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The main stream of Linguistic Data Summarization involves modeling numerical attributes using linguistic variables, which makes it difficult addressing real-world problems with qualitative or mixed data. Literature highlights challenges such as the limited expressiveness of summaries from classical protoforms, the need to explore relationships between them to find more useful patterns and refining language to improve their interpretability and usefulness. The latter is increasingly significant as the demand for explainability grows with the rise of black-box AI applications. This paper proposes SUMMARIA, a XAI support methodology by generating composite (enriched) linguistic summaries of qualitative data. A framework is formalized integrating Linguistic Data Summarization with the concept of rhetorical relation and defining the structure and quality metrics of a composite linguistic summary. Three abstract forms of composite linguistic summaries representing Evidence, Contrast and Emphasis relations are specified, inspired by Rhetorical Structure Theory. Also, a method based on Association Rules Mining, implements SUMMARIA in problem-solving via five algorithms. An empirical study tested SUMMARIA’s application on two judicial datasets and a substantially different behavior was found for four different scenarios, which reveals its sensitivity to the nature and distribution of the primary data. A human-expert validation was performed showing that the linguistic summaries are understandable and the relation type implicit in them is recognizable by the users.

In this paper I present a framework for the conceptualization of languages based on the prototype theory of categorization proposed by Eleanor Rosch and her colleagues for natural semantic categories. It is motivated by research in the Casamance region of southern Senegal, where a high level of multilingualism in non-standardized varieties is the norm, making accurate description of languages, and thus analysis of multilingual discourse, problematic. I show that languages in this context can be conceived of as categories, of which linguistic features may be more or less prototypical members. Such an approach can form the basis for a more robust method of language description, integrating rich sociolinguistic data, and facilitating more nuanced analysis of multilingual discourse data.

The identification and apprehending of suspects by law enforcement authorities rely heavily on facial sketches. The sketch artist creates sketches based on the witnesses’ memories. Sketch artists are few and limited in their availability. It is also evident that as time passes, the eyewitness forgets many of the important details, which can be expensive in time-sensitive investigations. The sketch was used to obtain the suspect’s image through the state-of-the-art sketch-photo retrieval model, which missed the relevance of time sensitivity. A linguistic description-based suspect face image retrieval approach is presented in this study. In the proposed approach, the facial attribute-value pair is extracted from eyewitness descriptions. Facial attribute saliency is also studied in this work and validated with the Fuzzy Analytic Hierarchy Process (FAHP) model. A weighted score is computed to retrieve the suspect face images. The effectiveness of the proposed method is assessed by comparing it to existing linguistic sketch-based retrieval methods as well as the sketch to photo retrieval models. As compared to state-of-the-art approaches, experimental results give an accuracy of 94.98%.

In this study, we develop a process of estimation of importance of features considered in face recognition by making use of the analytic hierarchy process (AHP). The AHP method of pairwise comparisons realized at three levels of hierarchy becomes crucial to realize a comprehensive weighting of cues so that sound estimates of weights associated with the individual features of faces can be formed. We demonstrate how to carry out an efficient process of face description by using a collection of linguistic descriptors of the features and their groups. Numerical dependencies between the features are quantified with the help of experienced criminology and psychology experts. Finally, we present an entropy-based method of evaluation of the relevance of the estimation process completed by the individuals. The intuitively appealing results of experiments are presented and analyzed in detail.

The increased demand of systems able to generate reports in natural language from numerical data involves the search for new solutions. This paper presents an adaptation of standard natural language generation methodologies to generate customized linguistic descriptions of data. Namely, we merge one of the most well-known architectures in the natural language generation research field together with our previous architecture for generating linguistic descriptions of complex phenomena. The latter is supported by the computational theory of perceptions which comes from the fuzzy sets and systems research field. We include a practical case of use dealing with the problem of inefficient consumption of energy at households. It generates natural language recommendations adapted to each household to promote a more responsible consumption. The proposal reveals opportunities of collaboration between the different research communities that are involved.

In 1890, the Maldivian judge and poet Sheikh Muhammad Jamaluddin connected poetry with linguistic description in two ways. First, when he described features of the Dhivehi language with the aid of Arabic linguistic theory, he used Dhivehi poetry as linguistic evidence for correct usage. Second, he authored Dhivehi-language poetry about Arabic linguistic theory. Cosmopolis scholarship relates a narrative of how the wide circulation of Sanskrit, Arabic, and/or Persian fostered a vast network of writers who authored texts in major vernacular languages like Bengali, Burmese, Javanese, Kannada, Khmer, Malay, Sinhala, Tamil, Telugu, Thai, Tibetan, Turkish, and Urdu. This scholarship suggests that authors living within a particular cosmopolis wrote in divergent vernacular languages yet were, in some sense, connected because they translated and responded creatively to the same widely circulated source texts written in Sanskrit, Arabic, and/or Persian. Yet in cosmopolis scholarship's effort to reveal understudied connections, various degrees of disconnection among writers of vernacular languages within a cosmopolis tend to be missed. One problem of overlooking disconnection among writers of vernacular languages is that readers could mistakenly conflate superculture-subculture interaction with intercultural interaction. In this article, I argue that Dhivehi-language poetry and linguistic description was inside the Arabic cosmopolis but simultaneously outside, because in circa 1890 non-Maldivians in the Arabic cosmopolis of South and Southeast Asia could not even read the Thaana script of the Dhivehi language.

