Language Statements Research Articles

Building Motivation in African American Caregivers of Adolescents With Obesity: Application of Sequential Analysis.

We sought to examine communication between counselors and caregivers of adolescents with obesity to determine what types of counselor behaviors increased caregivers' motivational statements regarding supporting their child's weight loss. We coded 20-min Motivational Interviewing sessions with 37 caregivers of African American 12-16-year-olds using the Minority Youth Sequential Coding for Observing Process Exchanges. We used sequential analysis to determine which counselor communication codes predicted caregiver motivational statements. Counselors' questions to elicit motivational statements and emphasis on autonomy increased the likelihood of both caregiver change talk and commitment language statements. Counselors' reflections of change talk predicted further change talk, and reflections of commitment language predicted more commitment language. When working to increase motivation among caregivers of adolescents with overweight or obesity, providers should strive to reflect motivational statements, ask questions to elicit motivational statements, and emphasize caregivers' autonomy.

How might language affect critical thinking performance?

This study examined whether language structure or language proficiency might affect students’ critical thinking performance. Previous research has claimed that many non-Western students struggle with the demands of demonstrating critical thought. Two language-related causes have been suggested: one concerning structural limitations in the non-Western students’ first language, and the other concerning their second language proficiency. In Study 1 described here, reports written by 110 Japanese second year university students, who had received instruction in academic discourse for critical evaluation (which is one aspect of critical thinking), were analyzed for use of evaluative statements. No disadvantage was found for use of the Japanese language, which is considered as having a more indirect structure that may make critical evaluation more difficult. Measurements of language proficiency in English and Japanese, however, were found to correlate with production of evaluative statements in those respective languages suggesting that language proficiency could affect critical evaluation use. In Study 2, the same task was given to 43 first year students who had not yet received the same instruction. Analysis revealed similar patterns in their written work but at a lower level, suggesting that the second year students had benefitted from the skills instruction. Furthermore, unlike the second year students, the first year students evidenced no correlations between their language proficiency scores and their production of evaluative statements, suggesting that proficiency on its own is inadequate: students need instruction on the specific language forms and structures to use to demonstrate critical thinking in their written work.

The bilingual brain turns a blind eye to negative statements in the second language.

Neurobilingualism research has failed to reveal significant language differences in the processing of affective content. However, the evidence to date derives mostly from studies in which affective stimuli are presented out of context, which is unnatural and fails to capture the complexity of everyday sentence-based communication. Here we investigated semantic integration of affectively salient stimuli in sentential context in the first- and second-language (L2) of late fluent Polish–English bilinguals living in the UK. The 19 participants indicated whether Polish and English sentences ending with a semantically and affectively congruent or incongruent adjective of controlled affective valence made sense while undergoing behavioral and electrophysiological recordings. We focused on the N400, a wave of event-related potentials known to index semantic integration. We expected N400 amplitude to index increased processing demands in L2 English comprehension and potential language–valence interactions to reveal differences in affective processing between languages. Contrary to our initial expectation, we found increased N400 for sentences in L1 Polish, possibly driven by greater affective salience of sentences in the native language. Critically, language interacted with affective valence, such that N400 amplitudes were reduced for English sentences ending in a negative fashion as compared to all other conditions. We interpreted this as a sign that bilinguals suppress L2 content embedded in naturalistic L2 sentences when it has negative valence, thus extending the findings of previous research on single words in clinical and linguistic research.

Coreference resolution improves extraction of Biological Expression Language statements from texts.

We describe a system that automatically extracts biological events from biomedical journal articles, and translates those events into Biological Expression Language (BEL) statements. The system incorporates existing text mining components for coreference resolution, biological event extraction and a previously formally untested strategy for BEL statement generation. Although addressing the BEL track (Track 4) at BioCreative V (2015), we also investigate how incorporating coreference resolution might impact event extraction in the biomedical domain. In this paper, we report that our system achieved the best performance of 20.2 and 35.2 in F-score for the full BEL statement level on both stage 1, and stage 2 using provided gold standard entities, respectively. We also report that our results evaluated on the training dataset show benefit from integrating coreference resolution with event extraction.

