Relevant bibliographies by topics / Manual annotation

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  2. Dissertations / Theses
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  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Manual annotation'

Author: Grafiati
Published: 4 June 2021
Last updated: 11 June 2025

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Journal articles on the topic "Manual annotation"

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Hecksel, Corey W., Michele C. Darrow, Wei Dai, et al. "Quantifying Variability of Manual Annotation in Cryo-Electron Tomograms." Microscopy and Microanalysis 22, no. 3 (2016): 487–96. http://dx.doi.org/10.1017/s1431927616000799.

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AbstractAlthough acknowledged to be variable and subjective, manual annotation of cryo-electron tomography data is commonly used to answer structural questions and to create a “ground truth” for evaluation of automated segmentation algorithms. Validation of such annotation is lacking, but is critical for understanding the reproducibility of manual annotations. Here, we used voxel-based similarity scores for a variety of specimens, ranging in complexity and segmented by several annotators, to quantify the variation among their annotations. In addition, we have identified procedures for merging annotations to reduce variability, thereby increasing the reliability of manual annotation. Based on our analyses, we find that it is necessary to combine multiple manual annotations to increase the confidence level for answering structural questions. We also make recommendations to guide algorithm development for automated annotation of features of interest.
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Rele, Chinmay P., Katie M. Sandlin, Wilson Leung, and Laura K. Reed. "Manual annotation of Drosophila genes: a Genomics Education Partnership protocol." F1000Research 11 (December 23, 2022): 1579. http://dx.doi.org/10.12688/f1000research.126839.1.

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Annotating the genomes of multiple species allows us to analyze the evolution of their genes. While many eukaryotic genome assemblies already include computational gene predictions, these predictions can benefit from review and refinement through manual gene annotation. The Genomics Education Partnership (GEP; https://thegep.org/) developed a structural annotation protocol for protein-coding genes that enables undergraduate student and faculty researchers to create high-quality gene annotations that can be utilized in subsequent scientific investigations. For example, this protocol has been utilized by the GEP faculty to engage undergraduate students in the comparative annotation of genes involved in the insulin signaling pathway in 27 Drosophila species, using D. melanogaster as the reference genome. Students construct gene models using multiple lines of computational and empirical evidence including expression data (e.g., RNA-Seq), sequence similarity (e.g., BLAST and multiple sequence alignment), and computational gene predictions. Quality control measures require each gene be annotated by at least two students working independently, followed by reconciliation of the submitted gene models by a more experienced student. This article provides an overview of the annotation protocol and describes how discrepancies in student submitted gene models are resolved to produce a final, high-quality gene set suitable for subsequent analyses. The protocol can be adapted to other scientific questions (e.g., expansion of the Drosophila Muller F element) and species (e.g., parasitoid wasps) to provide additional opportunities for undergraduate students to participate in genomics research. These student annotation efforts can substantially improve the quality of gene annotations in publicly available genomic databases.
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Finlayson, Mark. "The Story Workbench: An Extensible Semi-Automatic Text Annotation Tool." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 7, no. 2 (2011): 21–24. http://dx.doi.org/10.1609/aiide.v7i2.12458.

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Text annotations are of great use to researchers in the language sciences, and much effort has been invested in creating annotated corpora for an wide variety of purposes. Unfortunately, software support for these corpora tends to be quite limited: it is usually ad-hoc, poorly designed and documented, or not released for public use. I describe an annotation tool, the Story Workbench, which provides a generic platform for text annotation. It is free, open-source, cross-platform, and user friendly. It provides a number of common text annotation operations, including representations (e.g., tokens, sentences, parts of speech), functions (e.g., generation of initial annotations by algorithm, checking annotation validity by rule, fully manual manipulation of annotations) and tools (e.g., distributing texts to annotators via version control, merging doubly-annotated texts into a single file). The tool is extensible at many different levels, admitting new representations, algorithm, and tools. I enumerate ten important features and illustrate how they support the annotation process at three levels: (1) annotation of individual texts by a single annotator, (2) double-annotation of texts by two annotators and an adjudicator, and (3) annotation scheme development. The Story Workbench is scheduled for public release in March 2012.
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Rasmussen, Christoffer Bøgelund, Kristian Kirk, and Thomas B. Moeslund. "The Challenge of Data Annotation in Deep Learning—A Case Study on Whole Plant Corn Silage." Sensors 22, no. 4 (2022): 1596. http://dx.doi.org/10.3390/s22041596.

