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Wikipedia

Annotation

March 03, 2023

For the Wikipedia help page, see WP:ANNOTATION.

An annotation is extra information associated with a particular point in a document or other piece of information. It can be a note that includes a comment or explanation.[1] Annotations are sometimes presented in the margin of book pages. For annotations of different digital media, see web annotation and text annotation.

Literature and education

Textual scholarship

Main article: Text annotation

Textual scholarship is a discipline that often uses the technique of annotation to describe or add additional historical context to texts and physical documents to make it easier to understand.[2]

Student uses

Students often highlight passages in books in order to refer back to key phrases easily, or add marginalia to aid studying.

Annotated bibliographies add commentary on the relevance or quality of each source, in addition to the usual bibliographic information that merely identifies the source.

Mathematical expression annotation

Mathematical expressions (symbols and formulae) can be annotated with their natural language meaning. This is essential for disambiguation, since symbols may have different meanings (e.g., "E" can be "energy" or "expectation value", etc.).[3][4] The annotation process can be facilitated and accelerated through recommendation, e.g., using the "AnnoMathTeX" system that is hosted by Wikimedia.[5][6][7]

Learning and instruction

From a cognitive perspective, annotation has an important role in learning and instruction. As part of guided noticing it involves highlighting, naming or labelling and commenting aspects of visual representations to help focus learners' attention on specific visual aspects. In other words, it means the assignment of typological representations (culturally meaningful categories), to topological representations (e.g. images).[8] This is especially important when experts, such as medical doctors, interpret visualizations in detail and explain their interpretations to others, for example by means of digital technology.[9] Here, annotation can be a way to establish common ground between interactants with different levels of knowledge.[10] The value of annotation has been empirically confirmed, for example, in a study which shows that in computer-based teleconsultations the integration of image annotation and speech leads to significantly improved knowledge exchange compared with the use of images and speech without annotation.[11]

On YouTube

Annotations were removed on January 15, 2019 from YouTube after around a decade of service.[12] They had allowed users to provide information that popped up during videos, but YouTube indicated they did not work well on small mobile screens, and were being abused.

Software and engineering

Text documents

Main article: Text annotation

Markup languages like XML and HTML annotate text in a way that is syntactically distinguishable from that text. They can be used to add information about the desired visual presentation, or machine-readable semantic information, as in the semantic web.[13]

Tabular data

This includes CSV and XLS. The process of assigning semantic annotations to tabular data is referred to as semantic labelling. Semantic Labelling is the process of assigning annotations from ontologies to tabular data..[14][15][16][17]. This process is also referred to as semantic annotation.[18][17] Semantic Labelling is often done in a (semi-)automatic fashion. Semantic Labelling techniques works on entity columns,[17] numeric columns,[14][16][19][20] coordinates,[21] and more.[21][20]

Semantic Labelling Techniques

There are several semantic labelling types which utilises machine learning techniques. These techniques can be categorised following the work of Flach[22][23] as follows: geometric (using lines and planes, such as Support-vector machine, Linear regression), probabilistic (e.g., Conditional random field), logical (e.g., Decision tree learning), and Non-ML techniques (e.g., balancing coverage and specificity[24]). Note that the geometric, probabilistic, and logical machine learning models are not mutually exclusive.[22]

Geometric Techniques

Pham et al.[25] use Jaccard index and TF-IDF similarity for textual data and Kolmogorov–Smirnov test for the numeric ones. Alobaid and Corcho[26] use fuzzy clustering (c-means[27][28]) to label numeric columns.

Probabilistic Techniques

Limaye et al. [29] uses TF-IDF similarity and Graphical models. They also use Support-vector machine to compute the weights. Venetis et al. [30] construct an isA database which consists of the pairs (instance, class) and then compute maximum likelihood using these pairs.

Logical Techniques

Syed et al.[31] built Wikitology, which is "a hybrid knowledge base of structured and unstructured information extracted from Wikipedia augmented by RDF data from DBpedia and other Linked Data resources."[31]. For the Wikitology index, they use PageRank for Entity linking, which is one of the tasks often used in semantic labelling. Since they were not able to query Google for all Wikipedia articles to get the PageRank, they used Decision tree to approximate it.[31]

Non-ML techniques

Alobaid and Corcho[24] presented an approach to annotate entity columns. The technique starts by annotating the cells in the entity column with the entities from the reference knowledge graph (e.g., DBpedia). The classes are then gathered and each one of them is scored based on several formulas they presented taking into account the frequency of each class and their depth according to the subClass hierarchy.[32]

Semantic Labelling Common Tasks

There are some tasks are the common among the different semantic labelling approaches.

