1,720,966 research outputs found
Exploring Language Mechanisms: The Mass-Count Distinction and The Potts Neural Network
The aim of this thesis is to explore language mechanisms in two aspects. First, the statistical properties of syntax and semantics, and second, the neural mechanisms which could be of possible use in trying to understand how the brain learns those particular statistical properties. In the first part of the thesis (part A) we focus our attention on a detailed statistical study of the syntax and semantics of the mass-count distinction in nouns. We collected a database of how 1,434 nouns are used with respect to the mass-count distinction in six languages; additional informants characterised the semantics of the underlying concepts. Results indicate only weak correlations between semantics and syntactic usage. The classification rather than being bimodal, is a graded distribution and it is similar across languages, but syntactic classes do not map onto each other, nor do they reflect, beyond weak correlations, semantic attributes of the concepts. These findings are in line with the hypothesis that much of the mass/count syntax emerges from language- and even speaker-specific grammaticalisation. Further, in chapter 3 we test the ability of a simple neural network to learn the syntactic and semantic relations of nouns, in the hope that it may throw some light on the challenges in modelling the acquisition of the mass-count syntax. It is shown that even though a simple self-organising neural network is insufficient to learn a mapping implementing a syntactic- semantic link, it does however show that the network was able to extract the concept of 'count', and to some extent that of ‘mass’ as well, without any explicit definition, from both the syntactic and from the semantic data.
The second part of the thesis (part B) is dedicated to studying the properties of the Potts neural network. The Potts neural network with its adaptive dynamics represents a simplified model of cortical mechanisms. Among other cognitive phenomena, it intends to model language production by utilising the latching behaviour seen in the network. We expect that a model of language processing should robustly handle various syntactic- semantic correlations amongst the words of a language. With this aim, we test the effect on storage capacity of the Potts network when the memories stored in it share non trivial correlations. Increase in interference between stored memories due to correlations is studied along with modifications in learning rules to reduce the interference. We find that when strongly correlated memories are incorporated in the storage capacity definition, the network is able to regain its storage capacity for low sparsity. Strong correlations also affect the latching behaviour of the Potts network with the network unable to latch from one memory to another. However latching is shown to be restored by modifying the learning rule. Lastly, we look at another feature of the Potts neural network, the indication that it may exhibit spin-glass characteristics. The network is consistently shown to exhibit multiple stable degenerate energy states other than that of pure memories. This is tested for different degrees of correlations in patterns, low and high connectivity, and different levels of global and local noise. We state some of the implications that the spin-glass nature of the Potts neural network may have on language processing
A neural network perspective on the syntactic-semantic association between mass and count nouns
Analysing aspects of how our brain processes language may provide, even before the language faculty is really understood, useful insights into higher order cognitive functions. We take a small exploratory step in this direction with an attempt to test the ability of a standard, biologically plausible self-organising neural network to learn the association between syntax and semantics around the mass-count distinction. The mass-count distinction relates to the countability or un-countability of nouns, both in terms of their syntactic usage and of their semantic perception. Our previous statistical study has shown that the mass-count distinction is not bimodal and exhibits complex fuzzy relations between syntax and semantics. A neural network that expresses competition amongst output neurons with lateral inhibition is shown to identify the basic classes of mass and count in the syntactic markers and to produce a graded distribution of the nouns along the mass-count spectrum. The network however fails to successfully map the semantic classes of the nouns to their syntactic usage, thus corroborating the hypothesis that the syntactic usage of nouns in the mass-count domain is not simply predicted by the semantics of the noun
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
We have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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