Fuzzy logic‐based linguistic summaries of time series: a powerful tool for discovering knowledge on time varying processes and systems under imprecision

We present a novel approach to linguistic data summarization for numeric data, i.e., of the numbers to text type. Linguistic summarization is meant as a process of a comprehensive description of big and complex datasets via short statements in natural language. First, we briefly survey main developments in the traditional, well developed, and powerful approach to linguistic data summarization based on tools and techniques of natural language generation (NLG), notably due to Reiter and his collaborators. We indicate that this approach has a serious limitation on the representation and processing of imprecision that is characteristic for natural languages. We show that a fuzzy logic‐based approach to linguistic data summarization can be a simple yet efficient solution in this respect. We present the linguistic summaries represented by protoforms in the form of linguistically quantified propositions dealt with using tools and techniques of fuzzy logic to grasp an inherent imprecision of natural language. Such linguistic data summaries can provide a human user, whose only natural means of articulation and communication is natural language, with a simple yet effective and efficient means for the representation and manipulation of knowledge about processes and systems. We concentrate on the linguistic summarization of dynamic processes and systems, dealing with data represented as time series. We extend the basic, static data‐oriented concept of a linguistic data summary to the case of time series data, present various possible protoforms of linguistic summaries, and an analysis of their properties and ways of generation. We show two our own real applications of the new tools of linguistic summarization of time series, for the summarization of quotations of an investment (mutual) fund, and of Web server logs, to show the power of the tool. We also mention some other applications known from the literature. We conclude with some remarks on the strength of the linguistic summarization for broadly perceived data mining and knowledge discovery and some possible further research directions. WIREs Data Mining Knowl Discov 2016, 6:37–46. doi: 10.1002/widm.1175This article is categorized under: Fundamental Concepts of Data and Knowledge > Human Centricity and User Interaction Technologies > Computational Intelligence Technologies > Machine Learning

APPLICABILITY AND USABILITY OF PREDEFINED NATURAL LANGUAGE BOILERPLATES IN DOCUMENTING REQUIREMENTS

Natural language is frequently applied to document the stakeholders’ statements during requirement elicitation activities. Nevertheless, the use of generic natural language has potential for the issues of unclear and inconsistent requirements. These issues may result from the diverse interpretations by the stakeholders or other various sources of documents and artefacts. The main objective of this paper was to discuss the definition and application of predefined boilerplates to specify the requirements in the form of natural language statements. The proposed boilerplates were defined and classified based on two main types of requirements, namely functional and non-functional (performance, constraints, and specific quality). Two methods have been applied to evaluate the research results; the applicability of the predefined boilerplates was demonstrated using two different case studies, and the usability aspect is evaluated through synthetic environment experimentation using human respondents. As a summary, the predefined boilerplates were found helpful, especially among novice requirement engineers to express and specify their requirements in a consistent manner and a standardized way, relatively able to improve the quality of the natural language statements.

A Natural Language Query Builder Interface for Structured Databases Using Dependency Parsing

A natural language query builder interface retrieves the required data in structured form from database when query is entered in natural language. The user need not necessarily have sufficient technical knowledge of structured query language statements so nontechnical users can also use this proposed model. In natural language parsing, getting highly accurate syntactic analysis is a crucial step. Parsing of natural languages is the process of mapping an input string or a natural language sentence to its syntactic representation. Constituency parsing approach takes more time for parsing. So, natural language query builder interface is developed in which the parsing of natural language sentence is done by using dependency parsing approach. Dependency parsing technique is widespread in natural language domain because of its state-of-art accuracy and efficiency and also it performs best. In this paper, the buffering scheme is also proposed for natural language statements which will not load the whole sentence if it was done previously. Also there was a need of generalized access to all tables from database which is handled in this system.

On the relation between fuzzy and generalized quantifiers

Fuzzy quantified sentences have been widely applied for modeling statements in Natural Language since they allow to represent a broad type of intrinsically imprecise quantified statements that are usually linguistically expressed. Two different frameworks arise in order to model this imprecision in quantification: Zadeh's fuzzy quantifiers and the fuzzification of generalized quantification. For both models several approaches have been developed for assessing the degree of satisfiability of fuzzy quantified sentences. We present and compare both models, concluding that although the concept of quantifier in each model has not the same semantics, we can establish a connection between them and between the evaluation methods in both theories.

