942 resultados para Conceptual mistakes in text books


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Includes (p. [253]-460): Hymns and spritual songs. In three books. 1. Collected from the Scriptures. 2. Composed on divine subjects. 3. Prepared for the Lord's supper. By Isaac Watts ... Boston, 1819.

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Title varies.

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On cover: The reminiscences of a first whipper-in.

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Many mistakes in paging.

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Two studies investigated the context deletion effect, the attenuation of priming in implicit memory tests of words when words have been studied in text rather than in isolation. In Experiment 1, stem completion for single words was primed to a greater extent by words studied alone than in sentence contexts, and a higher proportion of completions from studied words was produced under direct instructions (cued recall) than under indirect instructions (produce the first completion that comes to mind). The effect of a sentence context was eliminated when participants were instructed to attend to the target word during the imagery generation task used in the study phase. In Experiment 2, the effect of a sentence context at study was reduced when the target word was presented in distinctive format within the sentence, and the study task (grammatical judgment) was directed at a word other than the target. The results implicate conceptual and perceptual processes that distinguish a word from its context in priming in word stem completion.

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This study presents a detailed contrastive description of the textual functioning of connectives in English and Arabic. Particular emphasis is placed on the organisational force of connectives and their role in sustaining cohesion. The description is intended as a contribution for a better understanding of the variations in the dominant tendencies for text organisation in each language. The findings are expected to be utilised for pedagogical purposes, particularly in improving EFL teaching of writing at the undergraduate level. The study is based on an empirical investigation of the phenomenon of connectivity and, for optimal efficiency, employs computer-aided procedures, particularly those adopted in corpus linguistics, for investigatory purposes. One important methodological requirement is the establishment of two comparable and statistically adequate corpora, also the design of software and the use of existing packages and to achieve the basic analysis. Each corpus comprises ca 250,000 words of newspaper material sampled in accordance to a specific set of criteria and assembled in machine readable form prior to the computer-assisted analysis. A suite of programmes have been written in SPITBOL to accomplish a variety of analytical tasks, and in particular to perform a battery of measurements intended to quantify the textual functioning of connectives in each corpus. Concordances and some word lists are produced by using OCP. Results of these researches confirm the existence of fundamental differences in text organisation in Arabic in comparison to English. This manifests itself in the way textual operations of grouping and sequencing are performed and in the intensity of the textual role of connectives in imposing linearity and continuity and in maintaining overall stability. Furthermore, computation of connective functionality and range of operationality has identified fundamental differences in the way favourable choices for text organisation are made and implemented.

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Abstract: Loss of central vision caused by age-related macular degeneration (AMD) is a problem affecting increasingly large numbers of people within the ageing population. AMD is the leading cause of blindness in the developed world, with estimates of over 600,000 people affected in the UK . Central vision loss can be devastating for the sufferer, with vision loss impacting on the ability to carry out daily activities. In particular, inability to read is linked to higher rates of depression in AMD sufferers compared to age-matched controls. Methods to improve reading ability in the presence of central vision loss will help maintain independence and quality of life for those affected. Various attempts to improve reading with central vision loss have been made. Most textual manipulations, including font size, have led to only modest gains in reading speed. Previous experimental work and theoretical arguments on spatial integrative properties of the peripheral retina suggest that ‘visual crowding’ may be a major factor contributing to inefficient reading. Crowding refers to the phenomena in which juxtaposed targets viewed eccentrically may be difficult to identify. Manipulating text spacing of reading material may be a simple method that reduces crowding and benefits reading ability in macular disease patients. In this thesis the effect of textual manipulation on reading speed was investigated, firstly for normally sighted observers using eccentric viewing, and secondly for observers with central vision loss. Test stimuli mimicked normal reading conditions by using whole sentences that required normal saccadic eye movements and observer comprehension. Preliminary measures on normally-sighted observers (n = 2) used forced-choice procedures in conjunction with the method of constant stimuli. Psychometric functions relating the proportion of correct responses to exposure time were determined for text size, font type (Lucida Sans and Times New Roman) and text spacing, with threshold exposure time (75% correct responses) used as a measure of reading performance. The results of these initial measures were used to derive an appropriate search space, in terms of text spacing, for assessing reading performance in AMD patients. The main clinical measures were completed on a group of macular disease sufferers (n=24). Firstly, high and low contrast reading acuity and critical print size were measured using modified MNREAD test charts, and secondly, the effect of word and line spacing was investigated using a new test, designed specifically for this study, called the Equal Readability Passages (ERP) test. The results from normally-sighted observers were in close agreement with those from the group of macular disease sufferers. Results show that: (i) optimum reading performance was achieved when using both double line and double word spacing; (ii) the effect of line spacing was greater than the effect of word spacing (iii) a text size of approximately 0.85o is sufficiently large for reading at 5o eccentricity. In conclusion, the results suggest that crowding is detrimental to reading with peripheral vision, and its effects can be minimized with a modest increase in text spacing.

