994 resultados para Figurative language


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Language Modeling (LM) has been successfully applied to Information Retrieval (IR). However, most of the existing LM approaches only rely on term occurrences in documents, queries and document collections. In traditional unigram based models, terms (or words) are usually considered to be independent. In some recent studies, dependence models have been proposed to incorporate term relationships into LM, so that links can be created between words in the same sentence, and term relationships (e.g. synonymy) can be used to expand the document model. In this study, we further extend this family of dependence models in the following two ways: (1) Term relationships are used to expand query model instead of document model, so that query expansion process can be naturally implemented; (2) We exploit more sophisticated inferential relationships extracted with Information Flow (IF). Information flow relationships are not simply pairwise term relationships as those used in previous studies, but are between a set of terms and another term. They allow for context-dependent query expansion. Our experiments conducted on TREC collections show that we can obtain large and significant improvements with our approach. This study shows that LM is an appropriate framework to implement effective query expansion.

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Intuitively, any ‘bag of words’ approach in IR should benefit from taking term dependencies into account. Unfortunately, for years the results of exploiting such dependencies have been mixed or inconclusive. To improve the situation, this paper shows how the natural language properties of the target documents can be used to transform and enrich the term dependencies to more useful statistics. This is done in three steps. The term co-occurrence statistics of queries and documents are each represented by a Markov chain. The paper proves that such a chain is ergodic, and therefore its asymptotic behavior is unique, stationary, and independent of the initial state. Next, the stationary distribution is taken to model queries and documents, rather than their initial distributions. Finally, ranking is achieved following the customary language modeling paradigm. The main contribution of this paper is to argue why the asymptotic behavior of the document model is a better representation then just the document’s initial distribution. A secondary contribution is to investigate the practical application of this representation in case the queries become increasingly verbose. In the experiments (based on Lemur’s search engine substrate) the default query model was replaced by the stable distribution of the query. Just modeling the query this way already resulted in significant improvements over a standard language model baseline. The results were on a par or better than more sophisticated algorithms that use fine-tuned parameters or extensive training. Moreover, the more verbose the query, the more effective the approach seems to become.

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Beryl & Gael discuss the ‘new’ metalanguage for knowledge about language presented in the Australian Curriculum English (ACARA, 2010). Their discussion connects to practice by recounting how one teacher scaffolds her students through detailed understandings of noun and adjective groups in reading activities. The stimulus text is the novel ‘A wrinkle in time’ (L’Engle, 1962, reproduced 2007) and the purpose is to build students’ understandings so they can work towards ‘expressing and developing ideas’ in written text (ACARA, 2010).

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This paper reports results from a study exploring the multimedia search functionality of Chinese language search engines. Web searching in Chinese (Mandarin) is a growing research area and a technical challenge for popular commercial Web search engines. Few studies have been conducted on Chinese language search engines. We investigate two research questions: which Chinese language search engines provide multimedia searching, and what multimedia search functionalities are available in Chinese language Web search engines. Specifically, we examine each Web search engine's (1) features permitting Chinese language multimedia searches, (2) extent of search personalization and user control of multimedia search variables, and (3) the relationships between Web search engines and their features in the Chinese context. Key findings show that Chinese language Web search engines offer limited multimedia search functionality, and general search engines provide a wider range of features than specialized multimedia search engines. Study results have implications for Chinese Web users, Website designers and Web search engine developers. © 2009 Elsevier Ltd. All rights reserved.

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The Lingodroids are a pair of mobile robots that evolve a language for places and relationships between places (based on distance and direction). Each robot in these studies has its own understanding of the layout of the world, based on its unique experiences and exploration of the environment. Despite having different internal representations of the world, the robots are able to develop a common lexicon for places, and then use simple sentences to explain and understand relationships between places even places that they could not physically experience, such as areas behind closed doors. By learning the language, the robots are able to develop representations for places that are inaccessible to them, and later, when the doors are opened, use those representations to perform goal-directed behavior.

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In second language classrooms, listening is gaining recognition as an active element in the processes of learning and using a second language. Currently, however, much of the teaching of listening prioritises comprehension without sufficient emphasis on the skills and strategies that enhance learners’ understanding of spoken language. This paper presents an argument for rethinking the emphasis on comprehension and advocates augmenting current teaching with an explicit focus on strategies. Drawing on the literature, the paper provides three models of strategy instruction for the teaching and development of listening skills. The models include steps for implementation that accord with their respective approaches to explicit instruction. The final section of the paper synthesises key points from the models as a guide for application in the second language classroom. The premise underpinning the paper is that the teaching of strategies can provide learners with active and explicit measures for managing and expanding their listening capacities, both in the learning and ‘real world’ use of a second language.

