Semantic Annotation of Unstructured Documents Using Concepts Similarity

Joint Authors

Pech, Fernando
Martinez, Alicia
Estrada, Hugo
Hernandez, Yasmin

Source

Scientific Programming

Issue

Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-10, 10 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2017-12-07

Country of Publication

Egypt

No. of Pages

10

Main Subjects

Mathematics

Abstract EN

There is a large amount of information in the form of unstructured documents which pose challenges in the information storage, search, and retrieval.

This situation has given rise to several information search approaches.

Some proposals take into account the contextual meaning of the terms specified in the query.

Semantic annotation technique can help to retrieve and extract information in unstructured documents.

We propose a semantic annotation strategy for unstructured documents as part of a semantic search engine.

In this proposal, ontologies are used to determine the context of the entities specified in the query.

Our strategy for extracting the context is focused on concepts similarity.

Each relevant term of the document is associated with an instance in the ontology.

The similarity between each of the explicit relationships is measured through the combination of two types of associations: the association between each pair of concepts and the calculation of the weight of the relationships.

American Psychological Association (APA)

Pech, Fernando& Martinez, Alicia& Estrada, Hugo& Hernandez, Yasmin. 2017. Semantic Annotation of Unstructured Documents Using Concepts Similarity. Scientific Programming،Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1203472

Modern Language Association (MLA)

Pech, Fernando…[et al.]. Semantic Annotation of Unstructured Documents Using Concepts Similarity. Scientific Programming No. 2017 (2017), pp.1-10.
https://search.emarefa.net/detail/BIM-1203472

American Medical Association (AMA)

Pech, Fernando& Martinez, Alicia& Estrada, Hugo& Hernandez, Yasmin. Semantic Annotation of Unstructured Documents Using Concepts Similarity. Scientific Programming. 2017. Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1203472

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1203472