Baseline Results for the ImageCLEF 2006 Medical Automatic Annotation Task

The development of research in the annotation area is growing. Researchers perform annotation task using various forms of datasets such as text, sound, images, and videos. Various algorithms are used to perform tasks. The purpose of this survey is to find out algorithms that are often used by researchers to perform annotation tasks, especially on text data. The literature surveys thirteen research papers on text annotation from the last 5 years. The results of this review indicate that SVM is the algorithm used for all three annotation methods: manual, automatic and semi-automatic annotation, with a significant accuracy above 80%. The result of this survey will be referred by the authors as the basis for subsequent research that will be conducted, especially in the semi-automatic annotation method.

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A Query-based Approach for Semi-Automatic Annotation of Web Services

International Journal of Information Systems and Social Change ◽

10.4018/jissc.2011040103 ◽

2011 ◽

Vol 2 (2) ◽

pp. 37-54 ◽

Cited By ~ 3

Author(s):

Mohammad Mourhaf AL Asswad ◽

Sergio de Cesare ◽

Mark Lycett

Keyword(s):

Web Services ◽

Semantic Web ◽

Semantic Annotation ◽

Semantic Web Services ◽

Manual Annotation ◽

Automatic Annotation ◽

Query Execution ◽

Annotation Task ◽

Compound Nouns ◽

Execution Engine

Semantic Web services (SWS) have attracted increasing attention due to their potential to automate discovery and composition of current syntactic Web services. An issue that prevents a wider adoption of SWS relates to the manual nature of the semantic annotation task. Manual annotation is a difficult, error-prone, and time-consuming process and automating the process is highly desirable. Though some approaches have been proposed to semi-automate the annotation task, they are difficult to use and cannot perform accurate annotation for the following reasons: (1) They require building application ontologies to represent candidate services and (2) they cannot perform accurate name-based matching when labels of candidate service elements and ontological entities contain Compound Nouns (CN). To overcome these two deficiencies, this paper proposes a query-based approach that can facilitate semi-automatic annotation of Web services. The proposed approach is easy to use because it does not require building application ontologies to represent services. Candidate service elements that need to be annotated are extracted from a WSDL file and used to generate query instances by filling a Standard Query Template. The resulting query instances are executed against a repository of ontologies using a novel query execution engine to find appropriate correspondences for candidate service elements. This query execution engine employs name-based and structural matching mechanisms that can perform effective and accurate similarity measurements between labels containing CNs. The proposed semi-automatic annotation approach is evaluated by employing it to annotate existing Web services using published domain ontologies. Precision and recall are used as evaluation metrics. The resulting precision and recall values demonstrate the effectiveness and applicability of the proposed approach.

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Baseline Results for the ImageCLEF 2008 Medical Automatic Annotation Task in Comparison over the Years

Lecture Notes in Computer Science - Evaluating Systems for Multilingual and Multimodal Information Access ◽

10.1007/978-3-642-04447-2_97 ◽

2009 ◽

pp. 752-755

Author(s):

Mark O. Güld ◽

Petra Welter ◽

Thomas M. Deserno

Keyword(s):

Automatic Annotation ◽

Annotation Task

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A Query-Based Approach for Semi-Automatic Annotation of Web Services

Information Systems and Modern Society ◽

10.4018/978-1-4666-2922-6.ch008 ◽

2012 ◽

pp. 125-143

Author(s):

Mohammad Mourhaf AL Asswad ◽

Sergio de Cesare ◽

Mark Lycett

Keyword(s):

Web Services ◽

Semantic Web ◽

Semantic Annotation ◽

Semantic Web Services ◽

Manual Annotation ◽

Automatic Annotation ◽

Query Execution ◽

Annotation Task ◽

Compound Nouns ◽

Execution Engine

Semantic Web services (SWS) have attracted increasing attention due to their potential to automate discovery and composition of current syntactic Web services. An issue that prevents a wider adoption of SWS relates to the manual nature of the semantic annotation task. Manual annotation is a difficult, error-prone, and time-consuming process and automating the process is highly desirable. Though some approaches have been proposed to semi-automate the annotation task, they are difficult to use and cannot perform accurate annotation for the following reasons: (1) They require building application ontologies to represent candidate services and (2) they cannot perform accurate name-based matching when labels of candidate service elements and ontological entities contain Compound Nouns (CN). To overcome these two deficiencies, this paper proposes a query-based approach that can facilitate semi-automatic annotation of Web services. The proposed approach is easy to use because it does not require building application ontologies to represent services. Candidate service elements that need to be annotated are extracted from a WSDL file and used to generate query instances by filling a Standard Query Template. The resulting query instances are executed against a repository of ontologies using a novel query execution engine to find appropriate correspondences for candidate service elements. This query execution engine employs name-based and structural matching mechanisms that can perform effective and accurate similarity measurements between labels containing CNs. The proposed semi-automatic annotation approach is evaluated by employing it to annotate existing Web services using published domain ontologies. Precision and recall are used as evaluation metrics. The resulting precision and recall values demonstrate the effectiveness and applicability of the proposed approach.

Download Full-text