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Recent advances in computer vision are primarily driven by the usage of deep learning, which is known to require large amounts of data, and creating datasets for this purpose is not a trivial task. Larger benchmark datasets often have detailed processes with multiple stages and users with different roles during annotation. However, this can be difficult to implement in smaller projects where resources can be limited. Therefore, in this work we present our processes for creating an image dataset for kernel fragmentation and stover overlengths in Whole Plant Corn Silage. This includes the guidelines for annotating object instances in respective classes and statistics of gathered annotations. Given the challenging image conditions, where objects are present in large amounts of occlusion and clutter, the datasets appear appropriate for training models. However, we experience annotator inconsistency, which can hamper evaluation. Based on this we argue the importance of having an evaluation form independent of the manual annotation where we evaluate our models with physically based sieving metrics. Additionally, instead of the traditional time-consuming manual annotation approach, we evaluate Semi-Supervised Learning as an alternative, showing competitive results while requiring fewer annotations. Specifically, given a relatively large supervised set of around 1400 images we can improve the Average Precision by a number of percentage points. Additionally, we show a significantly large improvement when using an extremely small set of just over 100 images, with over 3× in Average Precision and up to 20 percentage points when estimating the quality.
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Kors, Jan A., Simon Clematide, Saber A. Akhondi, Erik M. van Mulligen, and Dietrich Rebholz-Schuhmann. "A multilingual gold-standard corpus for biomedical concept recognition: the Mantra GSC." Journal of the American Medical Informatics Association 22, no. 5 (2015): 948–56. http://dx.doi.org/10.1093/jamia/ocv037.

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Abstract Objective To create a multilingual gold-standard corpus for biomedical concept recognition. Materials and methods We selected text units from different parallel corpora (Medline abstract titles, drug labels, biomedical patent claims) in English, French, German, Spanish, and Dutch. Three annotators per language independently annotated the biomedical concepts, based on a subset of the Unified Medical Language System and covering a wide range of semantic groups. To reduce the annotation workload, automatically generated preannotations were provided. Individual annotations were automatically harmonized and then adjudicated, and cross-language consistency checks were carried out to arrive at the final annotations. Results The number of final annotations was 5530. Inter-annotator agreement scores indicate good agreement (median F-score 0.79), and are similar to those between individual annotators and the gold standard. The automatically generated harmonized annotation set for each language performed equally well as the best annotator for that language. Discussion The use of automatic preannotations, harmonized annotations, and parallel corpora helped to keep the manual annotation efforts manageable. The inter-annotator agreement scores provide a reference standard for gauging the performance of automatic annotation techniques. Conclusion To our knowledge, this is the first gold-standard corpus for biomedical concept recognition in languages other than English. Other distinguishing features are the wide variety of semantic groups that are being covered, and the diversity of text genres that were annotated.
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Cronkite, David, Bradley Malin, John Aberdeen, Lynette Hirschman, and David Carrell. "Is the Juice Worth the Squeeze? Costs and Benefits of Multiple Human Annotators for Clinical Text De-identification." Methods of Information in Medicine 55, no. 04 (2016): 356–64. http://dx.doi.org/10.3414/me15-01-0122.

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SummaryBackground: Clinical text contains valuable information but must be de-identified before it can be used for secondary purposes. Accurate annotation of personally identifiable information (PII) is essential to the development of automated de-identification systems and to manual redaction of PII. Yet the accuracy of annotations may vary considerably across individual annotators and annotation is costly. As such, the marginal benefit of incorporating additional annotators has not been well characterized.Objectives: This study models the costs and benefits of incorporating increasing numbers of independent human annotators to identify the instances of PII in a corpus. We used a corpus with gold standard annotations to evaluate the performance of teams of annotators of increasing size.Methods: Four annotators independently identified PII in a 100-document corpus consisting of randomly selected clinical notes from Family Practice clinics in a large integrated health care system. These annotations were pooled and validated to generate a gold standard corpus for evaluation.Results: Recall rates for all PII types ranged from 0.90 to 0.98 for individual annotators to 0.998 to 1.0 for teams of three, when measured against the gold standard. Median cost per PII instance discovered during corpus annotation ranged from $ 0.71 for an individual annotator to $ 377 for annotations discovered only by a fourth annotator.Conclusions: Incorporating a second annotator into a PII annotation process reduces unredacted PII and improves the quality of annotations to 0.99 recall, yielding clear benefit at reasonable cost; the cost advantages of annotation teams larger than two diminish rapidly.
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Fuoli, Matteo. "A stepwise method for annotating appraisal." Functions of Language 25, no. 2 (2018): 229–58. http://dx.doi.org/10.1075/fol.15016.fuo.

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Abstract Despite a growing awareness of methodological issues, the literature on appraisal has not so far provided adequate answers to some of the key challenges involved in reliably identifying and classifying evaluative language expressions. This article presents a stepwise method for the manual annotation of appraisal in text that is designed to optimize reliability, replicability and transparency. The procedure consists of seven steps, from the creation of a context-specific annotation manual to the statistical analysis of the quantitative data derived from the manually-performed annotations. By presenting this method, the article pursues the twofold purpose of (i) providing a practical tool that can facilitate more reliable, replicable and transparent analyses, and (ii) fostering a discussion of the best practices that should be observed when manually annotating appraisal.
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Bayerl, Petra Saskia, and Karsten Ingmar Paul. "Identifying Sources of Disagreement: Generalizability Theory in Manual Annotation Studies." Computational Linguistics 33, no. 1 (2007): 3–8. http://dx.doi.org/10.1162/coli.2007.33.1.3.

