Supporting Complex Business Decisions with a Fuzzy Mobile Assistant

Researchers have recognized the importance of semantic expressiveness in understanding and solving complex problems and have identified a need to incorporate reasoning about uncertainty into decision tools that assist business managers. This study extends current approaches and develops new tools to allow artificial mobile assistants to manage rule-driven consultations by capturing and recommending problem solutions through natural language interfaces. A prototype assistant is described to support fuzzy knowledge representations and fuzzy rule-based consultations. The prototype’s application is implemented in a Windows 8 mobile device and applied in a case study of business outsourcing decisions

Ontological approach to development of computing with words based systems

AbstractComputing with words introduced by Zadeh becomes a very important concept in processing of knowledge represented in the form of propositions. Two aspects of this concept – approximation and personalization – are essential to the process of building intelligent systems for human-centric computing.For the last several years, Artificial Intelligence community has used ontology as a means for representing knowledge. Recently, the development of a new Internet paradigm – the Semantic Web – has led to introduction of another form of ontology. It allows for defining concepts, identifying relationships among these concepts, and representing concrete information. In other words, an ontology has become a very powerful way of representing not only information but also its semantics.The paper proposes an application of ontology, in the sense of the Semantic Web, for development of computing with words based systems capable of performing operations on propositions including their semantics. The ontology-based approach is very flexible and provides a rich environment for expressing different types of information including perceptions. It also provides a simple way of personalization of propositions. An architecture of computing with words based system is proposed. A prototype of such a system is described

Personalized individual semantics in Computing with Words for supporting linguistic Group Decision Making. An Application on Consensus reaching

Yucheng Dong would like to acknowledge the financial support of grants (Nos. 71171160, 71571124) from NSF of China, and a grant (No.xq15b01) from SSEM key research center at Sichuan province. Enrique Herrera-Viedma and Luis Mart´ınez would like to acknowledge the FEDER funds under Grant TIN2013-40658-P and TIN2015-66524-P respectivelyIn group decision making (GDM) dealing with Computing with Words (CW) has been highlighted the importance of the statement, words mean different things for different people, because of its influence in the final decision. Different proposals that either grouping such different meanings (uncertainty) to provide one representation for all people or use multi-granular linguistic term sets with the semantics of each granularity, have been developed and applied in the specialized literature. Despite these models are quite useful they do not model individually yet the different meanings of each person when he/she elicits linguistic information. Hence, in this paper a personalized individual semantics (PIS) model is proposed to personalize individual semantics by means of an interval numerical scale and the 2-tuple linguistic model. Specifically, a consistency-driven optimization-based model to obtain and represent the PIS is introduced. A new CW framework based on the 2-tuple linguistic model is then defined, such a CW framework allows us to deal with PIS to facilitate CW keeping the idea that words mean different things to different people. In order to justify the feasibility and validity of the PIS model, it is applied to solve linguistic GDM problems with a consensus reaching process.National Natural Science Foundation of China 71171160 71571124Sichuan University skqy201606European Union (EU) TIN2013-40658-P TIN2015-66524-

Induced hesitant 2-tuple linguistic aggregation operators with application in group decision making

In this article, hesitant 2-tuple linguistic arguments are used to evaluate the group decision making problems which have inter dependent or inter active attributes. Operational laws are developed for hesitant 2-tuple linguistic elements and based on these operational laws hesitant 2- tuple weighted averaging operator and generalized hesitant 2- tuple averaging operator are proposed. Combining Choquet integral with hesitant 2-tuple linguistic information, some new aggregation operators are defined, including the hesitant 2-tuple correlated averaging operator, the hesitant 2-tuple correlated geometric operator and the generalized hesitant 2-tuple correlated averaging operator. These proposed operators successfully manage the correlations among the elements. After investigating the properties of these operators, a multiple attribute decision making method based on these operators, is suggested. Finally, an example is given to illustrate the practicality and feasibility of proposed method

Retraction and Generalized Extension of Computing with Words

Fuzzy automata, whose input alphabet is a set of numbers or symbols, are a formal model of computing with values. Motivated by Zadeh's paradigm of computing with words rather than numbers, Ying proposed a kind of fuzzy automata, whose input alphabet consists of all fuzzy subsets of a set of symbols, as a formal model of computing with all words. In this paper, we introduce a somewhat general formal model of computing with (some special) words. The new features of the model are that the input alphabet only comprises some (not necessarily all) fuzzy subsets of a set of symbols and the fuzzy transition function can be specified arbitrarily. By employing the methodology of fuzzy control, we establish a retraction principle from computing with words to computing with values for handling crisp inputs and a generalized extension principle from computing with words to computing with all words for handling fuzzy inputs. These principles show that computing with values and computing with all words can be respectively implemented by computing with words. Some algebraic properties of retractions and generalized extensions are addressed as well.Comment: 13 double column pages; 3 figures; to be published in the IEEE Transactions on Fuzzy System

An Integrative Decision-Making Mechanism for Consumers’ Brand Selection using 2-Tuple Fuzzy Linguistic Perceptions and Decision Heuristics

