Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Semantic Processing of Database Textual Attributes Using Wikipedia
Date
2011-10-28
Author
Campana, Jesus R.
Medina, Juan M.
Vila, M. Amparo
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
105
views
0
downloads
Cite This
Text attributes in databases contain rich semantic information that is seldom processed or used. This paper proposes a method to extract and semantically represent concepts from texts stored in databases. This process relies on tools such as WordNet and Wikipedia to identify concepts extracted from texts and represent them as a basic ontology whose concepts are annotated with search terms. This ontology can play diverse roles. It can be seen as a conceptual summary of the content of an attribute, which can be used as a means to navigate through the textual content of an attribute. It can also be used as a profile for text search using the terms associated to the ontology concepts. The ontology is built as a subset of Wikipedia category graph, selected using diverse metrics. Category selection using these metrics is discussed and an example application is presented and evaluated.
Subject Keywords
Similarity metrics
,
Wikipedia category graph
,
Ontologies
,
Text processing
,
Databases
,
DeTre, G
URI
https://hdl.handle.net/11511/66556
Conference Name
9th International Conference on Flexible Query Answering Systems (FQAS 2011)
Collections
Unclassified, Conference / Seminar
Suggestions
OpenMETU
Core
Fuzzy querying im XML databases
Üstünkaya, Ekin; Yazıcı, Adnan; Department of Computer Engineering (2004)
Real-world information containing subjective opinions and judgments has emerged the need to represent complex and imprecise data in databases. Additionally, the challenge of transferring information between databases whose data storage methods are not compatible has been an important research topic. Extensible Markup Language (XML) has the potential to meet these challenges since it has the ability to represent complex and imprecise data. In this thesis, an XML based fuzzy data representation and querying s...
On Fuzzy Extensions to Energy Ontologies for Text Processing Applications
Kucuk, Dilek; Kucuk, Dogan; Yazıcı, Adnan (2014-10-28)
Ubiquitous application areas of domain ontologies include text processing applications like categorizing related documents of the domain, extraction of information from these documents, and semantic search. In this paper, we focus on the utilization of two energy ontologies, one for electrical power quality and the second for wind energy, within such applications. For this purpose, we present fuzzy extensions to these domain ontologies as fuzziness is an essential feature of the ultimate forms of the ontolo...
Novel Optimization Models to Generalize Deep Metric Learning
Gürbüz, Yeti Ziya; Alatan, Abdullah Aydın; Department of Electrical and Electronics Engineering (2022-8-24)
Deep metric learning (DML) aims to fit a parametric embedding function to data of semantic information (e.g. images) so that l2-distance between embedded samples is low whenever they share similar semantic entities. An embedding function of such behavior is attained by minimizing empirical expected pairwise loss that penalizes inter-/intra-class proximity violations in embedding space. Proxy-based methods which use a learnable embedding vector per class in their loss formulation are state-of-the-art. We fir...
Fuzzy data representation and querying in XML database
Ustunkaya, Ekin; Yazıcı, Adnan; George, Roy (2007-02-01)
Real-world information including subjective opinions and judgments need imprecise data to be modeled for representation and querying in databases. The Extensible Markup Language (XML) has become a de-facto standard for data modeling and exchange in recent years. Efforts on modeling imprecision and representing such data in XML have not been fully developed. In this paper, an XML based fuzzy data representation and querying system is presented. Complex and imprecise data are represented using a fuzzy extensi...
Uncertainty in a nested relational database model
Yazıcı, Adnan; Buckles, BP; Petry, FE (1999-07-01)
Some database models have already been developed to deal with complex values but they have constrains that data stored is precise and queries are crisp. However, as many researchers have pointed out, there is a need to present, manipulate, and query complex and uncertain data of various non-traditional database applications such as oceanography, multimedia, meteorology, office automation systems, engineering designs, expert database systems and geographic information systems. In this paper, we present a log...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
J. R. Campana, J. M. Medina, and M. A. Vila, “Semantic Processing of Database Textual Attributes Using Wikipedia,” Ghent, BELGIUM, 2011, vol. 7022, p. 84, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/66556.