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Many annotation projects have shown that the quality of manual annotations often is not as good as would be desirable for reliable data analysis. Identifying the main sources responsible for poor annotation quality must thus be a major concern. Generalizability theory is a valuable tool for this purpose, because it allows for the differentiation and detailed analysis of factors that influence annotation quality. In this article we will present basic concepts of Generalizability Theory and give an example for its application based on published data.
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Bayerl, Petra Saskia, and Karsten Ingmar Paul. "What Determines Inter-Coder Agreement in Manual Annotations? A Meta-Analytic Investigation." Computational Linguistics 37, no. 4 (2011): 699–725. http://dx.doi.org/10.1162/coli_a_00074.

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Recent discussions of annotator agreement have mostly centered around its calculation and interpretation, and the correct choice of indices. Although these discussions are important, they only consider the “back-end” of the story, namely, what to do once the data are collected. Just as important in our opinion is to know how agreement is reached in the first place and what factors influence coder agreement as part of the annotation process or setting, as this knowledge can provide concrete guidelines for the planning and set-up of annotation projects. To investigate whether there are factors that consistently impact annotator agreement we conducted a meta-analytic investigation of annotation studies reporting agreement percentages. Our meta-analysis synthesized factors reported in 96 annotation studies from three domains (word-sense disambiguation, prosodic transcriptions, and phonetic transcriptions) and was based on a total of 346 agreement indices. Our analysis identified seven factors that influence reported agreement values: annotation domain, number of categories in a coding scheme, number of annotators in a project, whether annotators received training, the intensity of annotator training, the annotation purpose, and the method used for the calculation of percentage agreements. Based on our results we develop practical recommendations for the assessment, interpretation, calculation, and reporting of coder agreement. We also briefly discuss theoretical implications for the concept of annotation quality.
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Salisbury, Alicia, and Philippos K. Tsourkas. "A Method for Improving the Accuracy and Efficiency of Bacteriophage Genome Annotation." International Journal of Molecular Sciences 20, no. 14 (2019): 3391. http://dx.doi.org/10.3390/ijms20143391.

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Bacteriophages are the most numerous entities on Earth. The number of sequenced phage genomes is approximately 8000 and increasing rapidly. Sequencing of a genome is followed by annotation, where genes, start codons, and functions are putatively identified. The mainstays of phage genome annotation are auto-annotation programs such as Glimmer and GeneMark. Due to the relatively small size of phage genomes, many groups choose to manually curate auto-annotation results to increase accuracy. An additional benefit of manual curation of auto-annotated phage genomes is that the process is amenable to be performed by students, and has been shown to improve student recruitment to the sciences. However, despite its greater accuracy and pedagogical value, manual curation suffers from high labor cost, lack of standardization and a degree of subjectivity in decision making, and susceptibility to mistakes. Here, we present a method developed in our lab that is designed to produce accurate annotations while reducing subjectivity and providing a degree of standardization in decision-making. We show that our method produces genome annotations more accurate than auto-annotation programs while retaining the pedagogical benefits of manual genome curation.
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Dissertations / Theses on the topic "Manual annotation"

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Burdett, Eric. "Reducing the Manual Annotation Effort for Handwriting Recognition Using Active Transfer Learning." BYU ScholarsArchive, 2021. https://scholarsarchive.byu.edu/etd/9258.

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Handwriting recognition systems have achieved remarkable performance over the past several years with the advent of deep neural networks. For high-quality recognition, these models require large amounts of labeled training data, which can be difficult to obtain. Various methods to reduce this effort have been proposed in the realms of active and transfer learning, but not in combination. We propose a framework for fitting new handwriting recognition models that joins active and transfer learning into a unified framework. Empirical results show the superiority of our method compared to traditional active learning, transfer learning, or standard supervised training schemes.
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Yáñez, del Valle José Maximiliano. "Manual annotation & text mining in a marketing service logic approach -ARC Framework-LATAM airlines case study research." Tesis, Universidad de Chile, 2014. http://www.repositorio.uchile.cl/handle/2250/117535.