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Much has been written on the organizational power of metaphor in discourse, eg on metaphor ‘chains’ and ‘clusters’ of linguistic metaphor in discourse (Koller 2003, Cameron & Stelma 2004, Semino 2008) and the role of extended and systematic metaphor in organizing long stretches of language, even whole texts (Cameron et al 2009, Cameron & Maslen 2010, Deignan et al 2013, Semino et al 2013). However, at times, this work belies the intricacies of how a single metaphoric idea can impact on a text. The focus of this paper is a UK media article derived from a HM Treasury press release on alleviating poverty. The language of the article draws heavily on orientational (spatial) metaphors, particularly metaphors of movement around GOOD IS UP. Although GOOD IS UP can be considered a single metaphoric idea, the picture the reader builds up as they move line by line through this text is complex and multifaceted. I take the idea of “building up a picture” literally in order to investigate the schema of motion relating to GOOD IS UP. To do this, fifteen informants (Masters students at a London university), tutored in Cognitive Metaphor Theory, were asked to read the article and underline words and expressions they felt related to GOOD IS UP. The text was then read back to the informant with emphasis given to the words they had underlined, while they drew a pictorial representation of the article based on the meanings of these words, integrating their drawings into a single picture as they went along. I present examples of the drawings the informants produced. I propose that using Metaphor-led Discourse Analysis to produce visual material in this way offers useful insights into how metaphor contributes to meaning making at text level. It shows how a metaphoric idea, such as GOOD IS UP, provides the text producer with a rich and versatile meaning-making resource for constructing text; and gives a ‘mind-map’ of how certain aspects of a media text are decoded by the text receiver. It also offers a partial representation of the elusive, intermediate ‘deverbalized’ stage of translation (Lederer 1987), where the sense of the source text is held in the mind before it is transferred to the target language. References Cameron, L., R. Maslen, Z. Todd, J. Maule, P. Stratton & N. Stanley. 2009. ‘The discourse dynamic approach to metaphor and metaphor-led analysis’. Metaphor and Symbol, 24(2), 63-89. Cameron, L. & R. Maslen (eds). 2010. Metaphor Analysis: Research Practice in Applied Linguistics, Social Sciences and Humanities. London: Equinox. Cameron, L. & J. Stelma. 2004. ‘Metaphor Clusters in Discourse’. Journal of Applied Linguistics, 1(2), 107-136. Deignan, A., J. Littlemore & E. Semino. 2013. Figurative Language, Genre and Register. Cambridge: Cambridge University Press. Koller, V. 2003. ‘Metaphor Clusters, Metaphor Chains: Analyzing the Multifunctionality of Metaphor in Text’. metaphorik.de, 5, 115-134. Lederer, M. 1987. ‘La théorie interprétative de la traduction’ in Retour à La Traduction. Le Francais dans Le Monde. Semino, E. 2008. Metaphor in Discourse. Cambridge: Cambridge University Press. Semino, E., A. Deignan & J. Littlemore. 2013. ‘Metaphor, Genre, and Recontextualization’. Metaphor and Symbol. 28(1), 41-59.

