scholarly journals Approaches to measure class importance in Knowledge Graphs

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252862
Author(s):  
Daniel Fernández-Álvarez ◽  
Johannes Frey ◽  
Jose Emilio Labra Gayo ◽  
Daniel Gayo-Avello ◽  
Sebastian Hellmann
Keyword(s):  
Linked Data ◽  
State Of The Art ◽  
Data Summarization ◽  
The Core ◽  
Novel Approach ◽  
Core Elements ◽  
Importance Ranking ◽  
Knowledge Graphs ◽  
Measure Class ◽  
Excellent Tool

The amount, size, complexity, and importance of Knowledge Graphs (KGs) have increased during the last decade. Many different communities have chosen to publish their datasets using Linked Data principles, which favors the integration of this information with many other sources published using the same principles and technologies. Such a scenario requires to develop techniques of Linked Data Summarization. The concept of a class is one of the core elements used to define the ontologies which sustain most of the existing KGs. Moreover, classes are an excellent tool to refer to an abstract idea which groups many individuals (or instances) in the context of a given KG, which is handy to use when producing summaries of its content. Rankings of class importance are a powerful summarization tool that can be used both to obtain a superficial view of the content of a given KG and to prioritize many different actions over the data (data quality checking, visualization, relevance for search engines…). In this paper, we analyze existing techniques to measure class importance and propose a novel approach called ClassRank. We compare the class usage in SPARQL logs of different KGs with the importance ranking produced by the approaches evaluated. Then, we discuss the strengths and weaknesses of the evaluated techniques. Our experimentation suggests that ClassRank outperforms state-of-the-art approaches measuring class importance.

scholarly journals Sampo-UI: A full stack JavaScript framework for developing semantic portal user interfaces

Semantic Web ◽  
2021 ◽  
pp. 1-16
Author(s):  
Esko Ikkala ◽  
Eero Hyvönen ◽  
Heikki Rantala ◽  
Mikko Koho
Keyword(s):  
User Interfaces ◽  
Linked Data ◽  
State Of The Art ◽  
Software Framework ◽  
End User ◽  
Faceted Search ◽  
Software Developer ◽  
Current State ◽  
Knowledge Graphs ◽  
User Friendly

This paper presents a new software framework, Sampo-UI, for developing user interfaces for semantic portals. The goal is to provide the end-user with multiple application perspectives to Linked Data knowledge graphs, and a two-step usage cycle based on faceted search combined with ready-to-use tooling for data analysis. For the software developer, the Sampo-UI framework makes it possible to create highly customizable, user-friendly, and responsive user interfaces using current state-of-the-art JavaScript libraries and data from SPARQL endpoints, while saving substantial coding effort. Sampo-UI is published on GitHub under the open MIT License and has been utilized in several internal and external projects. The framework has been used thus far in creating six published and five forth-coming portals, mostly related to the Cultural Heritage domain, that have had tens of thousands of end-users on the Web.

scholarly journals Fact Checking via Evidence Patterns

2018 ◽  
Author(s):  
Valeria Fionda ◽  
Giuseppe Pirrò
Keyword(s):  
Query Language ◽  
State Of The Art ◽  
Sparql Query ◽  
Efficient Algorithms ◽  
The State ◽  
The Core ◽  
Numerical Assessment ◽  
Comparable Accuracy ◽  
Fact Checking ◽  
Knowledge Graphs

We tackle fact checking using Knowledge Graphs (KGs) as a source of background knowledge. Our approach leverages the KG schema to generate candidate evidence patterns, that is, schema-level paths that capture the semantics of a target fact in alternative ways. Patterns verified in the data are used to both assemble semantic evidence for a fact and provide a numerical assessment of its truthfulness. We present efficient algorithms to generate and verify evidence patterns, and assemble evidence. We also provide a translation of the core of our algorithms into the SPARQL query language. Not only our approach is faster than the state of the art and offers comparable accuracy, but it can also use any SPARQL-enabled KG.

scholarly journals Dual Quaternion Embeddings for Link Prediction

2021 ◽  
Vol 11 (12) ◽  
pp. 5572
Author(s):  
Liming Gao ◽  
Huiling Zhu ◽  
Hankz Hankui Zhuo ◽  
Jin Xu 
Keyword(s):  
Artificial Intelligence ◽  
Link Prediction ◽  
State Of The Art ◽  
Knowledge Graph ◽  
Dual Quaternion ◽  
Novel Approach ◽  
Quaternion Space ◽  
Knowledge Graphs ◽  
Low Dimensional

The applications of knowledge graph have received much attention in the field of artificial intelligence. The quality of knowledge graphs is, however, often influenced by missing facts. To predict the missing facts, various solid transformation based models have been proposed by mapping knowledge graphs into low dimensional spaces. However, most of the existing transformation based approaches ignore that there are multiple relations between two entities, which is common in the real world. In order to address this challenge, we propose a novel approach called DualQuatE that maps entities and relations into a dual quaternion space. Specifically, entities are represented by pure quaternions and relations are modeled based on the combination of rotation and translation from head to tail entities. After that we utilize interactions of different translations and rotations to distinguish various relations between head and tail entities. Experimental results exhibit that the performance of DualQuatE is competitive compared to the existing state-of-the-art models.