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Tesis para optar al grado de Magíster en Marketing<br>El presente documento se basa en la aplicación de una nueva metodología, justificada dentro del marco teórico de Service Analytics y ARC. Esta metodología, consta de tres etapas: En primer lugar, un proceso de Anotación Manual, para analizar feedback escrito no estructurado de clientes. En segundo lugar un mapeo del proceso de servicios visto de la perspectiva de los clientes. Y finalmente, la construcción de un artefacto de Text Mining basado en los dos procesos anteriormente concretados, buscando automatizar el análisis de grandes masas de texto, proveniente de altas cantidades de comentarios de retroalimentación recibida de los clientes. En este documento, se trabaja esta metodología, aplicándola por primera vez en el idioma español, y en un dominio de servicios diferente a su predecesora original. Los objetivos de este trabajo, por tanto se pueden dividir en Impacto Académico e Impacto Organizacional, donde los primeros corresponden a realizar los ajustes pertinentes a las herramientas y definiciones actualmente existentes. Demostrando su capacidad de adaptación libre de dominio e idioma, entregando robustez y validación a la metodología. Los segundos corresponden a las aplicaciones prácticas de la metodología en base a la información provista por la organización involucrada. Generando un método eficiente y adaptado a sus operaciones de análisis de feedback de clientes, un boceto del servicio visto desde la perspectiva de sus clientes y finalmente un prototipo de artefacto de minería de texto. Todo esto, con la capacidad de construir sobre los mismos, herramientas y outputs de mayor complejidad y elaboración a futuro, lo cual sumado a los pocos casos de estudios existentes hasta el momento y la novedad de la metodología (iniciada el 2013 y con publicaciones recientes en 2014), les puede entregar una ventaja competitiva en la gestión del feedback de sus clientes respecto a otras organizaciones de la industria y mundo empresarial en general. La metodología utilizada para la investigación corresponde al Caso de Estudio, que en esta oportunidad contó con información provista por el Grupo LATAM Airlines, y su área de Contact Center; Junto al procedimiento de 5 Fases Iterativas de Takeda (Takeda, Veerkamp, & Yoshikawa, 1990). Los resultados logrados, considerando las limitaciones del estudio, se dividen por tanto en las tres fases del trabajo. En primer lugar, la conclusión clave de que es posible adaptar la metodología a otro idioma y dominio de servicios. Junto a esto, la entrega de un instructivo de anotación manual en español, una planilla propuesta para realizar en forma eficiente el procedimiento, y un set de observaciones relevantes para la metodología, como por ejemplo, la forma de tratar casos de Elementos Genéricos. En segundo lugar, el output del mapeo de servicios de la organización, con sus 4 grandes procesos de servicios y todos sus elementos pertenecientes al marco ARC. Por último, el primer prototipo del artefacto de Text Mining, lo cual puede ser el principio de una construcción avanzada por parte de la empresa.
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Schulder, Marc [Verfasser], and Dietrich [Akademischer Betreuer] Klakow. "Sentiment polarity shifters : creating lexical resources through manual annotation and bootstrapped machine learning / Marc Schulder ; Betreuer: Dietrich Klakow." Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2019. http://d-nb.info/1199932906/34.

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Blank, Clas. "Automatic vs. Manual Data Labeling : A System Dynamics Modeling Approach." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279572.

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Labeled data, which is a collection of data samples that have been tagged with one or more labels, play an important role many software organizations in today's market. It can help in solving automation problems, training and validating machine learning models, or analysing data. Many organizations therefore set up their own labeled data gathering system which supplies them with the data they require. Labeling data can either be done by humans or be done via some automated process. However, labeling datasets comes with costs to these organizations. This study will examine what this labeled data gathering system could look like and determine which components that play a crucial role when determining how costly an automatic approach is compared to a manual approach using the company Klarna's label acquisition system as a case study. Two models are presented where one describes a system that solely uses humans for data annotation, while the other model describes a system where labeling is done via an automatic process. These models are used to compare costs to an organization taking those approaches. Important findings include the identification of important components that affects which approach would be more economically efficient to an organization under certain circumstances. Some of these important components are the label decay rate, automatic and manual expected accuracy, and number of data points that require labeling.<br>Annoterad data, vilket är en kollektion utav datapunkter som har blivit annoterade med en eller flera taggar, spelar en viktig roll för många mjukvaruföretag i dagens marknad. Det kan hjälpa till att lösa automatiseringsingsproblem, träna och validera maskininlärningsmodeller, eller analysera data. Många organisationer sätter därför upp sina egna dataannoteringssystem som kan leverera den annoterade data som behövs inom organisationen. Annotering kan göras av människor, men kan också göras via en automatiserad process. Emellertid kommer annotering utav data med kostnader för organisationen. Denna studie undersöker hur ett sådant dataannoteringssystem kan se ut och analyserar vilka komponenter som spelar en betydande roll när kostnader mellan ett automatiserat system och ett manuellt system ska jämföras. Klarnas dataannoteringssystem kommer att användas som en case-studie. Två modeller presenteras varav den ena beskriver ett system där enbart manuellt annoteringsarbete utförs, och den andra beskriver ett system där annotering utav data utförs via en automatisk process. Några viktiga resultat av denna studie är identifikationen utav betydelsefulla parametrar i modellerna när det kommer till att jämföra den ekonomiska effektiviteten mellan de två olika dataannoteringsstrategierna. Exempel på dessa komponenter är annoteringens förfalltakt, den förväntade manuella/automatiska pricksäkerheten, och mängden data som behöver annoteras.
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Wamalwa, Mark. "Development of a comprehensive annotation and curation framework for analysis of Glossina Morsitans Morsitans expresses sequence tags." Thesis, University of the Western Cape, 2011. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_5497_1325767222.