Diagnosing behavioral differences between business process models: An approach based on event structures

Companies operating in multiple markets or segments often need to manage multiple variants of the same business process. Such multiplicity may stem for example from distinct products, different types of customers or regulatory differences across countries in which the companies operate. During the management of these processes, analysts need to compare models of multiple process variants in order to identify opportunities for standardization or to understand performance differences across variants. To support this comparison, this paper proposes a technique for diagnosing behavioral differences between process models. Given two process models, it determines if they are behaviorally equivalent, and if not, it describes their differences in terms of behavioral relations – like causal dependencies or conflicts – that hold in one model but not in the other. The technique is based on a translation from process models to event structures, a formalism that describes the behavior as a collection of events (task instances) connected by binary behavioral relations. A naïve version of this translation suffers from two limitations. First, it produces redundant difference statements because an event structure describing a process may contain unnecessary event duplications. Second, this translation is not directly applicable to process models with cycles as the corresponding event structure is infinite. To tackle the first issue, the paper proposes a technique for reducing the number of events in an event structure while preserving the behavior. For the second issue, relying on the theory of complete unfolding prefixes, the paper shows how to construct a finite prefix of the unfolding of a possibly cyclic process model where all possible causes of every activity is represented. Additionally, activities that can occur multiple times in an execution of the process are distinguished from those that can occur at most once. The finite prefix thus enables the diagnosis of behavioral differences in terms of activity repetition and causal relations that hold in one model but not in the other. The method is implemented as a prototype that takes as input process models in the Business Process Model and Notation (BPMN) and produces difference statements in natural language. Differences can also be graphically overlaid on the process models.

Determinants and Valuation Implications of Compulsory Stock Option Disclosures in a Weak Regulatory Setting—The Case of France

AbstractUsing a sample of listed French firms in 2005, the year of mandatory IFRS adoption in the European Union (EU), we investigate the determinants of disclosure compliance of stock option expenses under IFRS 2, Share‐based Payment. Stock options are a popular means of executive compensation in France relative to other EU countries. Prior to 2005, French accounting standards and corporate governance regulations did not require recognition of option expense amounts and required minimal supplementary disclosures. There was also a perception that enforcement was imperfect, in particular with respect to IFRS 2. Given this setting, we explore what factors influence the willingness of firms to follow compulsory IFRS requirements in a weak regulatory setting. We find that overall compliance with IFRS 2 disclosure requirements increases with U.S. and U.K. institutional ownership, U.S. cross‐listing, provision of English language statements, and decreases with CEO and family ownership of the firm. We also investigate how stock market prices are affected by the recognition and disclosure of stock option expenses according to IFRS 2 in this regulatory setting and find that investors value option expenses positively, particularly when accompanied by high‐disclosure compliance. Our findings have implications for other jurisdictions in the process of adopting or converging to IFRS.

Resolving Ambiguities in Natural Language Software Requirements

Requirements Engineering is one of the most vital activities in the entire Software Development Life Cycle. The success of the software is largely dependent on how well the users' requirements have been understood and converted into appropriate functionalities in the software. Typically, the users convey their requirements in natural language statements that initially appear easy to state. However, being stated in natural language, the statement of requirements often tends to suffer from misinterpretations and imprecise inferences. As a result, the requirements specified thus, may lead to ambiguities in the software specifications. One can indeed find numerous approaches that deal with ensuring precise requirement specifications. Naturally, an obvious approach to deal with ambiguities in natural language software specifications is to eliminate ambiguities altogether i.e. to use formal specifications. However, the formal methods have been observed to be cost-effective largely for the development of mission-critical software. Due to the technical sophistication required, these are yet to be accepted in the mainstream. Hence, the other alternative is to let the ambiguities exist in the natural language requirements but deal with the same using proven techniques viz. using approaches based on machine learning, knowledge and ontology to resolve them. One can indeed find numerous automated and semi-automated tools to resolve specific types of natural language software requirement ambiguities. However, to the best of our knowledge there is no published literature that attempts to compare and contrast the prevalent approaches to deal with ambiguities in natural language software requirements. Hence, in this paper, we attempt to survey and analyze the prevalent approaches that attempt to resolve ambiguities in natural language software requirements. We focus on presenting a state-of-the-art survey of the currently available tools for ambiguity resolution. The objective of this paper is to disseminate, dissect and analyze the research work published in the area, identify metrics for a comparative evaluation and eventually do the same. At the end, we identify open research issues with an aim to spark new interests and developments in this field.