What is the Core Elements of Social Innovation?

2019 ◽  
Vol 45 ◽  
pp. 83-109
Author(s):  
SangMi Cho ◽  
JongSerl Chun ◽  
SoYoung An ◽  
JiYeon Jung
Keyword(s):  
Social Innovation ◽  
The Core ◽  
Core Elements

Duoethnography: A Polytheoretical Approach to (Re)Storing, (Re)Storying the Meanings That One Gives

2020 ◽  
pp. 396-423
Author(s):  
John Joseph Norris ◽  
Richard D. Sawyer
Keyword(s):  
Social Justice ◽  
Critical Theory ◽  
Third Space ◽  
The Third ◽  
The Core ◽  
Wide Range ◽  
Core Elements ◽  
Feminist Inquiry

This chapter summarizes the advancement of duoethnography throughout its fifteen-year history, employing examples from a variety of topics in education and social justice to provide a wide range of approaches that one may take when conducting a duoethnography. A checklist articulates what its cofounders consider the core elements of duoethnographies, additional features that may or may not be employed and how some studies purporting to be duoethnographies may not be so. The chapter indicates connections between duoethnography and a number of methodological concepts including the third space, the problematics of representation, feminist inquiry, and critical theory using published examples by several duoethnographers.

scholarly journals 178. Implementation of the Core Elements of Antibiotic Stewardship in Nursing Homes – National Healthcare Safety Network (NHSN), 2016–2018

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S96-S96
Author(s):  
Katryna A Gouin ◽  
Sarah Kabbani; Angela Anttila ◽  
Josephine Mak ◽  
Elisabeth Mungai ◽  
Ti Tanissha McCray ◽  
...  
Keyword(s):  
Nursing Homes ◽  
Antibiotic Stewardship ◽  
Care Facility ◽  
Antibiotic Use ◽  
Infection Prevention And Control ◽  
Term Care ◽  
Long Term Care Facility ◽  
The Core ◽  
Use Of Resources ◽  
Core Elements

Abstract Background Since 2016, nursing homes (NHs) enrolled in the Centers for Disease Control and Prevention’s NHSN Long-term Care Facility (LTCF) Component have reported on their implementation of the core elements of antibiotic stewardship. In 2016, 42% of NHs reported implementing all seven core elements. Recent regulations require antibiotic stewardship programs in NHs. The objectives of this analysis were to track national progress in implementation of the core elements and evaluate how time dedicated to infection prevention and control (IPC) is associated with the implementation of the core elements. Methods We used the NHSN LTCF 2016–2018 Annual Surveys to assess NH characteristics and implementation of the core elements, defined as self-reported implementation of at least one corresponding stewardship activity. We reported absolute differences in percent implementation. We used log-binomial regression models to estimate the association between weekly IPC hours and the implementation of all seven core elements, while controlling for confounding by facility characteristics. Results We included 7,506 surveys from 2016–2018. In 2018, 71% of NHs reported implementation of all seven core elements, a 28% increase from 2016 (Fig. 1). The greatest increases in implementation from 2016–2018 were in Education (+19%), Reporting (+18%) and Drug Expertise (+15%) (Fig. 2). Ninety-eight percent of NHs had an individual responsible for antibiotic stewardship activities (Accountability), with 30% indicating that the role was fulfilled by an infection preventionist. Furthermore, 71% of NHs reported pharmacist involvement in improving antibiotic use, an increase of 27% since 2016. NHs that reported at least 20 hours of IPC activity per week were 14% more likely to implement all seven core elements, when controlling for facility ownership and affiliation, 95% CI: (1.07, 1.20). Conclusion NHs reported substantial progress in antibiotic stewardship implementation from 2016–2018. Improvements in accessing drug expertise, providing education and reporting antibiotic use may reflect increased stewardship awareness and use of resources among NH providers under new regulatory requirements. NHs with at least 20 hours dedicated to IPC per week may have greater capacity to implement all core elements. Disclosures All Authors: No reported disclosures

scholarly journals Deep Learning for Transient Image Reconstruction from ToF Data