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This study has successfully identified transcripts differentially expressed in the salivary gland and midgut and provides candidate genes that are critical to response to parasite invasion. Furthermore, an open-source Glossina resource (G-ESTMAP) was developed that provides interactive features and browsing of functional genomics data for researchers working in the field of Trypanosomiasis on the African continent.
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ALZETTA, CHIARA. "From Texts to Prerequisites. Identifying and Annotating Propaedeutic Relations in Educational Textual Resources." Doctoral thesis, Università degli studi di Genova, 2021. http://hdl.handle.net/11567/1050378.

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Prerequisite Relations (PRs) are dependency relations established between two distinct concepts expressing which piece(s) of information a student has to learn first in order to understand a certain target concept. Such relations are one of the most fundamental in Education, playing a crucial role not only for what concerns new knowledge acquisition, but also in the novel applications of Artificial Intelligence to distant and e-learning. Indeed, resources annotated with such information could be used to develop automatic systems able to acquire and organize the knowledge embodied in educational resources, possibly fostering educational applications personalized, e.g., on students' needs and prior knowledge. The present thesis discusses the issues and challenges of identifying PRs in educational textual materials with the purpose of building a shared understanding of the relation among the research community. To this aim, we present a methodology for dealing with prerequisite relations as established in educational textual resources which aims at providing a systematic approach for uncovering PRs in textual materials, both when manually annotating and automatically extracting the PRs. The fundamental principles of our methodology guided the development of a novel framework for PR identification which comprises three components, each tackling a different task: (i) an annotation protocol (PREAP), reporting the set of guidelines and recommendations for building PR-annotated resources; (ii) an annotation tool (PRET), supporting the creation of manually annotated datasets reflecting the principles of PREAP; (iii) an automatic PR learning method based on machine learning (PREL). The main novelty of our methodology and framework lies in the fact that we propose to uncover PRs from textual resources relying solely on the content of the instructional material: differently from other works, rather than creating de-contextualised PRs, we acknowledge the presence of a PR between two concepts only if emerging from the way they are presented in the text. By doing so, we anchor relations to the text while modelling the knowledge structure entailed in the resource. As an original contribution of this work, we explore whether linguistic complexity of the text influences the task of manual identification of PRs. To this aim, we investigate the interplay between text and content in educational texts through a crowd-sourcing experiment on concept sequencing. Our methodology values the content of educational materials as it incorporates the evidence acquired from such investigation which suggests that PR recognition is highly influenced by the way in which concepts are introduced in the resource and by the complexity of the texts. The thesis reports a case study dealing with every component of the PR framework which produced a novel manually-labelled PR-annotated dataset.
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Doersch, Carl. "Supervision Beyond Manual Annotations for Learning Visual Representations." Research Showcase @ CMU, 2016. http://repository.cmu.edu/dissertations/787.

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For both humans and machines, understanding the visual world requires relating new percepts with past experience. We argue that a good visual representation for an image should encode what makes it similar to other images, enabling the recall of associated experiences. Current machine implementations of visual representations can capture some aspects of similarity, but fall far short of human ability overall. Even if one explicitly labels objects in millions of images to tell the computer what should be considered similar—a very expensive procedure—the labels still do not capture everything that might be relevant. This thesis shows that one can often train a representation which captures similarity beyond what is labeled in a given dataset. That means we can begin with a dataset that has uninteresting labels, or no labels at all, and still build a useful representation. To do this, we propose to using pretext tasks: tasks that are not useful in and of themselves, but serve as an excuse to learn a more general-purpose representation. The labels for a pretext task can be inexpensive or even free. Furthermore, since this approach assumes training labels differ from the desired outputs, it can handle output spaces where the correct answer is ambiguous, and therefore impossible to annotate by hand. The thesis explores two broad classes of supervision. The first isweak image-level supervision, which is exploited to train mid-level discriminative patch classifiers. For example, given a dataset of street-level imagery labeled only with GPS coordinates, patch classifiers are trained to differentiate one specific geographical region (e.g. the city of Paris) from others. The resulting classifiers each automatically collect and associate a set of patches which all depict the same distinctive architectural element. In this way, we can learn to detect elements like balconies, signs, and lamps without annotations. The second type of supervision requires no information about images other than the pixels themselves. Instead, the algorithm is trained to predict the context around image patches. The context serves as a sort of weak label: to predict well, the algorithm must associate similar-looking patches which also have similar contexts. After training, the feature representation learned using this within-image context indeed captures visual similarity across images, which ultimately makes it useful for real tasks like object detection and geometry estimation.
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Burghardt, Manuel [Verfasser], and Christian [Akademischer Betreuer] Wolff. "Engineering annotation usability - Toward usability patterns for linguistic annotation tools / Manuel Burghardt. Betreuer: Christian Wolff." Regensburg : Universitätsbibliothek Regensburg, 2014. http://d-nb.info/1059004674/34.