Entity Linking and Disambiguation

This is the most common task in semantic labelling. Given a text of a cell and a data source, the approach predicts the entity and link it to the one identified in the given data source. For example, if the input to the approach were the text "Richard Feynman" and a URL to the SPARQL endpoint of DBpedia, the approach would return "http://dbpedia.org/resource/Richard_Feynman", which is the entity from DBpedia. Some approaches use exact match.[24] while others use similarity metrics such as Cosine similarity[29]

Subject Column Identification

The subject column of a table is the column that contain the main subjects/entities in the table.[33][23][30][34][35] Some approaches expects the subject column as an input[24] while others predict the subject column such as TableMiner+.[35]

Column Data-Type Detection

Columns types are divided differently by different approaches.[23] Some divide them into strings/text and numbers[26][25][36][37] while others divide them further[23] (e.g., Number Typology,[33] Date,[31][30] coordinates[38]).

Relation Prediction

The relation between Madrid and Spain is "capitalOf".[39] Such relations can easily be found in ontologies, such as DBpedia. Venetis et al.[30] use TextRunner[40] to extract the relation between two columns. Syed et al.[31] use the relation between the entities of the two columns and the most frequent relation is selected.

Gold Standards

T2D[41] is the most common gold standard for semantic labelling. Two versions exists of T2D: T2Dv1 (sometimes are referred to T2D as well) and T2Dv2.[41] Another known benchmarks are published with the SemTab Challenge.[42]

Source control

The "annotate" function (also known as "blame" or "praise") used in source control systems such as Git, Team Foundation Server and Subversion determines who committed changes to the source code into the repository. This outputs a copy of the source code where each line is annotated with the name of the last contributor to edit that line (and possibly a revision number). This can help establish blame in the event a change caused a malfunction, or identify the author of brilliant code.

Java annotations

Main article: Java annotation

A special case is the Java programming language, where annotations can be used as a special form of syntactic metadata in the source code.[43] Classes, methods, variables, parameters and packages may be annotated. The annotations can be embedded in class files generated by the compiler and may be retained by the Java virtual machine and thus influence the run-time behaviour of an application. It is possible to create meta-annotations out of the existing ones in Java.[44]

Image annotation

Main article: Automatic image annotation

Automatic image annotation is used to classify images for image retrieval systems.[45]

Computational biology

Main article: DNA annotation

Since the 1980s, molecular biology and bioinformatics have created the need for DNA annotation. DNA annotation or genome annotation is the process of identifying the locations of genes and all of the coding regions in a genome and determining what those genes do. An annotation (irrespective of the context) is a note added by way of explanation or commentary. Once a genome is sequenced, it needs to be annotated to make sense of it.[46]

Digital imaging

In the digital imaging community the term annotation is commonly used for visible metadata superimposed on an image without changing the underlying master image, such as sticky notes, virtual laser pointers, circles, arrows, and black-outs (cf. redaction).[47]

In the medical imaging community, an annotation is often referred to as a region of interest and is encoded in DICOM format.

Other uses

Law

In the United States, legal publishers such as Thomson West and Lexis Nexis publish annotated versions of statutes, providing information about court cases that have interpreted the statutes. Both the federal United States Code and state statutes are subject to interpretation by the courts, and the annotated statutes are valuable tools in legal research.[48]

Linguistics

Main article: Text annotation § Linguistic annotation

One purpose of annotation is to transform the data into a form suitable for computer-aided analysis. Prior to annotation, an annotation scheme is defined that typically consists of tags. During tagging, transcriptionists manually add tags into transcripts where required linguistical features are identified in an annotation editor. The annotation scheme ensures that the tags are added consistently across the data set and allows for verification of previously tagged data.[49] Aside from tags, more complex forms of linguistic annotation include the annotation of phrases and relations, e.g., in treebanks. Many different forms of linguistic annotation have been developed, as well as different formats and tools for creating and managing linguistic annotations, as described, for example, in the Linguistic Annotation Wiki.[50]

See also

 
Look up annotation in Wiktionary, the free dictionary.