The Amalgamation of NLP with TextCategorization

Text Mining (TM) and Natural Language Processing (NLP) are very closely related to each other. Though TM is not really associated with the semantic and the syntax of a language, it does try to link documents or unstructured data in such a way that at the end of the day we can say those documents are semantically closely associated. TM has a number of subtasks like Text Clustering, Text Summarizing, Text Categorizing, etc. In this paper we are discussing research related to converting a simple English language question to its equivalent Structured Query Language (SQL) statement for a novice to fetch information from a database. This tool that we have developed has been named the N-ELIDB – Natural English Language Query Interface to Database. This is a heuristic tool which after generating the SQL, tries to categorize the questions using the concept of Text Categorization. The previous part is for a normal user and the later part is for the Text Miner.

Ontology-Based Interpretation of Natural Language Philipp Cimiano, Christina Unger, and John McCrae (University of Arminia Bielefeld, Germany) Morgan & Claypool, Synthesis Lectures on Human Language Technologies, March 2014, 178 pages, (doi:10.2200/S00561ED1V01Y201401HLT024) , $45.00

<b>Ontology-Based Interpretation of Natural Language</b> <b>Philipp Cimiano, Christina Unger, and John McCrae</b> (University of Arminia Bielefeld, Germany) Morgan &amp; Claypool, Synthesis Lectures on Human Language Technologies, March 2014, 178 pages, (doi:10.2200/S00561ED1V01Y201401HLT024) , $45.00

Perceived Communicative Context and Emotional Content Amplify Visual Word Processing in the Fusiform Gyrus

The personal significance of a language statement depends on its communicative context. However, this is rarely taken into account in neuroscience studies. Here, we investigate how the implied source of single word statements alters their cortical processing. Participants' brain event-related potentials were recorded in response to identical word streams consisting of positive, negative, and neutral trait adjectives stated to either represent personal trait feedback from a human or to be randomly generated by a computer. Results showed a strong impact of perceived sender. Regardless of content, the notion of receiving feedback from a human enhanced all components, starting with the P2 and encompassing early posterior negativity (EPN), P3, and the late positive potential (LPP). Moreover, negative feedback by the "human sender" elicited a larger EPN, whereas positive feedback generally induced a larger LPP. Source estimations revealed differences between "senders" in visual areas, particularly the bilateral fusiform gyri. Likewise, emotional content enhanced activity in these areas. These results specify how even implied sender identity changes the processing of single words in seemingly realistic communicative settings, amplifying their processing in the visual brain. This suggests that the concept of motivated attention extends from stimulus significance to simultaneous appraisal of contextual relevance. Finally, consistent with distinct stages of emotional processing, at least in contexts perceived as social, humans are initially alerted to negative content, but later process what is perceived as positive feedback more intensely.

A new self-report inventory of dyslexia for students: criterion and construct validity.

The validity of a Dutch self-report inventory of dyslexia was ascertained in two samples of students. Six biographical questions, 20 general language statements and 56 specific language statements were based on dyslexia as a multi-dimensional deficit. Dyslexia and non-dyslexia were assessed with two criteria: identification with test results (Sample 1) and classification using biographical information (both samples). Using discriminant analyses, these criteria were predicted with various groups of statements. All together, 11 discriminant functions were used to estimate classification accuracy of the inventory. In Sample 1, 15 statements predicted the test criterion with classification accuracy of 98%, and 18 statements predicted the biographical criterion with classification accuracy of 97%. In Sample 2, 16 statements predicted the biographical criterion with classification accuracy of 94%. Estimations of positive and negative predictive value were 89% and 99%. Items of various discriminant functions were factor analysed to find characteristic difficulties of students with dyslexia, resulting in a five-factor structure in Sample 1 and a four-factor structure in Sample 2. Answer bias was investigated with measures of internal consistency reliability. Less than 20 self-report items are sufficient to accurately classify students with and without dyslexia. This supports the usefulness of self-assessment of dyslexia as a valid alternative to diagnostic test batteries.