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This chapter reports on a study of oracy in a first-year university Business course, with particular interest in the oracy demands for second language-using international students. The research is relevant at a time when Higher Education is characterised by the confluence of increased international enrolments, more dialogic teaching and learning, and imperatives for teamwork and collaboration. Data sources for the study included videotaped lectures and tutorials, course documents, student surveys, and an interview with the lecturer. The findings pointed to a complex, oracy-laden environment where interactive talk fulfilled high-stakes functions related to social inclusion, the co-construction of knowledge, and the accomplishment of assessment tasks. The salience of talk posed significant challenges for students negotiating these core functions in their second language. The study highlights the oracy demands in university courses and foregrounds the need for university teachers, curriculum writers and speaking test developers to recognise these demands and explicate them for the benefit of all students.

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With the recognition that language both reflects and constructs culture and English now widely acknowledged as an international language, the cul-tural content of language teaching materials is now being problematised. Through a quantitative analysis, this chapter focuses on opportunities for intercultural understanding and connectedness through representations of the identities that appear in two leading English language textbooks. The analyses reveal that the textbooks orientate towards British and western identities with representations of people from non-European/non-Western backgrounds being notable for their absence, while others are hidden from view. Indeed there would appear to be a neocolonialist orientation in oper-ation in the textbooks, one that aligns English with the West. The chapter proposes arguments for the consideration of cultural diversity in English language teaching (ELT) textbook design, and promoting intercultural awareness and acknowledging the contexts in which English is now being used. It also offers ways that teachers can critically reflect on existing ELT materials and proposes arguments for including different varieties of Eng-lish in order to ensure a level of intercultural understanding and connect-edness.

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Service-oriented Architectures (SOA) and Web services leverage the technical value of solutions in the areas of distributed systems and cross-enterprise integration. The emergence of Internet marketplaces for business services is driving the need to describe services, not only from a technical level, but also from a business and operational perspective. While, SOA and Web services reside in an IT layer, organizations owing Internet marketplaces are requiring advertising and trading business services which reside in a business layer. As a result, the gap between business and IT needs to be closed. This paper presents USDL (Unified Service Description Language), a specification language to describe services from a business, operational and technical perspective. USDL plays a major role in the Internet of Services to describe tradable services which are advertised in electronic marketplaces. The language has been tested using two service marketplaces as use cases.

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In information retrieval (IR) research, more and more focus has been placed on optimizing a query language model by detecting and estimating the dependencies between the query and the observed terms occurring in the selected relevance feedback documents. In this paper, we propose a novel Aspect Language Modeling framework featuring term association acquisition, document segmentation, query decomposition, and an Aspect Model (AM) for parameter optimization. Through the proposed framework, we advance the theory and practice of applying high-order and context-sensitive term relationships to IR. We first decompose a query into subsets of query terms. Then we segment the relevance feedback documents into chunks using multiple sliding windows. Finally we discover the higher order term associations, that is, the terms in these chunks with high degree of association to the subsets of the query. In this process, we adopt an approach by combining the AM with the Association Rule (AR) mining. In our approach, the AM not only considers the subsets of a query as “hidden” states and estimates their prior distributions, but also evaluates the dependencies between the subsets of a query and the observed terms extracted from the chunks of feedback documents. The AR provides a reasonable initial estimation of the high-order term associations by discovering the associated rules from the document chunks. Experimental results on various TREC collections verify the effectiveness of our approach, which significantly outperforms a baseline language model and two state-of-the-art query language models namely the Relevance Model and the Information Flow model