References

  1. ^ "Definition of ANNOTATION". www.merriam-webster.com.
  2. ^ Greetham, David C. (28 October 2015) [1992]. Textual Scholarship: An Introduction. Garland Reference Library of the Humanities. Vol. 1417. Routledge. ISBN 978-1-136-75579-8.
  3. ^ Moritz Schubotz; Philipp Scharpf; et al. (12 September 2018). "Introducing MathQA: a Math-Aware question answering system". Information Discovery and Delivery. Emerald Publishing Limited. 46 (4): 214–224. arXiv:1907.01642. doi:10.1108/IDD-06-2018-0022. S2CID 49484035.
  4. ^ Scharpf, P.; Schubotz, M.; et al. (2018). Representing Mathematical Formulae in Content MathML using Wikidata. ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018).
  5. ^ "AnnoMathTeX Formula/Identifier Annotation Recommender System".
  6. ^ Philipp Scharpf; Ian Mackerracher; et al. (17 September 2019). "AnnoMathTeX : a formula identifier annotation recommender system for STEM documents" (PDF). Proceedings of the 13th ACM Conference on Recommender Systems (RecSys 2019): 532–3. doi:10.1145/3298689.3347042. ISBN 9781450362436. S2CID 202639987.
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  25. ^ a b Pham, Minh; Alse, Suresh; Knoblock, Craig A.; Szekely, Pedro (2016). Groth, Paul; Simperl, Elena; Gray, Alasdair; Sabou, Marta; Krötzsch, Markus; Lecue, Freddy; Flöck, Fabian; Gil, Yolanda (eds.). "Semantic Labeling: A Domain-Independent Approach". The Semantic Web – ISWC 2016. Lecture Notes in Computer Science. Cham: Springer International Publishing. 9981: 446–462. doi:10.1007/978-3-319-46523-4_27. ISBN 978-3-319-46523-4.
  26. ^ a b Alobaid, Ahmad; Corcho, Oscar (2018). Faron Zucker, Catherine; Ghidini, Chiara; Napoli, Amedeo; Toussaint, Yannick (eds.). "Fuzzy Semantic Labeling of Semi-structured Numerical Datasets". Knowledge Engineering and Knowledge Management. Lecture Notes in Computer Science. Cham: Springer International Publishing. 11313: 19–33. doi:10.1007/978-3-030-03667-6_2. ISBN 978-3-030-03667-6.
  27. ^ Fuzzy c-Means Library, Ontology Engineering Group (UPM), 2022-01-29, retrieved 2023-01-04
  28. ^ fuzzy-c-means, Ontology Engineering Group (UPM), 2022-12-12, retrieved 2023-01-04
  29. ^ a b Limaye, Girija; Sarawagi, Sunita; Chakrabarti, Soumen (2010-09-01). "Annotating and searching web tables using entities, types and relationships". Proceedings of the VLDB Endowment. 3 (1–2): 1338–1347. doi:10.14778/1920841.1921005. ISSN 2150-8097. S2CID 9262964.
  30. ^ a b c d Venetis, Petros; Halevy, Alon; Madhavan, Jayant; Paşca, Marius; Shen, Warren; Wu, Fei; Miao, Gengxin; Wu, Chung (2011-06-01). "Recovering semantics of tables on the web". Proceedings of the VLDB Endowment. 4 (9): 528–538. doi:10.14778/2002938.2002939. ISSN 2150-8097. S2CID 11359711.
  31. ^ a b c d e Syed, Zareen; Finin, Tim; Mulwad, Varish; Joshi, Anupam (2010-04-26). "Exploiting a Web of Semantic Data for Interpreting Tables". Proceedings of the Second Web Science Conference.
  32. ^ "OWL Web Ontology Language Reference". www.w3.org. Retrieved 2022-09-22.
  33. ^ a b Alobaid, Ahmad; Kacprzak, Emilia; Corcho, Oscar (January 1, 2021). "Typology-based semantic labeling of numeric tabular data". Semantic Web. 12 (1): 5–20. doi:10.3233/SW-200397. S2CID 224853014 – via content.iospress.com.
  34. ^ Ermilov, Ivan; Ngomo, Axel-Cyrille Ngonga (2016), "TAIPAN: Automatic Property Mapping for Tabular Data", Lecture Notes in Computer Science, Cham: Springer International Publishing, pp. 163–179, doi:10.1007/978-3-319-49004-5_11, ISBN 978-3-319-49003-8, retrieved 2022-09-22
  35. ^ a b Zhang, Ziqi (2017-08-07). Hitzler, Pascal; Cruz, Isabel (eds.). "Effective and efficient Semantic Table Interpretation using TableMiner+". Semantic Web. 8 (6): 921–957. doi:10.3233/SW-160242.
  36. ^ Ramnandan, S.K.; Mittal, Amol; Knoblock, Craig A.; Szekely, Pedro (2015). Gandon, Fabien; Sabou, Marta; Sack, Harald; d’Amato, Claudia; Cudré-Mauroux, Philippe; Zimmermann, Antoine (eds.). "Assigning Semantic Labels to Data Sources". The Semantic Web. Latest Advances and New Domains. Lecture Notes in Computer Science. Cham: Springer International Publishing. 9088: 403–417. doi:10.1007/978-3-319-18818-8_25. ISBN 978-3-319-18818-8.
  37. ^ Zhang, Meihui; Chakrabarti, Kaushik (2013-06-22). "InfoGather+: semantic matching and annotation of numeric and time-varying attributes in web tables". Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data. SIGMOD '13. New York, NY, USA: Association for Computing Machinery: 145–156. doi:10.1145/2463676.2465276. ISBN 978-1-4503-2037-5. S2CID 15540847.
  38. ^ Quercini, Gianluca; Reynaud, Chantal (2013). "Entity discovery and annotation in tables". Proceedings of the 16th International Conference on Extending Database Technology - EDBT '13. New York, New York, USA: ACM Press: 693. doi:10.1145/2452376.2452457. ISBN 9781450315975. S2CID 8252126.
  39. ^ "About: capital of". dbpedia.org. Retrieved 2022-09-22.
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  43. ^ "JDK 5.0 Developer's Guide: Annotations". Sun Microsystems. 2007-12-18. from the original on 6 March 2008. Retrieved 2008-03-05..
  44. ^ Characterizing the Usage, Evolution and Impact of Java Annotations in Practice. "Characterizing the Usage, Evolution and Impact of Java Annotations in Practice".
  45. ^ Zhang, D.; Islam, M.M.; Lu, G. (2012). "A review on automatic image annotation techniques". Pattern Recognition. 45 (1): 346–362. Bibcode:2012PatRe..45..346Z. doi:10.1016/j.patcog.2011.05.013.
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  48. ^ Wyner, Adam; Peters, Wim; Katz, Daniel (2013). "A Case Study on Legal Case Annotation". In Ashley, Kevin D. (ed.). Legal Knowledge and Information Systems. Frontiers in Artificial Intelligence and Applications. Vol. 259. Amsterdam: IOS Press. pp. 165–174. doi:10.3233/978-1-61499-359-9-165. ISBN 978-1-61499-359-9.
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  50. ^ "LinguisticAnnotation". annotation.exmaralda.org.