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Millour, Alice. "Myriadisation de ressources linguistiques pour le traitement automatique de langues non standardisées." Thesis, Sorbonne université, 2020. http://www.theses.fr/2020SORUL126.

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Les sciences participatives, et en particulier la myriadisation (crowdsourcing) bénévole, représentent un moyen peu exploité de créer des ressources langagières pour certaines langues encore peu dotées, et ce malgré la présence de locuteurs sur le Web. Nous présentons dans ce travail les expériences que nous avons menées pour permettre la myriadisation de ressources langagières dans le cadre du développement d'un outil d'annotation automatique en parties du discours. Nous avons appliqué cette méthodologie à trois langues non standardisées, en l'occurrence l'alsacien, le créole guadeloupéen et le créole mauricien. Pour des raisons historiques différentes, de multiples pratiques (ortho)graphiques co-existent en effet pour ces trois langues. Les difficultés posées par l'existence de cette variation nous ont menée à proposer diverses tâches de myriadisation permettant la collecte de corpus bruts, d’annotations en parties du discours, et de variantes graphiques.L'analyse intrinsèque et extrinsèque de ces ressources, utilisées pour le développement d'outils d'annotation automatique, montrent l'intérêt d'utiliser la myriadisation dans un cadre linguistique non standardisé : les locuteurs ne sont pas ici considérés comme un ensemble uniforme de contributeurs dont les efforts cumulés permettent d'achever une tâche particulière, mais comme un ensemble de détenteurs de connaissances complémentaires. Les ressources qu'ils produisent collectivement permettent de développer des outils plus robustes à la variation rencontrée.Les plateformes développées, les ressources langagières, ainsi que les modèles de taggers entraînés sont librement disponibles<br>Citizen science, in particular voluntary crowdsourcing, represents a little experimented solution to produce language resources for some languages which are still little resourced despite the presence of sufficient speakers online. We present in this work the experiments we have led to enable the crowdsourcing of linguistic resources for the development of automatic part-of-speech annotation tools. We have applied the methodology to three non-standardised languages, namely Alsatian, Guadeloupean Creole and Mauritian Creole. For different historical reasons, multiple (ortho)-graphic practices coexist for these three languages. The difficulties encountered by the presence of this variation phenomenon led us to propose various crowdsourcing tasks that allow the collection of raw corpora, part-of-speech annotations, and graphic variants. The intrinsic and extrinsic analysis of these resources, used for the development of automatic annotation tools, show the interest of using crowdsourcing in a non-standardized linguistic framework: the participants are not seen in this context a uniform set of contributors whose cumulative efforts allow the completion of a particular task, but rather as a set of holders of complementary knowledge. The resources they collectively produce make possible the development of tools that embrace the variation.The platforms developed, the language resources, as well as the models of trained taggers are freely available
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Marchesini, Giulia <1992&gt. "Annotating Patrick White’s "The Solid Mandala" with Deep Features to Unravel Stylistic Devices." Master's Degree Thesis, Università Ca' Foscari Venezia, 2016. http://hdl.handle.net/10579/9209.

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Nobel Prize winner Patrick White (1912-1990) is considered to be one of the greatest and most influential writers of the 20th century, not only in Australia, his country, but in the rest of the world, as well. His innovative, multi-faceted and complex prose caught the interest of the critics and of many other writers, who in some cases strove to follow on his steps. Interpreting and decoding White’s works was always a challenge, however, considering the intricacy of this author’s style and the multiple levels he used to build his stories, and especially the novels. To shed more light on this debated topic, Gordon Collier examined in detail the stylistic features of The Solid Mandala (1966), one of White’s most famous and important novels, in his The Rocks and Sticks of Words (1992). His theories are fundamental to this master thesis, which aims to continue on the same path, trying to use quantitative and qualitative methods of analysis to better understand the role of the most important stylistic features in White’s style, as well as the use of stylistic devices in general. The dissertation is made of four chapters dealing with complementary aspects of this research. The first is dedicated to the presentation of Patrick White as a national and international author, of his novels – The Solid Mandala in particular – and of the reaction of the critics to his most important works. It also functions as a first approach to the complexity of this kind of style and to the difficulties of finding a comprehensive definition for it. The second introduces Collier’s approach to the stylistic analysis and the most relevant points of his theories, using them as a starting point to set hypotheses for the subsequent original stages of the study. White’s narrative is here proven as psychological, using specific devices in the style to mirror the character’s emotions and mental processes. In order to take the analysis to the text more in depth, these theories were used to build a tagging system to annotate the whole novel. The criteria of this annotation are based on an XML standard tagging system and follow Collier’s take on the stylistic features, aiming to confirm his findings, to detect possible anomalies, and most importantly to elaborate a comprehensive theory on the new data. The third chapter explains in detail this process of annotation, from the subdivision of the text in narremes to the reasoning behind each tag, attribute and value. The fourth and final chapter uses the data collected through the annotation to build a quantitative analysis, combining stylistic, narratological and linguistic features with statistical information, tables and diagrams. The purpose of the research has two directions. In a more general way, its main goal is to establish parameters for the annotation of stylistic features in a novel. The tagging system used for The Solid Mandala is of course specific to Patrick White’s style and to the peculiarities of his prose, but it can be easily adapted to other novels and authors, if needed. Furthermore, the data extracted from The Solid Mandala alone are in themselves sufficient for many different approaches to the novel and the author, leaving a number of broader perspectives to be explored. In a more specific way, this particular approach to the research selected semantic categories and chose to investigate the novel using as references the four sections, the three main characters, and the narremes of the reconstructed fabula as markers of events. With these starting parameters it was possible to give a specific reading of the statistics, which is only one of many, but perhaps the most interesting for a comprehensive view of the novel.
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Books on the topic "Manual annotation"

