scholarly journals Ontology-based Integration of Knowledge Base for Building an Intelligent Searching Chatbot

2021 ◽  
Vol 33 (9) ◽  
pp. 3101
Author(s):  
Hien D. Nguyen ◽  
Tuan-Vi Tran ◽  
Xuan-Thien Pham ◽  
Anh T. Huynh ◽  
Nhon V. Do
Keyword(s):  
Knowledge Base ◽  
Intelligent Searching

Application of Ontology Technology in Agricultural Information Retrieval

2013 ◽  
Vol 756-759 ◽  
pp. 1249-1253 ◽  
Author(s):  
Jin Cui Kang ◽  
Jing Long Gao
Keyword(s):  
Information Retrieval ◽  
Knowledge Base ◽  
Domain Knowledge ◽  
The Internet ◽  
Related Information ◽  
Agricultural Knowledge ◽  
Intelligent Searching ◽  
Knowledge Ontology

The agricultural information on the internet become more and more, it is very difficult to search accurate related information from such different information, in order to improve the efficiency of information retrieval on the internet, the intelligent searching technology of agricultural information based on ontology is proposed. The paper firstly introduces research on the agricultural ontology and information retrieval, and takes agriculture domain knowledge as research object, analyzes the characters of agricultural domain knowledge and semantics retrieval, then uses the agricultural ontology to make the structure of agriculture ontology knowledge, and constructs the related agricultural knowledge ontology and knowledge base, implementing the intelligent searching of the agricultural information. The results indicate that the application of agricultural ontology technology in the agricultural information retrieval not only achieves the intelligent retrieval of agricultural information, but also greatly improves the accuracy and reliability of agricultural information retrieval.

SPedia

2018 ◽  
pp. 1576-1596
Author(s):  
Muhammad Ahtisham Aslam ◽  
Naif Radi Aljohani
Keyword(s):  
Knowledge Base ◽  
Open Data ◽  
Data Publishing ◽  
High Quality ◽  
Scientific Publications ◽  
Sparql Endpoint ◽  
Web Of Data ◽  
Intelligent Searching ◽  
The Web

Producing the Linked Open Data (LOD) is getting potential to publish high-quality interlinked data. Publishing such data facilitates intelligent searching from the Web of data. In the context of scientific publications, data about millions of scientific documents published by hundreds and thousands of publishers is in silence as it is not published as open data and ultimately is not linked to other datasets. In this paper the authors present SPedia: a semantically enriched knowledge base of data about scientific documents. SPedia knowledge base provides information on more than nine million scientific documents, consisting of more than three hundred million RDF triples. These extracted datasets, allow users to put sophisticated queries by employing semantic Web techniques instead of relying on keyword-based searches. This paper also shows the quality of extracted data by performing sample queries through SPedia SPARQL Endpoint and analyzing results. Finally, the authors describe that how SPedia can serve as central hub for the cloud of LOD of scientific publications.

Research of Agricultural Information Management and Retrieval

2014 ◽  
Vol 989-994 ◽  
pp. 5630-5633
Author(s):  
Jun Feng Liang ◽  
Chun Jin ◽  
Lei Zhang ◽  
Xu Ning Liu
Keyword(s):  
Information Retrieval ◽  
Knowledge Base ◽  
Information Management ◽  
Scientific Knowledge ◽  
Information Organization ◽  
Agricultural Knowledge ◽  
Intelligent Searching ◽  
Knowledge Ontology

In order to improve the efficiency of agricultural information retrieval and provide the effect methods for the information retrieval of agricultural, the intelligent searching technology of agricultural information based on ontology is proposed. The paper firstly introduces the concept of ontology, analyzes the characters of agricultural knowledge, and constructs the related agricultural knowledge ontology and knowledge base, implementing the intelligent searching of the agricultural information. The results indicate that the research on agricultural ontology can contribute to organization and searching of agricultural scientific knowledge and provide methods for information organization and searching of agricultural knowledge.

SPedia

2017 ◽  
Vol 13 (1) ◽  
pp. 128-147 ◽  
Author(s):  
Muhammad Ahtisham Aslam ◽  
Naif Radi Aljohani
Keyword(s):  
Knowledge Base ◽  
Open Data ◽  
Data Publishing ◽  
High Quality ◽  
Scientific Publications ◽  
Sparql Endpoint ◽  
Web Of Data ◽  
Intelligent Searching ◽  
The Web

Producing the Linked Open Data (LOD) is getting potential to publish high-quality interlinked data. Publishing such data facilitates intelligent searching from the Web of data. In the context of scientific publications, data about millions of scientific documents published by hundreds and thousands of publishers is in silence as it is not published as open data and ultimately is not linked to other datasets. In this paper the authors present SPedia: a semantically enriched knowledge base of data about scientific documents. SPedia knowledge base provides information on more than nine million scientific documents, consisting of more than three hundred million RDF triples. These extracted datasets, allow users to put sophisticated queries by employing semantic Web techniques instead of relying on keyword-based searches. This paper also shows the quality of extracted data by performing sample queries through SPedia SPARQL Endpoint and analyzing results. Finally, the authors describe that how SPedia can serve as central hub for the cloud of LOD of scientific publications.

WinFriends: Building your English Knowledge-Base (Version 5.02)

2017 ◽  
Vol 20 (1) ◽  
pp. 208-220
Author(s):  
J. F. Coll
Keyword(s):  
Knowledge Base
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