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.

Fuzzy Annotation of Web Data Tables Driven by a Domain Ontology

Abstract: We propose an automatic system for annotating accurately data tables extracted from the web. This system is designed to provide additional data to an existing querying system called MIEL, which relies on a common vocabulary used to query local relational databases. We will use the same vocabulary, translated into an OWL ontology, to annotate the tables. Our annotation system is unsupervised. It uses only the knowledge defined in the ontology to automatically annotate the entire content of tables, using an aggregation approach: first annotate cells, then columns, then relations between those columns. The annotations are fuzzy: instead of linking an element of the table with a precise concept of the ontology, the elements of the table are annotated with several concepts, associated with their relevance degree. Our annotation process has been validated experimentally on scientific domains (microbial risk in food, chemical risk in food) and a technical domain (aeronautics).

H-InvDB in 2009: extended database and data mining resources for human genes and transcripts.

Abstract: We report the extended database and data mining resources newly released in the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/). H-InvDB is a comprehensive annotation resource of human genes and transcripts, and consists of two main views and six sub-databases. The latest release of H-InvDB (release 6.2) provides the annotation for 219,765 human transcripts in 43,159 human gene clusters based on human full-length cDNAs and mRNAs. H-InvDB now provides several new annotation features, such as mapping of microarray probes, new gene models, relation to known ncRNAs and information from the Glycogene database. H-InvDB also provides useful data mining resources-'Navigation search', 'H-InvDB Enrichment Analysis Tool (HEAT)' and web service APIs. 'Navigation search' is an extended search system that enables complicated searches by combining 16 different search options. HEAT is a data mining tool for automatically identifying features specific to a given human gene set. HEAT searches for H-InvDB annotations that are significantly enriched in a user-defined gene set, as compared with the entire H-InvDB representative transcripts. H-InvDB now has web service APIs of SOAP and REST to allow the use of H-InvDB data in programs, providing the users extended data accessibility.

Annotation and Image Markup: Accessing and Interoperating with the Semantic Content in Medical Imaging

Abstract: The annotation and image markup project makes large distributed collections of medical images in cyberspace and hospital information systems accessible using an information model of image content and ontologies. Interest in applying semantic Web technologies to the life sciences continues to accelerate. Biomedical research is increasingly an online activity as scientists combine and explore different types of data in cyberspace, putting together complementary views on problems that lead to new insights and discoveries. An e-Science paradigm is thus emerging; the biomedical community is looking for tools to help access, query, and analyze a myriad of data in cyberspace. Specifically, the biomedical community is beginning to embrace technologies such as ontologies to integrate scientific knowledge, standard syntaxes, and semantics to make biomedical knowledge explicit, and the semantic Web to establish virtual collaborations.

Bootstrapping and Evaluating Named Entity Recognition in the Biomedical Domain

Abstract: We demonstrate that bootstrapping a gene name recognizer for FlyBase curation from automatically annotated noisy text is more effective than fully supervised training of the recognizer on more general manually annotated biomedical text. We present a new test set for this task based on an annotation scheme which distinguishes gene names from gene mentions, enabling a more consistent annotation. Evaluating our recognizer using this test set indicates that performance on unseen genes is its main weakness. We evaluate extensions to the technique used to generate training data designed to ameliorate this problem.

PhotoMap: from location and time to context-aware photo annotations

Abstract: Despite the growth of geotagged multimedia data on the Web, spatial and temporal metadata are still poorly exploited by Web search engines and multimedia systems. Interpretation and inference processes can enlarge these metadata towards high quality information that are useful for annotating multimedia automatically. In this article, we propose a semi-automatic approach for annotating personal photos based on the use of OWL-DL ontologies together with the next generation of mobile devices. We present an ontology called ContextPhoto and a contextual photo annotation approach which improve the development of more efficient personal image management tools. ContextPhoto provides concepts for representing captured and inferred context information reusing Web standards that describe spatial, temporal and social networking data. In order to validate the context annotation process we propose, we have also designed and developed a mobile and Web location-based system. This new system, called PhotoMap, is an evolution of the related mobile annotation systems since it provides automatic annotation about the spatial, temporal and social contexts of a photo. We also present a demonstration of the PhotoMap application during a tourist tour in the city of Rome.