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Topic

Annotation

About: Annotation is a research topic. Over the lifetime, 6719 publications have been published within this topic receiving 203463 citations. The topic is also known as: note & markup.


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Patent
18 May 2011
TL;DR: Annotations can be automatically added to a media presentation during playback of the presentation without a user having to manually interact with the playback device as discussed by the authors, which can be used to determine whether a user is speaking to the computing device as well.
Abstract: Annotations can be automatically added to a media presentation during playback of the presentation without a user having to manually interact with the playback device. The playback device determines whether an annotation is to be added to the media presentation based on characteristics of voice input received at the device, such as voice input signal strength or variances in the voice input signal strength. Characteristics of video input received at the device can be used to determine whether a user is speaking to the computing device as well. The device can handle a new annotation overlapping an existing annotation by either removing the existing annotation or by shifting the existing annotation until there is no more overlap. A media presentation can comprise multiple annotation tracks.

59 citations

Journal ArticleDOI
TL;DR: The results show that methods which build on local image descriptors and discriminative models are able to provide good predictions of the image classes, mostly by using techniques that were originally developed in the machine learning and computer vision domain for object recognition in non-medical images.

59 citations

Journal ArticleDOI
TL;DR: A solution to this problem is a technique called deep annotation, which uses three elements of information-the information itself, its structure, and its context-to derive mappings.
Abstract: One of the core challenges of the Semantic Web is to create metadata by mass collaboration. A solution to this problem is a technique called deep annotation, which uses three elements of information-the information itself, its structure, and its context-to derive mappings.

59 citations

Journal ArticleDOI
Eva Klien1
TL;DR: A rule‐based strategy for the semantic annotation of geodata that combines Semantic Web and Geospatial Web Services technology is presented and lays the foundations for the specification of a semantic annotation tool for geospatial web services that supports data providers in annotating their sources according to multiple domain views.
Abstract: The ability to represent geospatial semantics is of great importance when building geospatial applications for the Web. This ability will enhance discovery, retrieval and translation of geographic information as well as the reuse of geographic information in different contexts. The problem of generating semantic annotations has been recognized as one of the most serious obstacles for realizing the Geospatial Semantic Web vision. We present a rule-based strategy for the semantic annotation of geodata that combines Semantic Web and Geospatial Web Services technology. In our approach, rules are employed to partially automate the annotation process. Rules define conditions for identifying geospatial concepts. Based on these rules, spatial analysis procedures are implemented that allow for inferring whether or not a feature in a dataset represents an instance of a geospatial concept. This automated evaluation of features in the dataset generates valuable information for the creation and refinement of semantic annotations on the concept level. The approach is illustrated by a case study on annotating data sources containing representations of lowlands. The presented strategy lays the foundations for the specification of a semantic annotation tool for geospatial web services that supports data providers in annotating their sources according to multiple domain views.

59 citations

Journal ArticleDOI
TL;DR: FastAnnotator is an automated annotation web tool designed to efficiently annotate sequences with their gene functions, enzyme functions or domains and is useful in transcriptome studies and especially for those focusing on non-model organisms or metatranscriptomes.
Abstract: Recent developments in high-throughput sequencing (HTS) technologies have made it feasible to sequence the complete transcriptomes of non-model organisms or metatranscriptomes from environmental samples. The challenge after generating hundreds of millions of sequences is to annotate these transcripts and classify the transcripts based on their putative functions. Because many biological scientists lack the knowledge to install Linux-based software packages or maintain databases used for transcript annotation, we developed an automatic annotation tool with an easy-to-use interface. To elucidate the potential functions of gene transcripts, we integrated well-established annotation tools: Blast2GO, PRIAM and RPS BLAST in a web-based service, FastAnnotator, which can assign Gene Ontology (GO) terms, Enzyme Commission numbers (EC numbers) and functional domains to query sequences. Using six transcriptome sequence datasets as examples, we demonstrated the ability of FastAnnotator to assign functional annotations. FastAnnotator annotated 88.1% and 81.3% of the transcripts from the well-studied organisms Caenorhabditis elegans and Streptococcus parasanguinis, respectively. Furthermore, FastAnnotator annotated 62.9%, 20.4%, 53.1% and 42.0% of the sequences from the transcriptomes of sweet potato, clam, amoeba, and Trichomonas vaginalis, respectively, which lack reference genomes. We demonstrated that FastAnnotator can complete the annotation process in a reasonable amount of time and is suitable for the annotation of transcriptomes from model organisms or organisms for which annotated reference genomes are not avaiable. The sequencing process no longer represents the bottleneck in the study of genomics, and automatic annotation tools have become invaluable as the annotation procedure has become the limiting step. We present FastAnnotator, which was an automated annotation web tool designed to efficiently annotate sequences with their gene functions, enzyme functions or domains. FastAnnotator is useful in transcriptome studies and especially for those focusing on non-model organisms or metatranscriptomes. FastAnnotator does not require local installation and is freely available at http://fastannotator.cgu.edu.tw .

59 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20231,461
20223,073
2021305
2020401
2019383
2018373