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translator, Ch'oe Tŏk-kyŏng, ed. Ponongsŏ yŏkchu: A translated annotation of the agricultural manual "Bonongseo". Sech'ang Ch'ulp'ansa, 2013.

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Tŏk-kyŏng, Ch'oe, and China Si nong si, eds. Nongsang chibyo yŏkchu: A translated annotation of the agricultural manual "Nongsang chibyo". Sech'ang Ch'ulp'ansa, 2012.

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1963-, Dickerson Darby, and Association of Legal Writing Directors., eds. ALWD citation manual: A professional system of citation. 4th ed. Aspen Publishers, 2010.

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McGaugh, Tracy L. Interactive citation workbook for ALWD citation manual. 2nd ed. LexisNexis, 2008.

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(State), Washington. 1993 port district manual: Port district laws and annotations. Book Pub. Co., 1993.

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Association, Texas Law Review, ed. Manual on usage & style. Texas Law Review Association, 2005.

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Dickerson, Darby. ALWD citation manual: A professional system of citation. 4th ed. Aspen Publishers, 2010.

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Hughes, Kathleen B., and William J. Hooks. New York law reports style manual. 2nd ed. West, 2012.

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New York (State). Law Reporting Bureau. New York law reports style manual. West Group, 2002.

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LaBoda, Katherine D., and Gary D. Spivey. New York law reports style manual. 2nd ed. Thomson/West, 2007.

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Book chapters on the topic "Manual annotation"

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Dingli, Alexiei. "Manual Annotation." In Intelligent Systems Reference Library. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20323-7_4.

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Bureeva, Svetlana, Svetlana Zvereva, Valentin Romanov, and Tatiana Serebryiskaya. "Manual Annotation of Protein Interactions." In Methods in Molecular Biology. Humana Press, 2009. http://dx.doi.org/10.1007/978-1-60761-175-2_5.

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Şakar, Ömer, Mohsen Safari, Marieke Huisman, and Anton Wijs. "Alpinist: An Annotation-Aware GPU Program Optimizer." In Tools and Algorithms for the Construction and Analysis of Systems. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99527-0_18.

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AbstractGPU programs are widely used in industry. To obtain the best performance, a typical development process involves the manual or semi-automatic application of optimizations prior to compiling the code. To avoid the introduction of errors, we can augment GPU programs with (pre- and postcondition-style) annotations to capture functional properties. However, keeping these annotations correct when optimizing GPU programs is labor-intensive and error-prone.This paper introduces Alpinist, an annotation-aware GPU program optimizer. It applies frequently-used GPU optimizations, but besides transforming code, it also transforms the annotations. We evaluate Alpinist, in combination with the VerCors program verifier, to automatically optimize a collection of verified programs and reverify them.
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McDonnell, Erin, Kimchi Strasser, and Adrian Tsang. "Manual Gene Curation and Functional Annotation." In Methods in Molecular Biology. Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7804-5_16.

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Zhang, Ziqi, Sam Chapman, and Fabio Ciravegna. "A Methodology towards Effective and Efficient Manual Document Annotation: Addressing Annotator Discrepancy and Annotation Quality." In Knowledge Engineering and Management by the Masses. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16438-5_21.

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Yue, Wang. "Application of Directed Recommendation in Text Manual Annotation." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-25128-4_190.

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Sohl, Jessica, and Heike Zinsmeister. "Exploring Ensemble Dependency Parsing to Reduce Manual Annotation Workload." In Lecture Notes in Computer Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73706-5_4.

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Poux, Sylvain, and Pascale Gaudet. "Best Practices in Manual Annotation with the Gene Ontology." In Methods in Molecular Biology. Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-3743-1_4.

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Jelínek, Tomáš, Barbora Štindlová, Alexandr Rosen, and Jirka Hana. "Combining Manual and Automatic Annotation of a Learner Corpus." In Text, Speech and Dialogue. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32790-2_15.

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Hinze, Annika, Ralf Heese, Markus Luczak-Rösch, and Adrian Paschke. "Semantic Enrichment by Non-experts: Usability of Manual Annotation Tools." In The Semantic Web – ISWC 2012. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35176-1_11.