In this article, we present a new machine learning model by imitation based on the linguistic description of complex phenomena. The idea consists of, first, capturing the behaviour of human players by creating a computational perception network based on the execution traces of the games and, second, representing it using fuzzy logic (linguistic variables and if-then rules). From this knowledge, a set of data (dataset) is automatically created to generate a learning model based on decision trees. This model will be used later to automatically control the movements of a bot. The result is an artificial agent that mimics the human player. We have implemented, tested and evaluated this technology from two different points of view: performance by using classical metrics (accuracy, ROC area and PRC area) and believability by using a Turing test for trained bots. The results obtained are interesting and promising, showing that this method can be a good alternative to design and implement the behaviour of intelligent agents in video game development.

In this paper, we present a novel approach to task planning based on an intelligent expert system that makes it possible to obtain a conclusion based on linguistically characterized knowledge. The main goal of the proposed task planning system is to arrange and display tasks for the solver in an effective way. Therefore, the system shows the most important tasks first and then the less important ones (in a determined ordering). The solver has a list of tasks arranged according to their importance at each time the task list is displayed. Another goal of the system is to show the effectiveness of all subordinate workers (solvers) for the manager. The expert knowledge contained in the system is characterized by three linguistic descriptions: determination of the task importance, determination of the final task importance, and determination of the efficiency of the task solvers. The system shows the ordered task list in real time. Evaluation of the relative and final importance of the tasks is performed periodically. The system has been implemented as a WEB application and verified on real data set. We also present experimental results of our system.

The article is devoted to the study of feminist linguistic concepts in which attempts are made to re-think the category of divinity. We study gender-neutral (inclusive) versions of English translations of the Bible that depict God not as the Father but as Father and Mother in the heaven. We also investigate quotations from classical versions of the Bible that use the model of imagining God in female terms (e. g., a mother, a nurse, a woman giving birth). The purpose of the paper is to study of feminist preferences is linguistic techniques of the Bible translation into English; to find out to what extent the results of such technique implementations are adequate from the point of view of the classical linguistic-theological approach; to define the limits to which these results are valuable for the linguistic analysis of sacred texts. The research methodology includes a contextual analysis method, comparative, structural, comparative historical methods. For comparison with gender-neutral versions of the Bible, quotations from classical translations are studied: the original edition of the English King James’s Bible of 1611, the Elizabethan Russian Slavonic Bible of 1751, the Synodal Russian Bible of 1876 and the Hebrew Masoretic text of the Tanakh. It is shown that, from a linguistic view, God is beyond the gender field and is not traditionally described in the categories of male or female natural gender (sex). It is established that the comparison of God in the classical versions of the Bible with a woman, is no more than a conventional linguistic procedure that does not testify the essentialist feminist nature of the divine. It is concluded that despite high attractiveness and usefulness of feminist discourse in modern times, the academic Christian theology, history of confessions and religious linguistics cannot accept the idea of God as a Creature embodying the two polar gender principles (male and female). Similarly, gender-neutral English translations of the Bible should not be recognised nor accepted by the scientific and Church communities as an Anglican canon.

In this book, Scott Soames defends the revolution in philosophy led by Saul Kripke, Hilary Putnam, and David Kaplan against attack from those wishing to revive descriptivism in the philosophy of language, internalism in the philosophy of mind, and conceptualism in the foundations of modality. Soames explains how, in the last twenty-five years, this attack on the anti-descriptivist revolution has coalesced around a technical development called two-dimensional modal logic that seeks to reinterpret the Kripkean categories of the necessary aposteriori and the contingent apriori in ways that drain them of their far-reaching philosophical significance. Arguing against this reinterpretation, Soames shows how the descriptivist revival has been aided by puzzles and problems ushered in by the anti-descriptivist revolution, as well as by certain errors and missteps in the anti-descriptivist classics themselves.Reference and Descriptionsorts through all this, assesses and consolidates the genuine legacy of Kripke and Kaplan, and launches a thorough and devastating critique of the two-dimensionalist revival of descriptivism. Through it all, Soames attempts to provide the outlines of a lasting, nondescriptivist perspective on meaning, and a nonconceptualist understanding of modality.