An Improved Semantic Search Model Based on Hybrid Fuzzy Description Logic

2006 ◽  
Author(s):  
Ruixuan Li ◽  
Kunmei Wen ◽  
Zhengding Lu ◽  
Xiaolin Sun ◽  
Zhigang Wang
Keyword(s):  
Description Logic ◽  
Semantic Search ◽  
Search Model ◽  
Model Based ◽  
Fuzzy Description

Deciding Query Entailment for Fuzzy Description Logic Knowledge Bases：The f-SH Family

2012 ◽  
Vol 35 (4) ◽  
pp. 767-785
Author(s):  
Jing-Wei CHENG ◽  
Zong-Min MA ◽  
Li YAN ◽  
Fu ZHANG
Keyword(s):  
Description Logic ◽  
Fuzzy Description

Semantics of OWL-S process model based on temporal description logic

2013 ◽  
Vol 33 (1) ◽  
pp. 266-269 ◽  
Author(s):  
Ming LI ◽  
Shiyi LIU ◽  
Fuzhong NIAN
Keyword(s):  
Process Model ◽  
Description Logic ◽  
Model Based

A Lexical Search Model based on word association norms

2019 ◽  
Vol 36 (5) ◽  
pp. 4587-4597
Author(s):  
Jorge Reyes-Magaña ◽  
Gemma Bel-Enguix ◽  
Helena Gómez-Adorno ◽  
Gerardo Sierra
Keyword(s):  
Word Association ◽  
Search Model ◽  
Model Based

scholarly journals How Fuzzy Is My Fuzzy Description Logic?

2012 ◽  
pp. 82-96 ◽  
Author(s):  
Stefan Borgwardt ◽  
Felix Distel ◽  
Rafael Peñaloza
Keyword(s):  
Description Logic ◽  
Fuzzy Description

scholarly journals A Weakly Supervised Academic Search Model Based on Knowledge-Enhanced Feature Representation

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Mingying Xu ◽  
Junping Du ◽  
Feifei Kou ◽  
Meiyu Liang ◽  
Xin Xu ◽  
...  
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Feature Representation ◽  
Search Model ◽  
Model Based ◽  
Proposed Model ◽  
Cloud Server ◽  
Weakly Supervised ◽  
Internet Of Things Technology ◽  
Academic Search

Internet of Things search has great potential applications with the rapid development of Internet of Things technology. Combining Internet of Things technology and academic search to build academic search framework based on Internet of Things is an effective solution to realize massive academic resource search. Recently, the academic big data has been characterized by a large number of types and spanning many fields. The traditional web search technology is no longer suitable for the search environment of academic big data. Thus, this paper designs academic search framework based on Internet of Things Technology. In order to alleviate the pressure of the cloud server processing massive academic big data, the edge server is introduced to clean and remove the redundancy of the data to form a clean data for further analysis and processing by the cloud server. Edge computing network effectively makes up for the deficiency of cloud computing in the conditions of distributed and high concurrent access, reduces long-distance data transmission, and improves the quality of network user experience. For Academic Search, this paper proposes a novel weakly supervised academic search model based on knowledge-enhanced feature representation. The proposed model can relieve high cost of acquisition of manually labeled data by obtaining a lot of pseudolabeled data and consider word-level interactive matching and sentence-level semantic matching for more accurate matching in the process of academic search. The experimental result on academic datasets demonstrate that the performance of the proposed model is much better than that of the existing methods.

scholarly journals Capability-oriented architectural analysis method based on fuzzy description logic

2016 ◽  
Vol 13 (1) ◽  
pp. 287-308 ◽  
Author(s):  
Zhang Tingting ◽  
Liu Xiaoming ◽  
Wang Zhixue ◽  
Dong Qingchao
Keyword(s):  
Business Strategy ◽  
Domain Knowledge ◽  
Description Logic ◽  
Description Logics ◽  
Model Verification ◽  
Architectural Analysis ◽  
Requirements Modeling ◽  
Strategy Model ◽  
Domain Specific Modeling ◽  
Fuzzy Description

A number of problems may arise from architectural requirements modeling, including alignment of it with business strategy, model integration and handling the uncertain and vague information. The paper introduces a method for modeling architectural requirements in a way of ontology-based and capability-oriented requirements elicitation. The requirements can be modeled within a three-layer framework. The Capability Meta-concept Framework is provided at the top level. The domain experts can capture the domain knowledge within the framework, forming the domain ontology at the second level. The domain concepts can be used for extending the UML to produce a domain-specific modeling language. A fuzzy UML is introduced to model the vague and uncertain features of the capability requirements. An algorithm is provided to transform the fuzzy UML models into the fuzzy Description Logics ontology for model verification. A case study is given to demonstrate the applicability of the method.

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