Semantically enriched Massive Open Online Courses (MOOCs) platform

Massive Open Online Courses (MOOCs) are becoming an essential source of information for both students and teachers. Noticeably, MOOCs have to adapt to the fast development of new technologies; they also have to satisfy the current generation of online students. The current MOOCs’ Management Systems, such as Coursera, Udacity, edX, etc., use content management platforms where content are organized in a hierarchical structure. We envision a new generation of MOOCs that support interpretability with formal semantics by using the SemanticWeb and the online social networks. Semantic technologies support more flexible information management than that offered by the current MOOCs’ platforms. Annotated information about courses, video lectures, assignments, students, teachers, etc., can be composed from heterogeneous sources, including contributions from the communities in the forum space. These annotations, combined with legacy data, build foundations for more efficient information discovery in MOOCs’ platforms. In this article we review various Collaborative Semantic Filtering technologies for building Semantic MOOCs’ management system, then, we present a prototype of a semantic middle-sized platform implemented at Western Kentucky University that answers these aforementioned requirements.     

基于桥连接的词典学习方法的语义解析

现阶段的语义解析方法大部分都基于组合语义,这类方法的核心就是词典。词典是词汇的集合,词汇定义了自然语言句子中词语到知识库本体中谓词的映射。语义解析一直面临着词典中词汇覆盖度不够的问题。针对此问题,该文在现有工作的基础上,提出了基于桥连接的词典学习方法,该方法能够在训练中自动引入新的词汇并加以学习,为了进一步提高新学习到的词汇的准确度,该文设计了新的词语—二元谓词的特征模板,并使用基于投票机制的核心词典获取方法。该文在两个公开数据集(WebQuestions和Free917)上进行了对比实验,实验结果表明,该文方法能够学习到新的词汇,提高词汇的覆盖度,进而提升语义解析系统的性能,特别是召回率。     

Mímir: An open-source semantic search framework for interactive information seeking and discovery

Semantic search is gradually establishing itself as the next generation search paradigm, which meets better a wider range of information needs, as compared to traditional full-text search. At the same time, however, expanding search towards document structure and external, formal knowledge sources (e.g. LOD resources) remains challenging, especially with respect to efficiency, usability, and scalability.This paper introduces Mímir—an open-source framework for integrated semantic search over text, document structure, linguistic annotations, and formal semantic knowledge. Mímir supports complex structural queries, as well as basic keyword search.Exploratory search and sense-making are supported through information visualisation interfaces, such as co-occurrence matrices and term clouds. There is also an interactive retrieval interface, where users can save, refine, and analyse the results of a semantic search over time. The more well-studied precision-oriented information seeking searches are also well supported.The generic and extensible nature of the Mímir platform is demonstrated through three different, real-world applications, one of which required indexing and search over tens of millions of documents and fifty to hundred times as many semantic annotations. Scaling up to over 150 million documents was also accomplished, via index federation and cloud-based deployment.     

Word length and lexical activation: Longer is better.

Many models of spoken word recognition posit the existence of lexical and sublexical representations, with excitatory and inhibitory mechanisms used to affect the activation levels of such representations. Bottom-up evidence provides excitatory input, and inhibition from phonetically similar representations leads to lexical competition. In such a system, long words should produce stronger lexical activation than short words, for 2 reasons: Long words provide more bottom-up evidence than short words, and short words are subject to greater inhibition due to the existence of more similar words. Four experiments provide evidence for this view. In addition, reaction-time-based partitioning of the data shows that long words generate greater activation that is available both earlier and for a longer time than is the case for short words. As a result, lexical influences on phoneme identification are extremely robust for long words but are quite fragile and condition-dependent for short words. Models of word recognition must consider words of all lengths to capture the true dynamics of lexical activation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

"Interactive use of lexical information in speech perception": Correction to Connine and Clifton.