March 03, 2023
annotation, this, article, multiple, issues, please, help, improve, discuss, these, issues, talk, page, learn, when, remove, these, template, messages, this, article, lead, section, short, adequately, summarize, points, please, consider, expanding, lead, provi. This article has multiple issues Please help improve it or discuss these issues on the talk page Learn how and when to remove these template messages This article s lead section may be too short to adequately summarize the key points Please consider expanding the lead to provide an accessible overview of all important aspects of the article February 2015 This article needs additional citations for verification Please help improve this article by adding citations to reliable sources Unsourced material may be challenged and removed Find sources Annotation news newspapers books scholar JSTOR February 2015 Learn how and when to remove this template message Learn how and when to remove this template message For the Wikipedia help page see WP ANNOTATION An annotation is extra information associated with a particular point in a document or other piece of information It can be a note that includes a comment or explanation 1 Annotations are sometimes presented in the margin of book pages For annotations of different digital media see web annotation and text annotation Contents 1 Literature and education 1 1 Textual scholarship 1 2 Student uses 1 3 Mathematical expression annotation 1 4 Learning and instruction 1 5 On YouTube 2 Software and engineering 2 1 Text documents 2 1 1 Tabular data 2 1 1 1 Semantic Labelling Techniques 2 1 1 1 1 Geometric Techniques 2 1 1 1 2 Probabilistic Techniques 2 1 1 1 3 Logical Techniques 2 1 1 1 4 Non ML techniques 2 1 1 2 Semantic Labelling Common Tasks 2 1 1 2 1 Entity Linking and Disambiguation 2 1 1 2 2 Subject Column Identification 2 1 1 2 3 Column Data Type Detection 2 1 1 2 4 Relation Prediction 2 1 1 3 Gold Standards 2 2 Source control 2 3 Java annotations 2 4 Image annotation 2 5 Computational biology 2 6 Digital imaging 3 Other uses 3 1 Law 3 2 Linguistics 4 See also 5 ReferencesLiterature and education EditTextual scholarship Edit Main article Text annotation Textual scholarship is a discipline that often uses the technique of annotation to describe or add additional historical context to texts and physical documents to make it easier to understand 2 Student uses Edit Students often highlight passages in books in order to refer back to key phrases easily or add marginalia to aid studying Annotated bibliographies add commentary on the relevance or quality of each source in addition to the usual bibliographic information that merely identifies the source Mathematical expression annotation Edit Mathematical expressions symbols and formulae can be annotated with their natural language meaning This is essential for disambiguation since symbols may have different meanings e g E can be energy or expectation value etc 3 4 The annotation process can be facilitated and accelerated through recommendation e g using the AnnoMathTeX system that is hosted by Wikimedia 5 6 7 Learning and instruction Edit From a cognitive perspective annotation has an important role in learning and instruction As part of guided noticing it involves highlighting naming or labelling and commenting aspects of visual representations to help focus learners attention on specific visual aspects In other words it means the assignment of typological representations culturally meaningful categories to topological representations e g images 8 This is especially important when experts such as medical doctors interpret visualizations in detail and explain their interpretations to others for example by means of digital technology 9 Here annotation can be a way to establish common ground between interactants with different levels of knowledge 10 The value of annotation has been empirically confirmed for example in a study which shows that in computer based teleconsultations the integration of image annotation and speech leads to significantly improved knowledge exchange compared with the use of images and speech without annotation 11 On YouTube Edit Annotations were removed on January 15 2019 from YouTube after around a decade of service 12 They had allowed users to provide information that popped up during videos but YouTube indicated they did not work well on small mobile screens and were being abused Software and engineering EditText documents Edit Main article Text annotation Markup languages like XML and HTML annotate text in a way that is syntactically distinguishable from that text