Academic literature on the topic 'Annotation via web'

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Journal articles on the topic "Annotation via web"

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Islamaj, Rezarta, Dongseop Kwon, Sun Kim, and Zhiyong Lu. "TeamTat: a collaborative text annotation tool." Nucleic Acids Research 48, W1 (2020): W5—W11. http://dx.doi.org/10.1093/nar/gkaa333.

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Abstract Manually annotated data is key to developing text-mining and information-extraction algorithms. However, human annotation requires considerable time, effort and expertise. Given the rapid growth of biomedical literature, it is paramount to build tools that facilitate speed and maintain expert quality. While existing text annotation tools may provide user-friendly interfaces to domain experts, limited support is available for figure display, project management, and multi-user team annotation. In response, we developed TeamTat (https://www.teamtat.org), a web-based annotation tool (loca
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Mazhoud, Omar, Anis Kalboussi, and Ahmed Hadj Kacem. "Educational Recommender System based on Learner’s Annotative Activity." International Journal of Emerging Technologies in Learning (iJET) 16, no. 10 (2021): 108. http://dx.doi.org/10.3991/ijet.v16i10.19955.

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In recent years, Educational Recommender Systems (ERSs) have attracted great attention as a solution towards addressing the problem of information overload in e-learning environments and providing relevant recommendations to online learners. These systems play a key role in helping learners to find educational resources relevant and pertinent to their profiles and context. So, it is necessary to identify information that helps learner’s profile definition and in identifying requests and interests. In this context, we suggest to take advantage of the annotation activity used usually in the lear
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Wang, Han, Xinxiao Wu, and Yunde Jia. "Video Annotation via Image Groups from the Web." IEEE Transactions on Multimedia 16, no. 5 (2014): 1282–91. http://dx.doi.org/10.1109/tmm.2014.2312251.

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Tschöpe, Okka, Lutz Suhrbier, Anton Güntsch, and Walter Berendsohn. "AnnoSys – an online tool for sharing annotations to enhance data quality." Biodiversity Information Science and Standards 1 (August 15, 2017): e20315. https://doi.org/10.3897/tdwgproceedings.1.20315.

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AnnoSys is a web-based open-source information system that enables users to correct and enrich specimen data published in data portals, thus enhancing data quality and documenting research developments over time. This brings the traditional annotation workflows for specimens to the Internet, as annotations become visible to researchers who subsequently observe the annotated specimen. During its first phase, the AnnoSys project developed a fully functional prototype of an annotation data repository for complex and cross-linked XML-standardized data in the ABCD (Access to biological collection d
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Ma, Zhigang, Feiping Nie, Yi Yang, Jasper R. R. Uijlings, and Nicu Sebe. "Web Image Annotation Via Subspace-Sparsity Collaborated Feature Selection." IEEE Transactions on Multimedia 14, no. 4 (2012): 1021–30. http://dx.doi.org/10.1109/tmm.2012.2187179.

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Wei, Chih-Hsuan, Alexis Allot, Robert Leaman, and Zhiyong Lu. "PubTator central: automated concept annotation for biomedical full text articles." Nucleic Acids Research 47, W1 (2019): W587—W593. http://dx.doi.org/10.1093/nar/gkz389.

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AbstractPubTator Central (https://www.ncbi.nlm.nih.gov/research/pubtator/) is a web service for viewing and retrieving bioconcept annotations in full text biomedical articles. PubTator Central (PTC) provides automated annotations from state-of-the-art text mining systems for genes/proteins, genetic variants, diseases, chemicals, species and cell lines, all available for immediate download. PTC annotates PubMed (29 million abstracts) and the PMC Text Mining subset (3 million full text articles). The new PTC web interface allows users to build full text document collections and visualize concept
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Lelong, Sebastien, Xinghua Zhou, Cyrus Afrasiabi, et al. "BioThings SDK: a toolkit for building high-performance data APIs in biomedical research." Bioinformatics 38, no. 7 (2022): 2077–79. http://dx.doi.org/10.1093/bioinformatics/btac017.

