877 resultados para natural language


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The article briefly reviews bilingual Slovak-Bulgarian/Bulgarian-Slovak parallel and aligned corpus. The corpus is collected and developed as results of the collaboration in the frameworks of the joint research project between Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, and Ľ. Štúr Institute of Linguistics, Slovak Academy of Sciences. The multilingual corpora are large repositories of language data with an important role in preserving and supporting the world's cultural heritage, because the natural language is an outstanding part of the human cultural values and collective memory, and a bridge between cultures. This bilingual corpus will be widely applicable to the contrastive studies of the both Slavic languages, will also be useful resource for language engineering research and development, especially in machine translation.

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The current study is a post-hoc analysis of data from the original randomized control trial of the Play and Language for Autistic Youngsters (PLAY) Home Consultation program, a parent-mediated, DIR/Floortime based early intervention program for children with ASD (Solomon, Van Egeren, Mahone, Huber, & Zimmerman, 2014). We examined 22 children from the original RCT who received the PLAY program. Children were split into two groups (high and lower functioning) based on the ADOS module administered prior to intervention. Fifteen-minute parent-child video sessions were coded through the use of CHILDES transcription software. Child and maternal language, communicative behaviors, and communicative functions were assessed in the natural language samples both pre- and post-intervention. Results demonstrated significant improvements in both child and maternal behaviors following intervention. There was a significant increase in child verbal and non-verbal initiations and verbal responses in whole group analysis. Total number of utterances, word production, and grammatical complexity all significantly improved when viewed across the whole group of participants; however, lexical growth did not reach significance. Changes in child communicative function were especially noteworthy, and demonstrated a significant increase in social interaction and a significant decrease in non-interactive behaviors. Further, mothers demonstrated an increase in responsiveness to the child’s conversational bids, increased ability to follow the child’s lead, and a decrease in directiveness. When separated for analyses within groups, trends emerged for child and maternal variables, suggesting greater gains in use of communicative function in both high and low groups over changes in linguistic structure. Additional analysis also revealed a significant inverse relationship between maternal responsiveness and child non-interactive behaviors; as mothers became more responsive, children’s non-engagement was decreased. Such changes further suggest that changes in learned skills following PLAY parent training may result in improvements in child social interaction and language abilities.

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O processamento de linguagem natural e as ontologias são ferramentas cuja interação permite uma melhor compreensão dos dados armazenados. Este trabalho, ao associar estas duas áreas aos elementos disponíveis numa base de dados prosopográfica, tornou possível identificar e classificar relacionamentos entre setores de ocupação na forma como eram designados na época, setores de atividade num formato mais próximo do de hoje e o estatuto social que essas incumbências tinham na sociedade coeva. Os dados utilizados são sobretudo de membros do Santo Ofício – do século XVI ao século XVIII. Para atingir este objetivo utilizaram-se algumas descrições textuais de ocorrências da época e outras pouco estruturadas, disponíveis no repositório SPARES. A aplicação de processamento de linguagem natural (remoção de stopwords e aplicação de stemming), conjugada com a construção de duas ontologias, tornou possível classificar esses dados, permitindo consultas mais eficazes. Ao contribuir para a classificação automática de dados históricos, propõem-se metodologias que podem ser aplicadas em dados de qualquer outra área do conhecimento, especialmente as que lidam com as variáveis de tempo e espaço de forma mais intensa; Abstract: OntoSPARES: from natural language to ontologies Contributions to the automatic classification of historical data (16th-18th centuries) The interaction between the natural language processing and ontologies are tools allowing a better understanding of the data stored. This work, by combining these two areas to the elements available in a prosopographic database, has made possible to identify and classify relationships between occupations of many individuals (in general Holy Office members of the 16th-18th centuries). To achieve this goal the data used was gathered in SPARES repository, including some textual descriptions of the time occurrences. They are all few structured. The application of natural language processing (stopwords removal and stemming application), combined with the construction of two ontologies, made possible to classify those data, allowing a more effective search. By contributing to the automatic classification of historical data, this thesis proposes methodologies that can be applied to data from any other field of knowledge, specially data dealing with time and space variables.

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Novice programmers have difficulty developing an algorithmic solution while simultaneously obeying the syntactic constraints of the target programming language. To see how students fare in algorithmic problem solving when not burdened by syntax, we conducted an experiment in which a large class of beginning programmers were required to write a solution to a computational problem in structured English, as if instructing a child, without reference to program code at all. The students produced an unexpectedly wide range of correct, and attempted, solutions, some of which had not occurred to their teachers. We also found that many common programming errors were evident in the natural language algorithms, including failure to ensure loop termination, hardwiring of solutions, failure to properly initialise the computation, and use of unnecessary temporary variables, suggesting that these mistakes are caused by inexperience at thinking algorithmically, rather than difficulties in expressing solutions as program code.

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Current regulatory requirements on data privacy make it increasingly important for enterprises to be able to verify and audit their compliance with their privacy policies. Traditionally, a privacy policy is written in a natural language. Such policies inherit the potential ambiguity, inconsistency and mis-interpretation of natural text. Hence, formal languages are emerging to allow a precise specification of enforceable privacy policies that can be verified. The EP3P language is one such formal language. An EP3P privacy policy of an enterprise consists of many rules. Given the semantics of the language, there may exist some rules in the ruleset which can never be used, these rules are referred to as redundant rules. Redundancies adversely affect privacy policies in several ways. Firstly, redundant rules reduce the efficiency of operations on privacy policies. Secondly, they may misdirect the policy auditor when determining the outcome of a policy. Therefore, in order to address these deficiencies it is important to identify and resolve redundancies. This thesis introduces the concept of minimal privacy policy - a policy that is free of redundancy. The essential component for maintaining the minimality of privacy policies is to determine the effects of the rules on each other. Hence, redundancy detection and resolution frameworks are proposed. Pair-wise redundancy detection is the central concept in these frameworks and it suggests a pair-wise comparison of the rules in order to detect redundancies. In addition, the thesis introduces a policy management tool that assists policy auditors in performing several operations on an EP3P privacy policy while maintaining its minimality. Formal results comparing alternative notions of redundancy, and how this would affect the tool, are also presented.

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Following an early claim by Nelson & McEvoy suggesting that word associations can display `spooky action at a distance behaviour', a serious investigation of the potentially quantum nature of such associations is currently underway. In this paper quantum theory is proposed as a framework suitable for modelling the mental lexicon, specifically the results obtained from both intralist and extralist word association experiments. Some initial models exploring this hypothesis are discussed, and they appear to be capable of substantial agreement with pre-existing experimental data. The paper concludes with a discussion of some experiments that will be performed in order to test these models.