They can be used to add information about the desired visual presentation or machine readable semantic information as in the semantic web 13 Tabular data Edit This includes CSV and XLS The process of assigning semantic annotations to tabular data is referred to as semantic labelling Semantic Labelling is the process of assigning annotations from ontologies to tabular data 14 15 16 17 This process is also referred to as semantic annotation 18 17 Semantic Labelling is often done in a semi automatic fashion Semantic Labelling techniques works on entity columns 17 numeric columns 14 16 19 20 coordinates 21 and more 21 20 Semantic Labelling Techniques Edit There are several semantic labelling types which utilises machine learning techniques These techniques can be categorised following the work of Flach 22 23 as follows geometric using lines and planes such as Support vector machine Linear regression probabilistic e g Conditional random field logical e g Decision tree learning and Non ML techniques e g balancing coverage and specificity 24 Note that the geometric probabilistic and logical machine learning models are not mutually exclusive 22 Geometric Techniques Edit Pham et al 25 use Jaccard index and TF IDF similarity for textual data and Kolmogorov Smirnov test for the numeric ones Alobaid and Corcho 26 use fuzzy clustering c means 27 28 to label numeric columns Probabilistic Techniques Edit Limaye et al 29 uses TF IDF similarity and Graphical models They also use Support vector machine to compute the weights Venetis et al 30 construct an isA database which consists of the pairs instance class and then compute maximum likelihood using these pairs Logical Techniques Edit Syed et al 31 built Wikitology which is a hybrid knowledge base of structured and unstructured information extracted from Wikipedia augmented by RDF data from DBpedia and other Linked Data resources 31 For the Wikitology index they use PageRank for Entity linking which is one of the tasks often used in semantic labelling Since they were not able to query Google for all Wikipedia articles to get the PageRank they used Decision tree to approximate it 31 Non ML techniques Edit Alobaid and Corcho 24 presented an approach to annotate entity columns The technique starts by annotating the cells in the entity column with the entities from the reference knowledge graph e g DBpedia The classes are then gathered and each one of them is scored based on several formulas they presented taking into account the frequency of each class and their depth according to the subClass hierarchy 32 Semantic Labelling Common Tasks Edit There are some tasks are the common among the different semantic labelling approaches Entity Linking and Disambiguation Edit This is the most common task in semantic labelling Given a text of a cell and a data source the approach predicts the entity and link it to the one identified in the given data source For example if the input to the approach were the text Richard Feynman and a URL to the SPARQL endpoint of DBpedia the approach would return http dbpedia org resource Richard Feynman which is the entity from DBpedia Some approaches use exact match 24 while others use similarity metrics such as Cosine similarity 29 Subject Column Identification Edit The subject column of a table is the column that contain the main subjects entities in the table 33 23 30 34 35 Some approaches expects the subject column as an input 24 while others predict the subject column such as TableMiner 35 Column Data Type Detection Edit Columns types are divided differently by different approaches 23 Some divide them into strings text and numbers 26 25 36 37 while others divide them further 23 e g Number Typology 33 Date 31 30 coordinates 38 Relation Prediction Edit The relation between Madrid and Spain is capitalOf 39 Such relations can easily be found in ontologies such as DBpedia Venetis et al 30 use TextRunner 40 to extract the relation between two columns Syed et al 31 use the relation between the entities of the two columns and the most frequent relation is selected Gold Standards Edit T2D 41 is the most common gold standard for semantic labelling Two versions exists of T2D T2Dv1 sometimes are referred to T2D as well and T2Dv2 41 Another known benchmarks are published with the SemTab Challenge 42 Source control Edit The annotate function also known as blame or praise used in source control systems such as Git Team Foundation Server and Subversion determines who committed changes to the source code into the repository This outputs a copy of the source code where each line is annotated with the name