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Conference papers on the topic "Manual annotation"

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Duffield, Cecily Jill, Jena D. Hwang, Susan Windisch Brown, et al. "Criteria for the manual grouping of verb senses." In the Linguistic Annotation Workshop. Association for Computational Linguistics, 2007. http://dx.doi.org/10.3115/1642059.1642067.

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Meyers, Adam, Michiko Kosaka, Heng Ji, et al. "Transducing logical relations from automatic and manual GLARF." In the Third Linguistic Annotation Workshop. Association for Computational Linguistics, 2009. http://dx.doi.org/10.3115/1698381.1698400.

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Amorim, Marcello N., Celso A. S. Santos, and Orivaldo L. Tavares. "Integrating Crowdsourcing and Human Computation for Complex Video Annotation Tasks." In Simpósio Brasileiro de Sistemas Multimídia e Web. Sociedade Brasileira de Computação, 2020. http://dx.doi.org/10.5753/webmedia_estendido.2020.13053.

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Video annotation is an activity that aims to supplement this type of multimedia object with additional content or information about its context, nature, content, quality and other aspects. These annotations are the basis for building a variety of multimedia applications for various purposes ranging from entertainment to security. Manual annotation is a strategy that uses the intelligence and workforce of people in the annotation process and is an alternative to cases where automatic methods cannot be applied. However, manual video annotation can be a costly process because as the content to be annotated increases, so does the workload for annotating. Crowdsourcing appears as a viable solution strategy in this con- text because it relies on outsourcing the tasks to a multitude of workers, who perform specific parts of the work in a distributed way. However, as the complexity of required media annoyances increases, it becomes necessary to employ skilled labor, or willing to perform larger, more complicated, and more time-consuming tasks. This makes it challenging to use crowdsourcing, as experts demand higher pay, and recruiting tends to be a difficult activity. In order to overcome this problem, strategies based on the decom- position of the main problem into a set of simpler subtasks suitable for crowdsourcing processes have emerged. These smaller tasks are organized in a workflow so that the execution process can be formalized and controlled. In this sense, this thesis aims to present a new framework that allows the use of crowdsourcing to create applications that require complex video annotation tasks. The developed framework considers the whole process from the definition of the problem and the decomposition of the tasks, until the construction, execution, and management of the workflow. This framework, called CrowdWaterfall, contemplates the strengths of current proposals, incorporating new concepts, techniques, and resources to overcome some of its limitations.
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Rodrigues, Felipe, Richard Semolini, Norton Trevisan Roman, and Ana Maria Monteiro. "TSeg – A Text Segmenter for Corpus Annotation." In VIII Simpósio Brasileiro de Sistemas de Informação. Sociedade Brasileira de Computação, 2012. http://dx.doi.org/10.5753/sbsi.2012.14419.

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This paper describes TSeg – a Java application that allows for both manual and automatic segmentation of a source text into basic units of annotation. TSeg provides a straightforward way to approach this task through a clear point-and-click interface. Once finished the text segmentation, the application outputs an XML file that may be used as input to a more problem specific annotation software. Hence, TSeg moves the identification of basic units of annotation out of the task of annotating these units, making it possible for both problems to be analysed in isolation, thereby reducing the cognitive load on the user and preventing potential damages to the overall outcome of the annotation process.
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Somasundaran, Swapna, Janyce Wiebe, Paul Hoffmann, and Diane Litman. "Manual annotation of opinion categories in meetings." In the Workshop. Association for Computational Linguistics, 2006. http://dx.doi.org/10.3115/1641991.1641998.

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Navarro-Galindo, José L., and José Samos. "Manual and automatic semantic annotation of web documents." In the 12th International Conference. ACM Press, 2010. http://dx.doi.org/10.1145/1967486.1967570.

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Startsev, Mikhail, Ioannis Agtzidis, and Michael Dorr. "Deep learning vs. manual annotation of eye movements." In ETRA '18: 2018 Symposium on Eye Tracking Research and Applications. ACM, 2018. http://dx.doi.org/10.1145/3204493.3208346.

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Hula, Jan, David Mojzisek, David Adamczyk, and Radek Cech. "Acquiring Custom OCR System with Minimal Manual Annotation." In 2020 IEEE Third International Conference on Data Stream Mining & Processing (DSMP). IEEE, 2020. http://dx.doi.org/10.1109/dsmp47368.2020.9204229.

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Ludusan, Bogdan, and Petra Wagner. "An Evaluation of Manual and Semi-Automatic Laughter Annotation." In Interspeech 2020. ISCA, 2020. http://dx.doi.org/10.21437/interspeech.2020-2521.

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Trani, Salvatore, Diego Ceccarelli, Claudio Lucchese, Salvatore Orlando, and Raffaele Perego. "Manual Annotation of Semi-Structured Documents for Entity-Linking." In CIKM '14: 2014 ACM Conference on Information and Knowledge Management. ACM, 2014. http://dx.doi.org/10.1145/2661829.2661854.

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