1,721,040 research outputs found
Combined distributional and logical semantics
Full text linkUnderstanding natural language sentences requires interpreting words, and combining
the meanings of words into the meanings of sentences. Despite much work on lexical
and compositional semantics individually, existing approaches are unlikely to offer a
complete solution. This thesis introduces a new approach, which combines the benefits
of distributional lexical semantics and logical compositional semantics.
Linguistic theories of compositional semantics have shown how logical forms can
be built for sentences, and how to represent semantic operators such as negatives,
quantifiers and modals. However, computational implementations of such theories
have shown poor performance on applications, mainly due to a reliance on incomplete
hand-built ontologies for the meanings of content words. Conversely, distributional semantics
has been shown to be effective in learning the representations of content words
based on collocations in large unlabelled corpora, but there are major outstanding challenges
in representing function words and building representations for sentences.
I introduce a new model which captures the main advantages of logical and distributional
approaches. The proposal closely follows formal semantics, except for changing
the definitions of content words. In traditional formal semantics, each word would
express a different symbol. Instead, I allow multiple words to express the same symbol,
corresponding to underlying concepts. For example, both the verb write and the noun
author can be made to express the same relation. These symbols can be learnt by clustering
symbols based on distributional statistics—for example, write and author will
share many similar arguments. Crucially, the clustering means that the representations
are symbolic, so can easily be incorporated into standard logical approaches.
The simple model proves insufficient, and I develop several extensions. I develop
an unsupervised probabilistic model of ambiguity, and show how this model can be
built into compositional derivations to produce a distribution over logical forms. The
flat clustering approach does not model relations between concepts, for example that
buying implies owning. Instead, I show how to build graph structures over the clusters,
which allows such inferences. I also explore if the abstract concepts can be generalized
cross-lingually, for example mapping French verb ecrire to the same cluster as
the English verb write. The systems developed show good performance on question
answering and entailment tasks, and are capable of both sophisticated multi-sentence
inferences involving quantifiers, and subtle reasoning about lexical semantics.
These results show that distributional and formal logical semantics are not mutually
exclusive, and that a combined model can be built that captures the advantages of each
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Full text link“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
Full text linkWe 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
Full text linkWe 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
No full textWe 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
Natural Language Generation for the Semantic Web: Unsupervised template extraction
No full textI propose an architecture for a Natural Language Generation system that automatically learns sentence templates, together with statistical document planning, from parallel RDF data and text. To this end, I design, build and test a proof-of-concept system (“LOD-DEF”) trained on un-annotated text from the Simple English Wikipedia and RDF triples from DBpedia, with the communicative goal of generating short descriptions of entities in an RDF ontology. Inspired by previous work, I implement a baseline triple-to-text generation system and I conduct human evaluation the LOD-DEF system against the baseline and human-generated output. LOD-DEF significantly outperforms the baseline on two of three measures: non-redundancy and structure and coherence
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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