of the last contributor to edit that line and possibly a revision number This can help establish blame in the event a change caused a malfunction or identify the author of brilliant code Java annotations Edit Main article Java annotation A special case is the Java programming language where annotations can be used as a special form of syntactic metadata in the source code 43 Classes methods variables parameters and packages may be annotated The annotations can be embedded in class files generated by the compiler and may be retained by the Java virtual machine and thus influence the run time behaviour of an application It is possible to create meta annotations out of the existing ones in Java 44 Image annotation Edit Main article Automatic image annotation Automatic image annotation is used to classify images for image retrieval systems 45 Computational biology Edit Main article DNA annotation Since the 1980s molecular biology and bioinformatics have created the need for DNA annotation DNA annotation or genome annotation is the process of identifying the locations of genes and all of the coding regions in a genome and determining what those genes do An annotation irrespective of the context is a note added by way of explanation or commentary Once a genome is sequenced it needs to be annotated to make sense of it 46 Digital imaging Edit In the digital imaging community the term annotation is commonly used for visible metadata superimposed on an image without changing the underlying master image such as sticky notes virtual laser pointers circles arrows and black outs cf redaction 47 In the medical imaging community an annotation is often referred to as a region of interest and is encoded in DICOM format Other uses EditLaw Edit In the United States legal publishers such as Thomson West and Lexis Nexis publish annotated versions of statutes providing information about court cases that have interpreted the statutes Both the federal United States Code and state statutes are subject to interpretation by the courts and the annotated statutes are valuable tools in legal research 48 Linguistics Edit Main article Text annotation Linguistic annotation One purpose of annotation is to transform the data into a form suitable for computer aided analysis Prior to annotation an annotation scheme is defined that typically consists of tags During tagging transcriptionists manually add tags into transcripts where required linguistical features are identified in an annotation editor The annotation scheme ensures that the tags are added consistently across the data set and allows for verification of previously tagged data 49 Aside from tags more complex forms of linguistic annotation include the annotation of phrases and relations e g in treebanks Many different forms of linguistic annotation have been developed as well as different formats and tools for creating and managing linguistic annotations as described for example in the Linguistic Annotation Wiki 50 See also Edit Look up annotation in Wiktionary the free dictionary Abstract summary Automatic image annotation Coding social sciences Drama annotation Comment various Footnote Hyperkino Index publishing Marginalia Metadata Nota Bene Obelus a symbol used on ancient manuscripts to mark passages that were suspected of being corrupted or spurious the practice of adding such marginal notes became known as obelism PDF annotation Subject indexing Semantics Tag metadata Text annotation Web annotation XPS annotationReferences Edit Definition of ANNOTATION www merriam webster com Greetham David C 28 October 2015 1992 Textual Scholarship An Introduction Garland Reference Library of the Humanities Vol 1417 Routledge ISBN 978 1 136 75579 8 Moritz Schubotz Philipp Scharpf et al 12 September 2018 Introducing MathQA a Math Aware question answering system Information Discovery and Delivery Emerald Publishing Limited 46 4 214 224 arXiv 1907 01642 doi 10 1108 IDD 06 2018 0022 S2CID 49484035 Scharpf P Schubotz M et al 2018 Representing Mathematical Formulae in Content MathML using Wikidata ACM SIGIR Conference on Research and Development in Information Retrieval SIGIR 2018 AnnoMathTeX Formula Identifier Annotation Recommender System Philipp Scharpf Ian Mackerracher et al 17 September 2019 AnnoMathTeX a formula identifier annotation recommender system for STEM documents PDF Proceedings of the 13th ACM Conference on Recommender Systems RecSys 2019 532 3 doi 10 1145 3298689 3347042 ISBN 9781450362436 S2CID 202639987 Philipp Scharpf Moritz Schubotz Bela Gipp 14 April 2021 Fast Linking of Mathematical Wikidata Entities in Wikipedia Articles