scholarly journals A Resource Search Model Based on Semantically Enabled P2P Grid

2007 ◽  
Author(s):  
Jun Ye ◽  
Zhishu Li ◽  
Yanyan Ma ◽  
Qing Li
Keyword(s):  
Search Model ◽  
Model Based ◽  
Resource Search

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 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.

A Human Flesh Search Model Based on Multiple Effects

2020 ◽  
Vol 7 (3) ◽  
pp. 1394-1405
Author(s):  
Fuzhong Nian ◽  
Hongyuan Diao
Keyword(s):  
Search Model ◽  
Model Based ◽  
Human Flesh

An Incentive Search Model Based on Utility in CAN Network

2011 ◽  
Vol 30 (6) ◽  
pp. 1485-1488
Author(s):  
Yong-hao Li ◽  
Yun Liu ◽  
De-quan He
Keyword(s):  
Search Model ◽  
Model Based
Sign in / Sign up

Export Citation Format

Share Document