Ontology based information extraction on free text radiological reports using natural language processing approach

Soysal, Ergin
This thesis describes an information extraction system that is designed to process free text Turkish radiology reports in order to extract and convert the available information into a structured information model. The system uses natural language processing techniques together with domain ontology in order to transform the verbal descriptions into a target information model, so that they can be used for computational purposes. The developed domain ontology is effectively used in entity recognition and relation extraction phases of the information extraction task. The ontology provides the flexibility in the design of extraction rules, and the structure of the ontology also determines the information model that describes the structure of the extracted semantic information. In addition, some of the missing terms in the sentences are identified with the help of the ontology. One of the main contributions of this thesis is the usage of ontology in information extraction that increases the expressive power of extraction rules and helps to determine missing items in the sentences. The system is the first information extraction system for Turkish texts. Since Turkish is a morphologically rich language, the system uses a morphological analyzer and the extraction rules are also based on the morphological features. TRIES achieved 93% recall and 98% precision results in the performance evaluations.


Design and evaluation of an ontology based information extraction system for radiological reports
Soysal, Ergin; Cicekli, Ilyas; Baykal, Nazife (2010-11-01)
This paper describes an information extraction system that extracts and converts the available information in free text Turkish radiology reports into a structured information model using manually created extraction rules and domain ontology. The ontology provides flexibility in the design of extraction rules, and determines the information model for the extracted semantic information. Although our information extraction system mainly concentrates on abdominal radiology reports, the system can be used in an...
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Karamanlıoğlu, Alper; Alpaslan, Ferda Nur; Department of Computer Engineering (2017)
In this thesis, an expert system developed with an ontology-based approach to detect Service Level Agreement (SLA) violations is presented. Ontologies represent explicit formal specifications of the concepts in a particular domain and the relationships among them. Expert systems, however, are frequently employed with ontologies because of their reasoning capabilities. The widespread use of SLAs in various areas complicates SLA management and in particular the detection of violations. Although it is necessar...
Ontological Video Annotation and Querying System for Soccer Games
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Ontology based semantic retrieval of video contents using metadata
Akpınar, Samet; Alpaslan, Ferda Nur; Department of Computer Engineering (2007)
The aim of this thesis is the development of an infrastructure which is used for semantic retrieval of multimedia contents. Motivated by the needs of semantic search and retrieval of multimedia contents, operating directly on the MPEG-7 based annotations can be thought as a reasonable way for meeting these needs as MPEG-7 is a common standard providing a wide multimedia content description schema. However, it is clear that the MPEG-7 formalism is deficient about the semantics and reasoning support. From thi...
A framework for ranking and categorizing medical documents
Al Zamıl, Mohammed GH. I.; Betin Can, Aysu; Department of Information Systems (2010)
In this dissertation, we present a framework to enhance the retrieval, ranking, and categorization of text documents in medical domain. The contributions of this study are the introduction of a similarity model to retrieve and rank medical textdocuments and the introduction of rule-based categorization method based on lexical syntactic patterns features. We formulate the similarity model by combining three features to model the relationship among document and construct a document network. We aim to rank ret...
Citation Formats
E. Soysal, “Ontology based information extraction on free text radiological reports using natural language processing approach,” Ph.D. - Doctoral Program, Middle East Technical University, 2010.