Using Annotation Recommendation PDF Companion Proceedings of the Web Conference 2021 WWW 21 Companion 602 9 arXiv 2104 05111 doi 10 1145 3442442 3452348 ISBN 9781450383134 S2CID 233210264 Pea R D 2006 Video as Data and Digital Video Manipulation Techniques for Transforming Learning Sciences Research Education and Other Cultural Practices The International Handbook of Virtual Learning Environments PDF Springer pp 1321 93 doi 10 1007 978 1 4020 3803 7 55 ISBN 978 1 4020 3803 7 Coiera E 2014 Communication spaces J Am Med Inform Assoc 21 3 414 422 doi 10 1136 amiajnl 2012 001520 PMC 3994845 PMID 24005797 Clark Herbert H 1996 Using Language Cambridge University Press ISBN 978 0 521 56745 9 Pimmer C Mateescu M Zahn C Genewein U 2013 Smartphones as multimodal communication devices to facilitate clinical knowledge processes a randomized controlled trial Journal of Medical Internet Research 15 11 e263 doi 10 2196 jmir 2758 PMC 3868983 PMID 24284080 YouTube annotations will disappear for good in January engadget 2018 11 27 Retrieved 2019 01 19 Web Annotation Data Model World Wide Web Consortium 11 December 2014 Retrieved 25 August 2015 a b Alobaid Ahmad Kacprzak Emilia Corcho Oscar January 1 2021 Typology based semantic labeling of numeric tabular data Semantic Web 12 1 5 20 doi 10 3233 SW 200397 S2CID 224853014 via content iospress com Taheriyan Mohsen Knoblock Craig A Szekely Pedro Ambite Jose Luis March 1 2016 Learning the semantics of structured data sources Web Semantics Science Services and Agents on the World Wide Web 37 C 152 169 arXiv 1601 04105 doi 10 1016 j websem 2015 12 003 S2CID 7409058 via March 2016 a b Alobaid Ahmad Corcho Oscar 2018 Faron Zucker Catherine Ghidini Chiara Napoli Amedeo Toussaint Yannick eds Fuzzy Semantic Labeling of Semi structured Numerical Datasets Knowledge Engineering and Knowledge Management Lecture Notes in Computer Science Cham Springer International Publishing 11313 19 33 doi 10 1007 978 3 030 03667 6 2 ISBN 978 3 030 03667 6 a b c Alobaid Ahmad Corcho Oscar 2022 03 15 Balancing coverage and specificity for semantic labelling of subject columns Knowledge Based Systems 240 108092 doi 10 1016 j knosys 2021 108092 ISSN 0950 7051 S2CID 245971543 Hassanzadeh O Ward Michael J Rodriguez Muro Mariano Srinivas Kavitha December 17 2015 Understanding a large corpus of web tables through matching with knowledge bases an empirical study S2CID 442374 via Semantic Scholar Neumaier Sebastian Umbrich Jurgen Parreira Josiane Xavier Polleres Axel 2016 Groth Paul Simperl Elena Gray Alasdair Sabou Marta Krotzsch Markus Lecue Freddy Flock Fabian Gil Yolanda eds Multi level Semantic Labelling of Numerical Values The Semantic Web ISWC 2016 Lecture Notes in Computer Science Cham Springer International Publishing 9981 428 445 doi 10 1007 978 3 319 46523 4 26 ISBN 978 3 319 46523 4 a b Zhang Meihui Chakrabarti Kaushik 2013 06 22 InfoGather semantic matching and annotation of numeric and time varying attributes in web tables Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data SIGMOD 13 New York NY USA Association for Computing Machinery 145 156 doi 10 1145 2463676 2465276 ISBN 978 1 4503 2037 5 S2CID 15540847 a b Ritze Dominique Lehmberg Oliver Bizer Christian July 13 2015 Matching HTML Tables to DBpedia Proceedings of the 5th International Conference on Web Intelligence Mining and Semantics Association for Computing Machinery pp 1 6 doi 10 1145 2797115 2797118 ISBN 9781450332934 S2CID 207228254 via ACM Digital Library a b Flach Peter 2012 Machine Learning The Art and Science of Algorithms that Make Sense of Data Cambridge Cambridge University Press doi 10 1017 cbo9780511973000 ISBN 978 1 107 09639 4 a b c d Alobaid Ahmad c 2020 Knowledge Graph Based Semantic Labeling of Tabular Data phd thesis E T S de Ingenieros Informaticos UPM doi 10 20868 upm thesis 64068 a b c d Alobaid Ahmad Corcho Oscar 2022 03 15 Balancing coverage and specificity for semantic labelling of subject columns Knowledge Based Systems 240 108092 doi 10 1016 j knosys 2021 108092 ISSN 0950 7051 S2CID 245971543 a b Pham Minh Alse Suresh Knoblock Craig A Szekely Pedro 2016 Groth Paul Simperl Elena Gray Alasdair Sabou Marta Krotzsch Markus Lecue Freddy Flock Fabian Gil Yolanda eds Semantic Labeling A Domain Independent Approach The Semantic Web ISWC 2016 Lecture Notes in Computer Science Cham Springer International Publishing 9981 446 462 doi 10 1007 978 3 319 46523 4 27 ISBN 978 3 319 46523 4 a b Alobaid Ahmad Corcho Oscar 2018 Faron Zucker Catherine Ghidini Chiara Napoli Amedeo Toussaint Yannick eds Fuzzy Semantic Labeling of Semi structured Numerical Datasets Knowledge