Reports an error in "Interactive use of lexical information in speech perception" by Cynthia M. Connine and Charles Clifton (Journal of Experimental Psychology: Human Perception and Performance, 1987[May], Vol 13[2], 291-299). In the aforementioned article, Figures 1 and 2 were inadvertently transposed. The figure on p. 294 is actually Figure 2, and the figure on p. 296 is actually Figure 1. The captions are correct as they stand. (The following abstract of the original article appeared in record 1987-23984-001.) Two experiments are reported that demonstrate contextual effects on identification of speech voicing continua. Experiment 1 demonstrated the infuence of lexical knowledge on identification of ambiguous tokens from word–nonword and nonword–word continua. Reaction times for word and nonword responses showed a word advantage only for ambiguous stimulus tokens (at the category boundary); no word advantage was found for clear stimuli (at the continua endpoints). Experiment 2 demonstrated an effect of a postperceptual variable, monetary payoff, on nonword–nonword continua. Identification responses were influenced by monetary payoff, but reaction times for bias-consistent and bias-inconsistent responses did not differ at the category boundary. An advantage for bias-consistent responses was evident at the continua endpoints. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Another Perspective on Vocabulary Richness

This article examines the usefulness ofvocabulary richness for authorship attributionand tests the assumption that appropriatemeasures of vocabulary richness can capture anauthor's distinctive style or identity. Afterbriefly discussing perceived and actualvocabulary richness, I show that doubling andcombining texts affects some measures incomputationally predictable but conceptuallysurprising ways. I discuss some theoretical andempirical problems with some measures anddevelop simple methods to test how wellvocabulary richness distinguishes texts bydifferent authors. These methods show thatvocabulary richness is ineffective for largegroups of texts because of the extremevariability within and among them. I concludethat vocabulary richness is of marginal valuein stylistic and authorship studies because thebasic assumption that it constitutes awordprint for authors is false.     

The time course of plausibility effects on eye movements in reading: Evidence from noun-noun compounds.

Readers' eye movements were monitored as they read sentences containing noun-noun compounds that varied in frequency (e.g., elevator mechanic, mountain lion). The left constituent of the compound was either plausible or implausible as a head noun at the point at which it appeared, whereas the compound as a whole was always plausible. When the head noun analysis of the left constituent was implausible, reading times on this word were inflated, beginning with the first fixation. This finding is consistent with previous demonstrations of very rapid effects of plausibility on eye movements. Compound frequency did not modulate the plausibility effect, and all disruption was resolved by the time readers' eyes moved to the next word. These findings suggest (contra Kennison, 2005) that the parser initially analyzes a singular noun as a head instead of a modifier. In addition, the findings confirm that the very rapid effect of plausibility on eye movements is not due to strategic factors, because in the present experiment, unlike in previous demonstrations, this effect appeared in sentences that were globally plausible. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

What's the use of being happy? Mood states, useful objects, and repetition priming effects.

Two experiments involving 99 undergraduate participants sought to examine the influence of mood states on encoding speed within lexical decision and pronunciation tasks. Mood states were measured naturalistically in Experiment 1 and manipulated in Experiment 2. Stimuli consisted of nouns representing useful (e.g., food) and nonuseful (e.g., lint) objects. Mood states had no implications for initial encoding speed. However, when the same words were presented a 2nd time (i.e., repeated), happy individuals displayed a tendency to encode useful words faster than nonuseful ones. Thus, mood states influenced repetition priming on the basis of stimulus valence. The authors propose that happiness sensitizes individuals to useful or rewarding objects, which in turn creates a stronger memory trace for such stimuli in the future. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Working memory in mild Alzheimer's disease and early Parkinson's disease.

Alzheimer's disease (AD) and Parkinson's disease (PD) impair working memory (WM). It is unclear, however, whether the deficits seen early in the course of these diseases are similar. To address this issue, the authors compared the performance of 22 patients with mild AD, 20 patients with early PD and without dementia, and 112 control participants on tests of inhibition, short-term memory, and 2 commonly administered tests of WM. The results suggest that although mild AD and early PD both impair WM, the deficits may be related to the interruption of different processes that contribute to WM performance. Early PD disrupted inhibitory processes, whereas mild AD did not. The WM deficits seen in patients with AD may be secondary to deficits in other cognitive capacities, including semantic memory. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

NL句法分析中超语法符合现象的处理

本文回顾并总结了句法层次上六种不同类型的超语法符合(extra grammaticality,简称EG)现象及它们的恢复原则, 描述了如何用扩充的GLR分析器(Extended GLR Parser简称EGLR)完整解决其中四种、部分解决其余两种现象的技术。在处理后两种现象时, 要涉及语义问题。