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Abstract Summary To meet the increased need of making biomedical resources more accessible and reusable, Web Application Programming Interfaces (APIs) or web services have become a common way to disseminate knowledge sources. The BioThings APIs are a collection of high-performance, scalable, annotation as a service APIs that automate the integration of biological annotations from disparate data sources. This collection of APIs currently includes MyGene.info, MyVariant.info and MyChem.info for integrating annotations on genes, variants and chemical compounds, respectively. These APIs are used b
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Park, Yeon-Ji, Min-a. Lee, Geun-Je Yang, Soo Jun Park, and Chae-Bong Sohn. "Biomedical Text NER Tagging Tool with Web Interface for Generating BERT-Based Fine-Tuning Dataset." Applied Sciences 12, no. 23 (2022): 12012. http://dx.doi.org/10.3390/app122312012.

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In this paper, a tagging tool is developed to streamline the process of locating tags for each term and manually selecting the target term. It directly extracts the terms to be tagged from sentences and displays it to the user. It also increases tagging efficiency by allowing users to reflect candidate categories in untagged terms. It is based on annotations automatically generated using machine learning. Subsequently, this architecture is fine-tuned using Bidirectional Encoder Representations from Transformers (BERT) to enable the tagging of terms that cannot be captured using Named-Entity Re
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Hu, Mengqiu, Yang Yang, Fumin Shen, Luming Zhang, Heng Tao Shen, and Xuelong Li. "Robust Web Image Annotation via Exploring Multi-Facet and Structural Knowledge." IEEE Transactions on Image Processing 26, no. 10 (2017): 4871–84. http://dx.doi.org/10.1109/tip.2017.2717185.

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Wang, Han, Xiabi Liu, Xinxiao Wu, and Yunde Jia. "Cross-domain structural model for video event annotation via web images." Multimedia Tools and Applications 74, no. 23 (2014): 10439–56. http://dx.doi.org/10.1007/s11042-014-2175-z.

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Dissertations / Theses on the topic "Annotation via web"

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Mitran, Mădălina. "Annotation d'images via leur contexte spatio-temporel et les métadonnées du Web." Toulouse 3, 2014. http://thesesups.ups-tlse.fr/2399/.

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En Recherche d'Information (RI), les documents sont classiquement indexés en fonction de leur contenu, qu'il soit textuel ou multimédia. Les moteurs de recherche s'appuyant sur ces index sont aujourd'hui des outils performants, répandus et indispensables. Ils visent à fournir des réponses pertinentes selon le besoin de l'utilisateur, sous forme de textes, images, sons, vidéos, etc. Nos travaux de thèse s'inscrivent dans le contexte des documents de type image. Plus précisément, nous nous sommes intéressés aux systèmes d'annotation automatique d'images qui permettent d'associer automatiquement
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Bedoya, Ramos Daniel. "Capturing Musical Prosody Through Interactive Audio/Visual Annotations." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS698.

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Des projets de science participative (SP) ont stimulé la recherche dans plusieurs disciplines au cours des dernières années. Des citoyens scientifiques contribuent à cette recherche en effectuant des tâches cognitives, favorisant l'apprentissage, l'innovation et l'inclusion. Bien que le crowdsourcing ait servi à recueillir des annotations structurelles en musique, la SP reste sous-utilisée pour étudier l'expressivité musicale. On introduit un nouveau protocole d'annotation pour capturer la prosodie musicale, associée aux variations acoustiques introduites par les interprètes pour rendre la mus
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Wang, Sheng-Ren, and 王聖仁. "Web-based Summary Writing Learning Environment via the Model of Integrating Concept Mapping and Sharing Annotation." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/16309342212500880796.

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碩士<br>國立臺北教育大學<br>教育傳播與科技研究所<br>94<br>In order to solve the difficulties of learners’ summary writing in web-based learning environment, the present study brings up a web-based summary writing model integrating concept mapping, annotation, and CSCL(computer support collaborative learning). Summary writing is beneficial for learners’ reading comprehension, recall, and recognizing the text’s main idea, but it’s still difficult for some learners. Take the judgment of importance for example. When reading a longer or more complicated text, many learners always couldn’t determine what should be dele
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Books on the topic "Annotation via web"

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Anne of Green Gables a Young Adult Novel an Annotation. Independently Published, 2022.

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Montgomery, L. M. Anne of Green Gables : Spécial Annotations by: Le Papillon Bleu. Independently Published, 2020.

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Anne of Green Gables: Englische Lektüre mit Audio-CD für das 1. und 2. Lernjahr. Illustrierte Lektüre mit Annotationen und Zusatztexten. Klett Sprachen GmbH, 2015.