Leitura de imagens fotográficas orientadas para a representação documental

As imagens são uma parte essencial da cultura visual contemporânea. O modo de significado deles é muito diferente do das declarações lingüísticas, por isso é difícil verbalizar o significado deles. O artigo analisa os diferentes referenciais teóricos que consideram as imagens fotográficas como objeto de estudo científico. Ele se concentra especificamente nos processos de leitura de fotografias, que dão origem à análise de conteúdo. Ele propõe um modelo para leitura de imagens fotográficas orientadas para a representação documental e recuperação de informações. As habilidades necessárias, os fatores envolvidos e as operações semânticas que são realizadas durante a leitura das fotografias são determinadas. O modelo estabelecido é aplicado à leitura documental da foto de Robert Doisneau Le Baiser do Hotel de Ville (1950).

La lectura de las imágenes fotográficas orientada hacia la representación documental

The images are an essential part of contemporary visual culture. His way of signifying is very different from the language statements, so it is difficult to verbalize their meaning. The article analyzes the different theoretical frameworks that the photographic images consider as an object of scientific study. It focuses specifically on the process of reading the photographs, which give rise to content analysis. It proposes a model of reading-oriented photographic images documentary representation and retrieval of information. The necessary skills are identified, the factors involved and semantic operations carried out during the reading of the photographs. The established model is applied to the reading of documentary photography Robert Doisneau Le baiser de l'Hôtel de Ville (1950).

Проблемы понимания текстовой и символьной информации при обучении математике

We posed the problem of understanding the text and symbol messages by students. We considered the interpretation of the concept of "understanding" in philosophy and psychology, presented psycholinguistic aspect of the concept in detail. We proposed a general classification of problems of perception of speech by students in teaching mathematics. We identified two broad categories of problems of understanding the language statements (direct problematic language codes perception and incorrect perception of the context). We introduce the concept of "reversible language constructs”, discuss the various types of reversible language constructs found in educational materials on math. The analogy is provided to demonstrate the similarity of reversible structures of natural language with constructs of algebraic material. The author presents the classification of reversible constructs. We substantiated the importance of the study of reversible structures decoding by students, identified properties of reversible constructs perception, the conditions for their understanding. We revealed the further ways to study how to create an effective technique for decoding reversible constructs (with the use of educational material on algebra).

Lying in a native and foreign language.

This study explores the interaction between deceptive language and second language processing. One hundred participants were asked to produce veridical and false statements in either their first or second language. Pupil size, speech latencies, and utterance durations were analyzed. Results showed additive effects of statement veracity and the language in which these statements were produced. That is, false statements elicited larger pupil dilations and longer naming latencies compared with veridical statements, and statements in the foreign language elicited larger pupil dilations and longer speech durations and compared with first language. Importantly, these two effects did not interact, suggesting that the processing cost associated with deception is similar in a native and foreign language. The theoretical implications of these observations are discussed.

An analysis of programming language statement frequency in C, C++, and Java source code

SummaryStatement frequency data can inform programming language research and provide a solid basis for frequency‐based code analysis. This paper presents an analysis of programming language statement frequency in a large corpus of C, C++, and Java source code, comprised of more than 54 million lines of code. Across these languages, the top four work‐performing statement types are Method/Function Call, Assignment, If, and Return. As compared to studies of Formula Translating System, Common Business Oriented Language and Programming Language One in the 1970s, the main change is the prevalence of method/function calls. Statement use frequency across languages is remarkably similar, and within each individual language, most statement types have a frequency distribution that occupies a small range. A more detailed examination of assignment and looping statement types shows that many assignments simply involve copying of data and that C++/Java use for statements more than C. Copyright © 2014 John Wiley &amp; Sons, Ltd.