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A Semantic Retrieval System for Extracting Relationships from Biological Corpus


Affiliations
1 Department of Information Systems, Benha University, Egypt
 

The World Wide Web holds a large size of different information. Sometimes while searching the World Wide Web, users always do not gain the type of information they expect. In the subject of information extraction, extracting semantic relationships between terms from documents become a challenge. This paper proposes a system helps in retrieving documents based on the query expansion and tackles the extracting of semantic relationships from biological documents. This system retrieved documents that are relevant to the input terms then it extracts the existence of a relationship. In this system, we use Boolean model and the pattern recognition which helps in determining the relevant documents and determining the place of the relationship in the biological document. The system constructs a term-relation table that accelerates the relation extracting part. The proposed method offers another usage of the system so the researchers can use it to figure out the relationship between two biological terms through the available information in the biological documents. Also for the retrieved documents, the system measures the percentage of the precision and recall.

Keywords

Inverted List, Information Retrieval, Gene Ontology, Information Extraction, Relationship Extraction, Pattern Recognition.
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Abstract Views: 358

PDF Views: 151




  • A Semantic Retrieval System for Extracting Relationships from Biological Corpus

Abstract Views: 358  |  PDF Views: 151

Authors

Hassan Mahmoud
Department of Information Systems, Benha University, Egypt
Saif Salah Kareem
Department of Information Systems, Benha University, Egypt
El-Shishtawy Tarek
Department of Information Systems, Benha University, Egypt

Abstract


The World Wide Web holds a large size of different information. Sometimes while searching the World Wide Web, users always do not gain the type of information they expect. In the subject of information extraction, extracting semantic relationships between terms from documents become a challenge. This paper proposes a system helps in retrieving documents based on the query expansion and tackles the extracting of semantic relationships from biological documents. This system retrieved documents that are relevant to the input terms then it extracts the existence of a relationship. In this system, we use Boolean model and the pattern recognition which helps in determining the relevant documents and determining the place of the relationship in the biological document. The system constructs a term-relation table that accelerates the relation extracting part. The proposed method offers another usage of the system so the researchers can use it to figure out the relationship between two biological terms through the available information in the biological documents. Also for the retrieved documents, the system measures the percentage of the precision and recall.

Keywords


Inverted List, Information Retrieval, Gene Ontology, Information Extraction, Relationship Extraction, Pattern Recognition.

References