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1962
Author(s):  
Enrico Buratto ◽  
Adriano Simonetto ◽  
Gianluca Agresti ◽  
Henrik Schäfer ◽  
Pietro Zanuttigh
Keyword(s):  
Deep Learning ◽  
State Of The Art ◽  
Light Response ◽  
Real Data ◽  
Depth Image ◽  
Learning Approach ◽  
Multiple Reflections ◽  
Noisy Input ◽  
Novel Approach ◽  
Incoming Light

In this work, we propose a novel approach for correcting multi-path interference (MPI) in Time-of-Flight (ToF) cameras by estimating the direct and global components of the incoming light. MPI is an error source linked to the multiple reflections of light inside a scene; each sensor pixel receives information coming from different light paths which generally leads to an overestimation of the depth. We introduce a novel deep learning approach, which estimates the structure of the time-dependent scene impulse response and from it recovers a depth image with a reduced amount of MPI. The model consists of two main blocks: a predictive model that learns a compact encoded representation of the backscattering vector from the noisy input data and a fixed backscattering model which translates the encoded representation into the high dimensional light response. Experimental results on real data show the effectiveness of the proposed approach, which reaches state-of-the-art performances.

scholarly journals A New Multi-Person Pose Estimation Method Using the Partitioned CenterPose Network

2021 ◽  
Vol 11 (9) ◽  
pp. 4241
Author(s):  
Jiahua Wu ◽  
Hyo Jong Lee
Keyword(s):  
Pose Estimation ◽  
Human Body ◽  
State Of The Art ◽  
Estimation Method ◽  
Bottom Up ◽  
Center Point ◽  
Novel Approach ◽  
Body Joints

In bottom-up multi-person pose estimation, grouping joint candidates into the appropriately structured corresponding instance of a person is challenging. In this paper, a new bottom-up method, the Partitioned CenterPose (PCP) Network, is proposed to better cluster the detected joints. To achieve this goal, we propose a novel approach called Partition Pose Representation (PPR) which integrates the instance of a person and its body joints based on joint offset. PPR leverages information about the center of the human body and the offsets between that center point and the positions of the body’s joints to encode human poses accurately. To enhance the relationships between body joints, we divide the human body into five parts, and then, we generate a sub-PPR for each part. Based on this PPR, the PCP Network can detect people and their body joints simultaneously, then group all body joints according to joint offset. Moreover, an improved l1 loss is designed to more accurately measure joint offset. Using the COCO keypoints and CrowdPose datasets for testing, it was found that the performance of the proposed method is on par with that of existing state-of-the-art bottom-up methods in terms of accuracy and speed.

scholarly journals TransET: Knowledge Graph Embedding with Entity Types

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1407
Author(s):  
Peng Wang ◽  
Jing Zhou ◽  
Yuzhang Liu ◽  
Xingchen Zhou
Keyword(s):  
Link Prediction ◽  
State Of The Art ◽  
Score Function ◽  
Graph Embedding ◽  
Vector Spaces ◽  
Knowledge Graph ◽  
Semantic Features ◽  
Knowledge Graphs ◽  
Real World Datasets ◽  
Low Dimensional

Knowledge graph embedding aims to embed entities and relations into low-dimensional vector spaces. Most existing methods only focus on triple facts in knowledge graphs. In addition, models based on translation or distance measurement cannot fully represent complex relations. As well-constructed prior knowledge, entity types can be employed to learn the representations of entities and relations. In this paper, we propose a novel knowledge graph embedding model named TransET, which takes advantage of entity types to learn more semantic features. More specifically, circle convolution based on the embeddings of entity and entity types is utilized to map head entity and tail entity to type-specific representations, then translation-based score function is used to learn the presentation triples. We evaluated our model on real-world datasets with two benchmark tasks of link prediction and triple classification. Experimental results demonstrate that it outperforms state-of-the-art models in most cases.

Webside manner: maskless communication

Diagnosis ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Ankit Mehta ◽  
Benji K. Mathews
Keyword(s):  
Communication Skills ◽  
Rapid Expansion ◽  
Technical Aspects ◽  
The Core ◽  
Core Elements ◽  
Virtual Visits ◽  
Virtual Platform ◽  
Structured Approach

Abstract Telemedicine has seen a rapid expansion lately, with virtual visits ushering in telediagnosis. Given the shift in the interpersonal and technical aspects of communications in a virtual visit, it is prudent to understand its effect on the patient-provider relationships. A range of interpersonal and communication skills can be utilized during telemedicine consultations in establishing relationships, and reaching a diagnosis. We propose a construct of “webside manner,” a structured approach to ensure the core elements of bedside etiquette are translated into the virtual encounter. This approach entails the totality of any interpersonal exchange on a virtual platform, to ensure a clinician’s presence, empathy and compassion is translated through this medium.

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