1,720,984 research outputs found
Aligning texts and knowledge bases with semantic sentence simplification
Finding the natural language equivalent of structured data is both a challenging and promising task. In particular, an efficient alignment of knowledge bases with texts would benefit many applications, including natural language generation, information retrieval and text simplification. In this paper, we present an approach to build a dataset of triples aligned with equivalent sentences written in natural language. Our approach consists of three main steps. First, target sentences are annotated automatically with knowledge base (KB) concepts and instances. The triples linking these elements in the KB are extracted as candidate facts to be aligned with the annotated sentence. Second, we use textual mentions referring to the subject and object of these facts to semantically simplify the target sentence via crowdsourcing. Third, the sentences provided by different contributors are post-processed to keep only the most relevant simplifications for the alignment with KB facts. We present different filtering methods, and share the constructed datasets in the public domain. These datasets contain 1050 sentences aligned with 1885 triples. They can be used to train natural language generators as well as semantic or contextual text simplifiers
Aligning Texts and Knowledge Bases with Semantic Sentence Simplification
The linked repository contains the resultant datasets of the Semantic Sentence Simplification (S3) methodology. Two high quality data-to-text corpora have been built: (i) DBpedia triples aligned with single Wikipedia sentences and (ii) triples from the Unified Medical Language System (UMLS) aligned with single MedlinePlus sentences.</span
Microbial named entity recognition using BERT models
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2024-08-01The student, Brian Rao, accepted the attached license on 2022-07-20 at 11:54.The student, Brian Rao, submitted this Thesis for approval on 2022-07-20 at 13:17.This Thesis was approved for publication on 2022-07-21 at 08:51.DSpace SAF Submission Ingestion Package generated from Vireo submission #18392 on 2022-11-16 at 10:56:38Bacteria are critical subjects of microbiological research that span many rapidly-growing fields of study. The development and widespread application of high-throughput sequencing has led to more microbial data being collected in recent years than ever before. This study investigates the capabilities of the popular Natural Language Processing (NLP) model Bidirectional Encoder Representations from Transformers (BERT) on the relatively understudied text mining domain of microbiology. This is done by fine-tuning a variety of BERT models (BERT, DistilBERT, SciBERT, BioBERT, PubMedBERT) on the Bacteria Biotope 2019 Open Shared Task (BB2019-OST) corpus of annotated microbial research text and evaluating the best performing models on the Named Entity Recognition (NER) task. Following this, an in-depth error analysis was conducted to gain insights into BERT’s entity recognition capabilities. Finally, to investigate performance capabilities further, learning rate and batch size hyperparameters were tuned to increase F1-score. The best BERT model in the comparison was BioBERT, earning an F1-score of 73.82 (±1.04) with default hyperparameters, and 75.35 (±0.62) with tuned hyperparameters. BioBERT had better F1-scores and entity-level statistics, despite PubMedBERT ranking high in biomedical NLP benchmarks. This suggests that the generality of the pretraining corpora of BERT models is particularly important for text mining in the microbial domain
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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