in the language. In the article, substantivization is considered as a method of forming a noun from other parts of speech. According to the author, “substance” is a generally accepted term in linguistics. Substance is one of the main ways of enriching the lexical layer of the language due to the possibilities of intralingual word formation. Reasoning, in a broader sense, is the formation of nouns by transitioning different parts of speech to them. Key words: substantivization, substantivaty, conversion, the process of word formation, functional aspect, morphological, syntactic

Fuzzy risk analysis in crop selection using information measures on quadripartitioned single-valued neutrosophic sets

Crop selection is a critical task that involves assessing multiple risk factors to achieve maximum yield. Therefore, risk assessment plays a pivotal role in choosing suitable crops for cultivation. Probabilistic and possibilistic methods are the two primary approaches used for the crop selection process. Probabilistic methods are cost-intensive due to data handling, while possibilistic methods, utilizing linguistic variables, are considered more reliable. In this article, we represent such linguistic variables using Quadripartitioned Single-Valued Neutrosophic Sets (QSVNSs), extensions of Single-Valued Neutrosophic Sets (SVNSs) characterized by four independent membership functions that enhance uncertainty accommodation. We propose two QSVNS-based information measures, entropy and similarity, to transform the final risks evaluated in the form of QSVNSs into linguistic variables for easier comprehension by the general audience. We apply this framework to mustard and paddy cultivation in Assam, a state located in northeastern India, conducting thorough analyses and validation tests. Additionally, statistical tests are presented to demonstrate the significance of the obtained results. The final risk of mustard cultivation is found to be ‘absolutely high’, as the largest similarity value of 0.9910 is obtained for the linguistic term ‘absolutely high’ among all computed similarity value results. Similarly, for paddy cultivation, the largest similarity value of 0.9159 is obtained for the linguistic term ‘very low’, indicating its final risk in our assumed scenario. Thus, the veracity and proficiency of our newly constructed measures are reflected in their practical applications.

An Integrated CREAM for Human Reliability Analysis Based on Consensus Reaching Process under Probabilistic Linguistic Environment

Human reliability analysis (HRA) is widely used to evaluate the impact of human errors on various complex human–machine systems for enhancing their safety and reliability. Nevertheless, it is hard to estimate the human error probability (HEP) in reality due to the uncertainty of state assessment information and the complex relations among common performance conditions (CPCs). In this paper, we aim to present a new integrated cognitive reliability and error analysis method (CREAM) to solve the HRA problems under probabilistic linguistic environment. First, the probabilistic linguistic term sets (PLTSs) are utilized to handle the uncertain task state assessments provided by experts. Second, the minimum conflict consensus model (MCCM) is employed to deal with conflict task state assessment information to assist experts reach consensus. Third, the entropy weighting method is used to determine the relative objective weights of CPCs. Additionally, the CPC effect indexes are introduced to assess the overall effect of CPCs on performance reliability and obtain the HEP estimation. Finally, the reliability of the proposed CREAM is demonstrated via a healthcare practical case. The result shows that the new integrated CREAM can not only effectively represent experts’ uncertain task state assessments but also determine more reliable HEP estimation in HRA.