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In the era of Web 2.0, huge volumes of consumer reviews are posted to the Internet every day. Manual approaches to detecting and analyzing fake reviews (i.e., spam) are not practical due to the problem of information overload. However, the design and development of automated methods of detecting fake reviews is a challenging research problem. The main reason is that fake reviews are specifically composed to mislead readers, so they may appear the same as legitimate reviews (i.e., ham). As a result, discriminatory features that would enable individual reviews to be classified as spam or ham may not be available. Guided by the design science research methodology, the main contribution of this study is the design and instantiation of novel computational models for detecting fake reviews. In particular, a novel text mining model is developed and integrated into a semantic language model for the detection of untruthful reviews. The models are then evaluated based on a real-world dataset collected from amazon.com. The results of our experiments confirm that the proposed models outperform other well-known baseline models in detecting fake reviews. To the best of our knowledge, the work discussed in this article represents the first successful attempt to apply text mining methods and semantic language models to the detection of fake consumer reviews. A managerial implication of our research is that firms can apply our design artifacts to monitor online consumer reviews to develop effective marketing or product design strategies based on genuine consumer feedback posted to the Internet.

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Error correction is perhaps the most widely used method for responding to student writing. While various studies have investigated the effectiveness of providing error correction, there has been relatively little research incorporating teachers' beliefs, practices, and students' preferences in written error correction. The current study adopted features of an ethnographic research design in order to explore the beliefs and practices of ESL teachers, and investigate the preferences of L2 students regarding written error correction in the context of a language institute situated in the Brisbane metropolitan district. In this study, two ESL teachers and two groups of adult intermediate L2 students were interviewed and observed. The beliefs and practices of the teachers were elicited through interviews and classroom observations. The preferences of L2 students were elicited through focus group interviews. Responses of the participants were encoded and analysed. Results of the teacher interviews showed that teachers believe that providing written error correction has advantages and disadvantages. Teachers believe that providing written error correction helps students improve their proof-reading skills in order to revise their writing more efficiently. However, results also indicate that providing written error correction is very time consuming. Furthermore, teachers prefer to provide explicit written feedback strategies during the early stages of the language course, and move to a more implicit strategy of providing written error correction in order to facilitate language learning. On the other hand, results of the focus group interviews suggest that students regard their teachers' practice of written error correction as important in helping them locate their errors and revise their writing. However, students also feel that the process of providing written error correction is time consuming. Nevertheless, students want and expect their teachers to provide written feedback because they believe that the benefits they gain from receiving feedback on their writing outweigh the apparent disadvantages of their teachers' written error correction strategies.

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In this paper, we argue that second language (L2) reading research, which has been informed by studies involving first language (L1) alphabetic English reading, may be less relevant to L2 readers with non-alphabetic reading backgrounds, such as Chinese readers with an L1 logographic (Chinese character) learning history. We provide both neuroanatomical and behavioural evidence from Chinese language reading studies to support our claims. The paper concludes with an argument outlining the need for a universal L2 reading model which can adequately account for readers with diverse L1 orthographic language learning histories.

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Language-use has proven to be the most complex and complicating of all Internet features, yet people and institutions invest enormously in language and crosslanguage features because they are fundamental to the success of the Internet’s past, present and future. The thesis takes into focus the developments of the latter – features that facilitate and signify linking between or across languages – both in their historical and current contexts. In the theoretical analysis, the conceptual platform of inter-language linking is developed to both accommodate efforts towards a new social complexity model for the co-evolution of languages and language content, as well as to create an open analytical space for language and cross-language related features of the Internet and beyond. The practiced uses of inter-language linking have changed over the last decades. Before and during the first years of the WWW, mechanisms of inter-language linking were at best important elements used to create new institutional or content arrangements, but on a large scale they were just insignificant. This has changed with the emergence of the WWW and its development into a web in which content in different languages co-evolve. The thesis traces the inter-language linking mechanisms that facilitated these dynamic changes by analysing what these linking mechanisms are, how their historical as well as current contexts can be understood and what kinds of cultural-economic innovation they enable and impede. The study discusses this alongside four empirical cases of bilingual or multilingual media use, ranging from television and web services for languages of smaller populations, to large-scale, multiple languages involving web ventures by the British Broadcasting Corporation, the Special Broadcasting Service Australia, Wikipedia and Google. To sum up, the thesis introduces the concepts of ‘inter-language linking’ and the ‘lateral web’ to model the social complexity and co-evolution of languages online. The resulting model reconsiders existing social complexity models in that it is the first that can explain the emergence of large-scale, networked co-evolution of languages and language content facilitated by the Internet and the WWW. Finally, the thesis argues that the Internet enables an open space for language and crosslanguage related features and investigates how far this process is facilitated by (1) amateurs and (2) human-algorithmic interaction cultures.