Engineering and Knowledge Management Lecture Notes in Computer Science Cham Springer International Publishing 11313 19 33 doi 10 1007 978 3 030 03667 6 2 ISBN 978 3 030 03667 6 Fuzzy c Means Library Ontology Engineering Group UPM 2022 01 29 retrieved 2023 01 04 fuzzy c means Ontology Engineering Group UPM 2022 12 12 retrieved 2023 01 04 a b Limaye Girija Sarawagi Sunita Chakrabarti Soumen 2010 09 01 Annotating and searching web tables using entities types and relationships Proceedings of the VLDB Endowment 3 1 2 1338 1347 doi 10 14778 1920841 1921005 ISSN 2150 8097 S2CID 9262964 a b c d Venetis Petros Halevy Alon Madhavan Jayant Pasca Marius Shen Warren Wu Fei Miao Gengxin Wu Chung 2011 06 01 Recovering semantics of tables on the web Proceedings of the VLDB Endowment 4 9 528 538 doi 10 14778 2002938 2002939 ISSN 2150 8097 S2CID 11359711 a b c d e Syed Zareen Finin Tim Mulwad Varish Joshi Anupam 2010 04 26 Exploiting a Web of Semantic Data for Interpreting Tables Proceedings of the Second Web Science Conference OWL Web Ontology Language Reference www w3 org Retrieved 2022 09 22 a b Alobaid Ahmad Kacprzak Emilia Corcho Oscar January 1 2021 Typology based semantic labeling of numeric tabular data Semantic Web 12 1 5 20 doi 10 3233 SW 200397 S2CID 224853014 via content iospress com Ermilov Ivan Ngomo Axel Cyrille Ngonga 2016 TAIPAN Automatic Property Mapping for Tabular Data Lecture Notes in Computer Science Cham Springer International Publishing pp 163 179 doi 10 1007 978 3 319 49004 5 11 ISBN 978 3 319 49003 8 retrieved 2022 09 22 a b Zhang Ziqi 2017 08 07 Hitzler Pascal Cruz Isabel eds Effective and efficient Semantic Table Interpretation using TableMiner Semantic Web 8 6 921 957 doi 10 3233 SW 160242 Ramnandan S K Mittal Amol Knoblock Craig A Szekely Pedro 2015 Gandon Fabien Sabou Marta Sack Harald d Amato Claudia Cudre Mauroux Philippe Zimmermann Antoine eds Assigning Semantic Labels to Data Sources The Semantic Web Latest Advances and New Domains Lecture Notes in Computer Science Cham Springer International Publishing 9088 403 417 doi 10 1007 978 3 319 18818 8 25 ISBN 978 3 319 18818 8 Zhang Meihui Chakrabarti Kaushik 2013 06 22 InfoGather semantic matching and annotation of numeric and time varying attributes in web tables Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data SIGMOD 13 New York NY USA Association for Computing Machinery 145 156 doi 10 1145 2463676 2465276 ISBN 978 1 4503 2037 5 S2CID 15540847 Quercini Gianluca Reynaud Chantal 2013 Entity discovery and annotation in tables Proceedings of the 16th International Conference on Extending Database Technology EDBT 13 New York New York USA ACM Press 693 doi 10 1145 2452376 2452457 ISBN 9781450315975 S2CID 8252126 About capital of dbpedia org Retrieved 2022 09 22 Etzioni Oren Banko Michele Soderland Stephen Weld Daniel S 2008 12 01 Open information extraction from the web Communications of the ACM 51 12 68 74 doi 10 1145 1409360 1409378 ISSN 0001 0782 S2CID 207169186 a b Bizer Dominique Ritze Oliver Lehmberg Christian Web Data Commons T2Dv2 webdatacommons org Retrieved 2022 07 18 Semantic Web Challenge on Tabular Data to Knowledge Graph Matching www cs ox ac uk Retrieved 2022 09 30 JDK 5 0 Developer s Guide Annotations Sun Microsystems 2007 12 18 Archived from the original on 6 March 2008 Retrieved 2008 03 05 Characterizing the Usage Evolution and Impact of Java Annotations in Practice Characterizing the Usage Evolution and Impact of Java Annotations in Practice Zhang D Islam M M Lu G 2012 A review on automatic image annotation techniques Pattern Recognition 45 1 346 362 Bibcode 2012PatRe 45 346Z doi 10 1016 j patcog 2011 05 013 Medical Definition of Genome annotation MedicineNet Retrieved 2021 09 09 Pelka Obioma Nensa Felix Friedrich Christoph M 2018 11 12 Annotation of enhanced radiographs for medical image retrieval with deep convolutional neural networks PLOS ONE 13 11 e0206229 Bibcode 2018PLoSO 1306229P doi 10 1371 journal pone 0206229 ISSN 1932 6203 PMC 6231616 PMID 30419028 Wyner Adam Peters Wim Katz Daniel 2013 A Case Study on Legal Case Annotation In Ashley Kevin D ed Legal Knowledge and Information Systems Frontiers in Artificial Intelligence and Applications Vol 259 Amsterdam IOS Press pp 165 174 doi 10 3233 978 1 61499 359 9 165 ISBN 978 1 61499 359 9 Annotation Schemes CAWSE PDF General Annotation Conventions 2017 02 05 Retrieved 2019 01 06 LinguisticAnnotation annotation exmaralda org Retrieved from https en wikipedia org w index php title Annotation amp oldid 1132500352, wikipedia, wiki, book, books, library,

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