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Crowd-sourcing Updates of Large Knowledge Graphs

Albin Ahmeti, Víctor Mireles, Artem Revenko, Marta Sabou, Martin Schauer
2018 International Semantic Web Conference  
The method is most suitable for large knowledge graphs, for which it is unreasonable for a single curator to be aware of all the existing content.  ...  Users can provide their updates in an intuitive way without requiring expertise about the knowledge already contained in the graph.  ...  As part of this project, we are designing a web-based system which collects extensions to a large knowledge graph from the crowd of citizens which use the platform 4 .  ... 
dblp:conf/semweb/AhmetiMRSS18 fatcat:gzhgvsfdrjbwba6khoavn6l3vu

Crowd-Sourced Knowledge Graph Extension: A Belief Revision Based Approach

Artem Revenko, Marta Sabou, Albin Ahmeti, Martin Schauer
2018 AAAI Conference on Human Computation & Crowdsourcing  
This feedback enables the educational aspect of the approach. The approach guarantees the consistency of the crowd-sourced knowledge when it is being integrated into the knowledge graph.  ...  In this paper we introduce a novel crowd-sourcing approach that allows the crowdworkers to provide their update in a simplistic intuitive form without having the information about the knowledge already  ...  collects extensions to a large knowledge graph from a crowd of citizens which use this platform 4 .  ... 
dblp:conf/hcomp/RevenkoSAS18 fatcat:o4st7m5oxvf33n3k7okjoo2d3i

RoboBrain: Large-Scale Knowledge Engine for Robots [article]

Ashutosh Saxena, Ashesh Jain, Ozan Sener, Aditya Jami, Dipendra K. Misra, Hema S. Koppula
2015 arXiv   pre-print
In this paper we introduce a knowledge engine, which learns and shares knowledge representations, for robots to carry out a variety of tasks.  ...  The knowledge stored in the engine comes from multiple sources including physical interactions that robots have while performing tasks (perception, planning and control), knowledge bases from the Internet  ...  We also thank Yun Jiang, Ian Lenz, Jaeyong Sung, and Chenxia Wu for their contributions to the knowledge for RoboBrain.  ... 
arXiv:1412.0691v2 fatcat:nbqybxn3zne67l6ksq4phbz4ia

Geotagging: Systematic Anatomization and Conceptual Model for POI Verification

2020 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
This verified POI data can be used further in knowledge Graph creation to get better search facility.  ...  In this paper, we have explored the available techniques to improve and verify the crowd sourced data and propose a conceptual model to accomplish the objective of verifying and managing the geotagged  ...  Crowd Sourcing Platform Crowd Sourcing is the practice where large number of people involved in collecting the data contributing in any project / task allocated to them [48] .  ... 
doi:10.35940/ijitee.k7820.0991120 fatcat:twxah67m2vdldaweyqtrgvnh4a

A Survey of Techniques for Constructing Chinese Knowledge Graphs and Their Applications

Tianxing Wu, Guilin Qi, Cheng Li, Meng Wang
2018 Sustainability  
We first describe the background of OBOR, and then introduce the concept and development history of knowledge graph and typical Chinese knowledge graphs.  ...  Afterwards, we present the details of techniques for constructing Chinese knowledge graphs, and demonstrate several applications of Chinese knowledge graphs.  ...  Lytras who gave a lot of suggestions on how knowledge graphs impact the implementation of OBOR. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/su10093245 fatcat:wrqgfkwfanfejnffn6nyr4nqbq

Knowledge Graph Semantic Enhancement of Input Data for Improving AI

Shreyansh Bhatt, Amit Sheth, Valerie Shalin, Jinjin Zhao, Amit Sheth
2020 IEEE Internet Computing  
The term Knowledge Graph (KG) is in vogue as for many practical applications, it is convenient and useful to organize this background knowledge in the form of a graph.  ...  Intelligent systems designed using machine learning algorithms require a large number of labeled data.  ...  The knowledge graph is updated based on the results and the application-specific objective optimization is then run for a KG, which leads to an improved (application-specific) representation of the KG.  ... 
doi:10.1109/mic.2020.2979620 fatcat:q4xrsmddnfbvzjhev4xqknfo64

Efficient Reasoning upon Fusion of Many Data Sources

Chase Alexander Yakaboski, Eugene Santos
2021 Proceedings of the ... International Florida Artificial Intelligence Research Society Conference  
Past research has focused on knowledge fusion situations that only involve a limited number of sources.  ...  Bayesian Knowledge Bases (BKB), a graphical model for representing structured probabilistic information, allow for efficient fusion of knowledge from multiple sources.  ...  As I-nodes are random variable instantiations, then Reproduce Ability = Low and Over Crowd = No would be examples of I-nodes in our correlation graph.  ... 
doi:10.32473/flairs.v34i1.128539 fatcat:2ohr4ypza5ecto6l6z5ckjqzky

Arnold: Declarative Crowd-Machine Data Integration

Shawn R. Jeffery, Liwen Sun, Matt DeLand, Nick Pendar, Rick Barber, Andrew Galdi
2013 Conference on Innovative Data Systems Research  
Human input, or crowd-sourcing, is an effective tool to help produce such high-quality data. It is infeasible, however, to involve humans at every step of the data cleaning process for all data.  ...  We have developed a declarative approach to data cleaning and integration that balances when and where to apply crowd-sourcing and machine computation using a new type of data independence that we term  ...  When utilizing crowd-sourcing at large scale, however, such knowledge is largely inaccessible to an application developer.  ... 
dblp:conf/cidr/JefferySDPBG13 fatcat:22alxihccvdc5d3ca5pcubeq5y

Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD)

Alwatben Batoul Rashed, Hazlina Hamdan, Nurfadhlina Mohd Sharef, Md Nasir Sulaiman, Razali Yaakob, Mansir Abubakar
2020 IJAIN (International Journal of Advances in Intelligent Informatics)  
According to the literature, crowding distance is one of the most efficient algorithms that was developed based on density measures to treat the problem of selection mechanism for archive updates.  ...  Generally, clustering is difficult and complex phenomenon, where the appropriate numbers of clusters are always unknown, comes with a large number of potential solutions, and as well the datasets are unsupervised  ...  Archive update Crowding distance is first sorted in ascending order of the computed objective function values of the set of solutions.  ... 
doi:10.26555/ijain.v6i1.366 fatcat:rjuqbdiikvh37o5z75bpamtj74

Fault-Tolerant Entity Resolution with the Crowd [article]

Anja Gruenheid and Besmira Nushi and Tim Kraska and Wolfgang Gatterbauer and Donald Kossmann
2015 arXiv   pre-print
Although the crowd generates insightful information especially for complex problems such as entity resolution (ER), the output quality of crowd workers is often noisy.  ...  The challenge that we address in this paper is how to minimize the cost for task requesters while maximizing ER result quality under the assumption of unreliable input from the crowd.  ...  Knowledge Graph [31] or the Facebook Entities Graph [32] .  ... 
arXiv:1512.00537v1 fatcat:cfkaaju3kndnbezglerqvyfs54

Hybrid Graph Neural Networks for Crowd Counting [article]

Ao Luo, Fan Yang, Xin Li, Dong Nie, Zhicheng Jiao, Shangchen Zhou and Hong Cheng
2020 arXiv   pre-print
Crowd counting is an important yet challenging task due to the large scale and density variation.  ...  Specifically, HyGnn integrates a hybrid graph to jointly represent the task-specific feature maps of different scales as nodes, and two types of relations as edges:(i) multi-scale relations for capturing  ...  Introduction Crowd counting, with the purpose of analyzing large crowds quickly, is a crucial yet challenging computer vision and AI task.  ... 
arXiv:2002.00092v1 fatcat:4avijoqgh5aivkhniffzqlhc4y

Improving Situational Awareness In Emergencies Through Crowd Supported Analysis Of Social Media

Jakob Rogstadius, Vassilis Kostakos, Jim Laredo, Maja Vukovic
2011 Zenodo  
streams of status updates into actionable pieces of information.  ...  Through a combination of algorithmic and crowdsourcing techniques, the proposed system gathers, analyzes, organizes and then visualizes social media activity around an event in real-time and turns overwhelming  ...  the unique human capabilities to adapt to new situations, prioritize information, infer knowledge, estimate trust and question sources.  ... 
doi:10.5281/zenodo.1117407 fatcat:q3tjoxzojzhnfmjbzs6bh42uva

Hybrid Graph Neural Networks for Crowd Counting

Ao Luo, Fan Yang, Xin Li, Dong Nie, Zhicheng Jiao, Shangchen Zhou, Hong Cheng
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
Crowd counting is an important yet challenging task due to the large scale and density variation.  ...  Specifically, HyGnn integrates a hybrid graph to jointly represent the task-specific feature maps of different scales as nodes, and two types of relations as edges: (i) multi-scale relations capturing  ...  This work was supported in part by the National Key R&D Program of China (No.2017YFB1302300) and the NSFC (No.U1613223).  ... 
doi:10.1609/aaai.v34i07.6839 fatcat:us2dcwyueffjro5oqi344bvdi4

Sources of Change for Modern Knowledge Organization Systems

Michael Lauruhn, Paul Groth
2016 Knowledge organization  
He is currently a member of the Dublin Core Metadata Initiative's Governing Board.  ...  Before joining Labs in 2010, he held consulting and technical positions helping large companies and organizations define and implement taxonomies and metadata schemas.  ...  However, this is an increasingly active field because of application of knowledge bases in large-scale search by the likes of Google and Microsoft under the heading of knowledge graphs (Dong, et al. 2014  ... 
doi:10.5771/0943-7444-2016-8-622 fatcat:7mfeurwpanhxvfey4eqdq73p3y

Cloud Update of Geodetic Normal Distribution Map Based on Crowd-Sourcing Detection against Road Environment Changes

Chansoo Kim, Sungjin Cho, Myoungho Sunwoo, Paulo Resende, Benazouz Bradaï, Kichun Jo
2022 Journal of Advanced Transportation  
Unfortunately, a point cloud map occupies too large data size to transmit data in the uploading and downloading of the map update framework.  ...  The proposed GND map update framework comprises two parts: map change detection based on crowd-sourcing vehicles and map updating based on a map cloud server.  ...  However, to the best of our knowledge, no crowd-sourced data-based map update systems currently exist for other geometric map structures.  ... 
doi:10.1155/2022/4486177 doaj:daacb0cbfc5d45cfbfc2c9a31d0281b1 fatcat:royjlfialfeb7oarqi5npuopkq
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