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One of the leading motivations behind the multilingual semantic web is to make resources accessible digitally in an online global multilingual context. Consequently, it is fundamental for knowledge bases to find a way to manage multilingualism and thus be equipped with those procedures for its conceptual modelling. In this context, the goal of this paper is to discuss how common-sense knowledge and cultural knowledge are modelled in a multilingual framework. More particularly, multilingualism and conceptual modelling are dealt with from the perspective of FunGramKB, a lexico-conceptual knowledge base for natural language understanding. This project argues for a clear division between the lexical and the conceptual dimensions of knowledge. Moreover, the conceptual layer is organized into three modules, which result from a strong commitment towards capturing semantic knowledge (Ontology), procedural knowledge (Cognicon) and episodic knowledge (Onomasticon). Cultural mismatches are discussed and formally represented at the three conceptual levels of FunGramKB.

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This proposal is a non-quantitative study based on a corpus of real data which offers a principled account of the translation strategies employed in the translation of English film titles into Spanish in terms of cognitive modeling. More specifically, we draw on Ruiz de Mendoza and Galera’s (2014) work on what they term content (or low-level) cognitive operations, based on either ‘stands for’ or ‘identity’ relations, in order to investigate possible motivating factors for translations which abide by oblique procedures, i.e. for non-literal renderings of source titles. The present proposal is made in consonance with recent findings within the framework of Cognitive Linguistics (Samaniego 2007), which evidence that this linguistic approach can fruitfully address some relevant issues in Translation Studies, the most outstanding for our purposes being the exploration of the cognitive operations which account for the use of translation strategies (Rojo and Ibarretxe-Antuñano 2013: 10), mainly expansion and reduction operations, parameterization, echoing, mitigation and comparison by contrast. This fits in nicely with a descriptive approach to translation and particularly with skopos theory, whose main aim consists in achieving functionally adequate renderings of source texts.

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With the dramatic growth of text information, there is an increasing need for powerful text mining systems that can automatically discover useful knowledge from text. Text is generally associated with all kinds of contextual information. Those contexts can be explicit, such as the time and the location where a blog article is written, and the author(s) of a biomedical publication, or implicit, such as the positive or negative sentiment that an author had when she wrote a product review; there may also be complex context such as the social network of the authors. Many applications require analysis of topic patterns over different contexts. For instance, analysis of search logs in the context of the user can reveal how we can improve the quality of a search engine by optimizing the search results according to particular users; analysis of customer reviews in the context of positive and negative sentiments can help the user summarize public opinions about a product; analysis of blogs or scientific publications in the context of a social network can facilitate discovery of more meaningful topical communities. Since context information significantly affects the choices of topics and language made by authors, in general, it is very important to incorporate it into analyzing and mining text data. In general, modeling the context in text, discovering contextual patterns of language units and topics from text, a general task which we refer to as Contextual Text Mining, has widespread applications in text mining. In this thesis, we provide a novel and systematic study of contextual text mining, which is a new paradigm of text mining treating context information as the ``first-class citizen.'' We formally define the problem of contextual text mining and its basic tasks, and propose a general framework for contextual text mining based on generative modeling of text. This conceptual framework provides general guidance on text mining problems with context information and can be instantiated into many real tasks, including the general problem of contextual topic analysis. We formally present a functional framework for contextual topic analysis, with a general contextual topic model and its various versions, which can effectively solve the text mining problems in a lot of real world applications. We further introduce general components of contextual topic analysis, by adding priors to contextual topic models to incorporate prior knowledge, regularizing contextual topic models with dependency structure of context, and postprocessing contextual patterns to extract refined patterns. The refinements on the general contextual topic model naturally lead to a variety of probabilistic models which incorporate different types of context and various assumptions and constraints. These special versions of the contextual topic model are proved effective in a variety of real applications involving topics and explicit contexts, implicit contexts, and complex contexts. We then introduce a postprocessing procedure for contextual patterns, by generating meaningful labels for multinomial context models. This method provides a general way to interpret text mining results for real users. By applying contextual text mining in the ``context'' of other text information management tasks, including ad hoc text retrieval and web search, we further prove the effectiveness of contextual text mining techniques in a quantitative way with large scale datasets. The framework of contextual text mining not only unifies many explorations of text analysis with context information, but also opens up many new possibilities for future research directions in text mining.