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Book chapters on the topic "Annotation via web"

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Xu, Hongtao, Xiangdong Zhou, Lan Lin, Yu Xiang, and Baile Shi. "Automatic Web Image Annotation via Web-Scale Image Semantic Space Learning." In Advances in Data and Web Management. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00672-2_20.

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De Virgilio, Roberto, and Lorenzo Dolfi. "Web Navigation via Semantic Annotations." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33999-8_41.

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Collmer, C. W., M. Lindeberg, and Alan Collmer. "Gene Ontology (GO) for Microbe–Host Interactions and Its Use in Ongoing Annotation of Three Pseudomonas syringae Genomes via the Pseudomonas–Plant Interaction (PPI) Web Site." In Pseudomonas syringae Pathovars and Related Pathogens – Identification, Epidemiology and Genomics. Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6901-7_23.

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Fiaidhi, Jinan, Sabah Mohammed, and Yuan Wei. "Implications of Web 2.0 Technology on Healthcare." In Healthcare and the Effect of Technology. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-61520-733-6.ch016.

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Now that the health and medical sector is slowly but surely beginning to embrace Web 2.0 technologies and tactics such as social networking, blogging, and sharing health information, such usage may become an everyday occurrence. This new trend is emerging under the Health 2.0 umbrella where it has important effects on the future of medicine. This chapter introduces some important Health 2.0 concepts and discusses their advantages for health care and medical practice. In addition, this chapter provides a case study for building a Semantic Blog for Gene Annotation and Searching (GAS) among socia
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Hoyle David C., Delderfield Mark, Kitching Lee, Smith Gareth, and Buchan Iain. "Shared Genomics: High Performance Computing for distributed insights in genomic medical research." In Studies in Health Technology and Informatics. IOS Press, 2009. https://doi.org/10.3233/978-1-60750-027-8-232.

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The study of the genetics of diseases is entering a new era. Increasingly, genome-wide association studies are being used to identify positions within the human genome that have a link with a disease condition. The number of genomic locations studied means that High Performance Computing (HPC) solutions will have to increasingly be used in the statistical analysis of these data sets. Understanding the biomedical implications of the statistical analysis will also require heavy use of bioinformatics annotation tools. In this paper we report the outcome of developing HPC statistical genetics anal
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Sabou Marta, Maleshkova Maria, and Pan Jeff Z. "Semantically Enabling Web Service Repositories." In Studies on the Semantic Web. IOS Press, 2014. https://doi.org/10.3233/978-1-61499-370-4-139.

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The success of the Web service technology has brought topics such as software reuse and discovery once again on the agenda of software engineers. While there are several efforts towards automating Web service discovery and composition, many developers still search for services via online Web service repositories and then combine them manually. However, from our analysis of these repositories, it yields that, unlike traditional software libraries, they rely on little metadata to support service discovery. We believe that the major cause is the difficulty of automatically deriving metadata that
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Yang, Yuzhou, Yangming Zhou, Qichao Ying, Zhenxing Qian, and Xinpeng Zhang. "Search, Examine and Early-Termination: Fake News Detection with Annotation-Free Evidences." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2024. http://dx.doi.org/10.3233/faia240649.

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Pioneer researches recognize evidences as crucial elements in fake news detection apart from patterns. Existing evidence-aware methods either require laborious pre-processing procedures to assure relevant and high-quality evidence data, or incorporate the entire spectrum of available evidences in all news cases, regardless of the quality and quantity of the retrieved data. In this paper, we propose an approach named SEE that retrieves useful information from web-searched annotation-free evidences with an early-termination mechanism. The proposed SEE is constructed by three main phases: Searchi
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Ghali Fawaz and Cristea Alexandra I. "MOT 2.0: A Case Study on the Usefuleness of Social Modeling for Personalized E-Learning Systems." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2009. https://doi.org/10.3233/978-1-60750-028-5-333.