Consumers perform decision-making (DM) processes to select their preferred brands during their entire consumer journeys. These DM processes are based on the multiple perceptions they have about the products available in the market they are aware of. These consumers usually perform different DM strategies and employ diverse heuristics depending on the nature of the purchase, ranging from more pure optimal choices to faster decisions. Therefore, the design of realistic DM approaches for modeling these consumer behaviors requires a good representation of consumer perceptions and a reliable process for integrating their corresponding heuristics. In this work, we use fuzzy linguistic information to represent consumer perceptions and propose four consumer DM heuristics to model the qualitative linguistic information for the consumer buying decision. In particular, we use 2-tuple fuzzy linguistic variables, which is a substantially more natural and realistic representation without falling in a loss of information. The set of selected heuristics differ in the degree of involvement the consumers give to their decisions. Additionally, we propose a heuristic selection mechanism to integrate the four heuristics in a single DM procedure by using a regulation parameter. Our experimental analysis shows that the combination of these heuristics in a portfolio manner improves the performance of our model with a realistic representation of consumer perceptions. The model’s outcome matches the expected behavior of the consumers in several real market scenarios

Violette Leduc in translation : between censure, recognition and emancipation

Les livres de l’écrivaine française Violette Leduc, publiés entre 1946 et 1973, sont de premiers exemples d’écriture féministe autobiographique abordant des questions telles que la santé mentale, la maternité imparfaite et la sexualité d’un point de vue féminin. En raison de la nature controversée de son travail, elle a été censurée à plusieurs reprises tout au long du processus de publication en France — pendant la production initiale du manuscrit sous la forme d’autocensure, par le mentorat de Simone de Beauvoir, par les éditeurs de Gallimard et par la presse. Après avoir remporté un succès critique malgré la résistance à son travail, ses livres ont été traduits dans de nombreuses langues, y compris l’anglais. Bien que la censure de Leduc ait été documentée et explorée depuis diverses perspectives, la traduction de son écriture et de sa diffusion hors de la France est à peine mentionnée. Cette étude aborde donc la question de comment la traduction, en particulier la traduction anglaise, comme agent de publication des écrits de Leduc, répond à la censure précédente de son écriture — amplifie-t-elle ou atténue-t-elle la répression, aide-t-elle à réprimer ou à émanciper les représentations minoritaires? Pour explorer ces questions, nous présentons le cas des 200 pages d’écriture les plus controversées de Leduc — un passage retiré de sa place d’origine au début d’un autre livre pour devenir le texte autonome de Thérèse et Isabelle. Ce livre, qui retrace la brève relation amoureuse entre deux étudiantes pensionnaires, a été ouvertement censuré en français. Il fut traduit en anglais en 1967 et, contrairement aux autres livres de Leduc, fut réédité sous sa forme non expurgée en 2000 et fut retraduit en 2012. Ces deux traductions sont ici considérées comme continuation du plus large processus de production réception, de l’écriture initiale à la réception critique continue. Ce faisant, les théories traductionnelles de la censure et des études queer et féministes fournissent une perspective critique permettant de comprendre la signification contextuelle et historique du texte, tandis que la théorie traduction-spécifique de la complexité sert de cadre analytique pour une compréhension nuancée des sources d’influence et d’émergence interdépendantes. De cette perspective complexe, sont identifiés des modèles qui mettent en évidence le rôle de la traduction en tant qu’agent de censure et/ou d’émancipation, et leurs effets sur la compréhension contemporaine de l’héritage de Leduc.French writer Violette Leduc’s books, published between 1946 and 1973, are some of the earliest examples of autobiographical feminist writing addressing issues such as mental health, unideal motherhood and sexuality from a female perspective. Due to the controversial nature of her work, she was repeatedly censored throughout the publication process in France – from the initial manuscript production in the form of self-censorship, through her relationship with Simone de Beauvoir, by the editors at Gallimard and, ultimately, by the press. After finding critical success despite the resistance to her work, her books were translated into many languages, including English. Although Leduc’s censorship has been documented and discussed from a range of perspectives, the translation of her writing and its circulation outside of France is barely mentioned. This study therefore addresses the question of how translation, specifically the English translation, as another gatekeeper in Leduc’s publication process, responds to the previous censorship of her writing – does it magnify or attenuate repression, does it help emancipate or repress minority representations? To explore these questions, we present the case of Leduc’s most controversial 200 pages of writing – a passage removed from its original place at the beginning of another book to become the standalone Thérèse et Isabelle. This text, which recounts the brief romantic relationship between two female boarding school students, was overtly censored in French. It was translated into English in 1967 and, unlike Leduc’s other books, was rereleased in its unexpurgated form in 2000 and was retranslated in 2012. For the purposes of this analysis, these two translations are considered within the wider production process, from initial writing to ongoing critical reception. In so doing, translational theories of censorship and queer and feminist studies provide a critical lens through which to understand contextual and historical significance, while translation-specific discussions of complexity theory are applied as an analytical framework through which to populate a nuanced understanding of inter-related sources of influence and emergence. From this complex perspective, patterns are identified that highlight the role of translation as an agent of censorship and/or emancipation, significantly influencing the contemporary understanding of Leduc’s legacy

CRITICAL ANALYSES OF NATURAL LANGUAGE PROCESSING (NLP) IN UNDERSTANDING SEMANTICS

Today, language understanding systems do quite many useful things with processing natural language, even they are able to process the data much faster than humans are. Nevertheless, they do not have the same logical understanding of natural language yet as humans have and the interpretation capabilities of a language understanding system depending on the semantic theory is not sufficient in all aspects. The research is centered on some of the important issues that arise using it in natural language processing.Today, language understanding systems do quite many useful things with processing natural language, even they are able to process the data much faster than humans are. Nevertheless, they do not have the same logical understanding of natural language yet as humans have and the interpretation capabilities of a language understanding system depending on the semantic theory is not sufficient in all aspects. The research is centered on some of the important issues that arise using it in natural language processing