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In this paper, we report on our findings from the first evaluation of MOT 2.0, an Adaptive Web 2.0 e-learning tool, which supports: 1) collaborative authoring (i.e. editing content of other users, describing content using tags, rating, commenting on the content, etc); 2) authoring for collaboration (i.e., adding author activities, such as defining groups of authors, subscribing to other authors, communication between authors, etc); 3) group-based adaptive authoring via group-based privileges; 4) social annotation i.e., tagging, rating, and feedback on the content via group-based privileges; 5)
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Santos Cristiana, Pruski Cédric, Da Silveira Marcos, et al. "Complaint Ontology Pattern &ndash; COP." In Studies on the Semantic Web. IOS Press, 2017. https://doi.org/10.3233/978-1-61499-826-6-69.

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In this chapter we present an ontology design pattern to conceptualize complaints, an important concept still uncovered by ODPs. The proposed Complaint Ontology Pattern (COP) has been designed based on the analysis of free text complaints from available complaint datasets (banking, air transport, automobile), among other knowledge sources. We present a detailed use-case from consumer disputes. We evaluate the pattern by annotating the complaints from our use case and by discussing how COP aligns to existing ontologies. Knowledge engineers can further model complaints for specific domains and p
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Brahmia, Zouhaier, Fabio Grandi, Barbara Oliboni, and Rafik Bouaziz. "Supporting Structural Evolution of Data in Web-Based Systems via Schema Versioning in the tXSchema Framework." In Advances in Computer and Electrical Engineering. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-5384-7.ch013.

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τXSchema is a framework for creating and validating temporal XML documents, while using a temporal schema that consists of three components: a conventional XML schema document annotated with a set of temporal logical and physical annotations. Each one of these components can evolve over time to reflect changes in the real world. In addition, schema versioning has been long advocated to be the most efficient way to keep track of both data and schema evolution. Hence, in this chapter the authors complete τXSchema, which is predisposed from the origin to support schema versioning, by defining the
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Conference papers on the topic "Annotation via web"

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Braylan, Alexander, and Matthew Lease. "Modeling and Aggregation of Complex Annotations via Annotation Distances." In WWW '20: The Web Conference 2020. ACM, 2020. http://dx.doi.org/10.1145/3366423.3380250.

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Yagnik, Jay, and Atiq Islam. "Learning people annotation from the web via consistency learning." In the international workshop. ACM Press, 2007. http://dx.doi.org/10.1145/1290082.1290121.

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Gong, Xinyu, Yuefu Zhou, Yue Bi, et al. "Estimating Web Attack Detection via Model Uncertainty from Inaccurate Annotation." In 2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom). IEEE, 2019. http://dx.doi.org/10.1109/cscloud/edgecom.2019.00019.

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Shen, Hualei, Dianfu Ma, Yongwang Zhao, and Rongwei Ye. "Collaborative annotation of medical images via web browser for teleradiology." In 2012 International Conference on Computerized Healthcare (ICCH). IEEE, 2012. http://dx.doi.org/10.1109/icch.2012.6724483.

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Cao, Liangliang, Jie Yu, Jiebo Luo, and Thomas S. Huang. "Enhancing semantic and geographic annotation of web images via logistic canonical correlation regression." In the seventeen ACM international conference. ACM Press, 2009. http://dx.doi.org/10.1145/1631272.1631292.

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Voloshina, Ekaterina, and Polina Leonova. "The Universal Database for Lexical Typology." In INTERNATIONAL CONFERENCE on Computational Linguistics and Intellectual Technologies. RSUH, 2023. http://dx.doi.org/10.28995/2075-7182-2023-22-1133-1140.

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The paper presents the principles of creating a database for research in lexical typology and describes the possibilities of its use as a linguistic resource. The database is built around semantic fields and frames, i. e. units of analysis in the frame-based theory of lexical typology. The database provides a universal format for storing the data; therefore, any project in lexical typology can be easily added. The database does not only store the data from previous research projects but allows anyone who wants to contribute to submit data via its web interface. The database includes examples p
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Jia, Jimin, Nenghai Yu, and Xian-Sheng Hua. "Annotating personal albums via web mining." In Proceeding of the 16th ACM international conference. ACM Press, 2008. http://dx.doi.org/10.1145/1459359.1459421.

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Pattanaik, Vishwajeet, Shweta Suran, and Dirk Draheim. "Enabling Social Information Exchange via Dynamically Robust Annotations." In iiWAS2019: The 21st International Conference on Information Integration and Web-based Applications & Services. ACM, 2019. http://dx.doi.org/10.1145/3366030.3366060.

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