Collective Entity Disambiguation Based on Hierarchical Semantic Similarity

2020 ◽  
Vol 16 (2) ◽  
pp. 1-17 ◽  
Author(s):  
Bingjing Jia ◽  
Hu Yang ◽  
Bin Wu ◽  
Ying Xing
Keyword(s):  
Semantic Similarity ◽  
Semantic Matching ◽  
Sources Of Information ◽  
Multiple Sources ◽  
Global Features ◽  
Global Coherence ◽  
Similarity Model ◽  
Benchmark Datasets ◽  
Entity Disambiguation ◽  
Multiple Granularities

Entity disambiguation involves mapping mentions in texts to the corresponding entities in a given knowledge base. Most previous approaches were based on handcrafted features and failed to capture semantic information over multiple granularities. For accurately disambiguating entities, various information aspects of mentions and entities should be used in. This article proposes a hierarchical semantic similarity model to find important clues related to mentions and entities based on multiple sources of information, such as contexts of the mentions, entity descriptions and categories. This model can effectively measure the semantic matching between mentions and target entities. Global features are also added, including prior popularity and global coherence, to improve the performance. In order to verify the effect of hierarchical semantic similarity model combined with global features, named HSSMGF, experiments were carried out on five publicly available benchmark datasets. Results demonstrate the proposed method is very effective in the case that documents have more mentions.

Supporting the Development of Clinical Reasoning of Preprofessional Novices in Dysphagia Management

2019 ◽  
Vol 40 (03) ◽  
pp. 151-161 ◽  
Author(s):  
Sebastian Doeltgen ◽  
Stacie Attrill ◽  
Joanne Murray
Keyword(s):  
Clinical Reasoning ◽  
Clinical Decision Making ◽  
Management Practice ◽  
Clinical Decision ◽  
Assessment Process ◽  
Evidence Based ◽  
Sources Of Information ◽  
Multiple Sources ◽  
Implicit Processing ◽  
Reasoning Skills

AbstractProficient clinical reasoning is a critical skill in high-quality, evidence-based management of swallowing impairment (dysphagia). Clinical reasoning in this area of practice is a cognitively complex process, as it requires synthesis of multiple sources of information that are generated during a thorough, evidence-based assessment process and which are moderated by the patient's individual situations, including their social and demographic circumstances, comorbidities, or other health concerns. A growing body of health and medical literature demonstrates that clinical reasoning skills develop with increasing exposure to clinical cases and that the approaches to clinical reasoning differ between novices and experts. It appears that it is not the amount of knowledge held, but the way it is used, that distinguishes a novice from an experienced clinician. In this article, we review the roles of explicit and implicit processing as well as illness scripts in clinical decision making across the continuum of medical expertise and discuss how they relate to the clinical management of swallowing impairment. We also reflect on how this literature may inform educational curricula that support SLP students in developing preclinical reasoning skills that facilitate their transition to early clinical practice. Specifically, we discuss the role of case-based curricula to assist students to develop a meta-cognitive awareness of the different approaches to clinical reasoning, their own capabilities and preferences, and how and when to apply these in dysphagia management practice.

Single-shot Semantic Matching Network for Moment Localization in Videos

2021 ◽  
Vol 17 (3) ◽  
pp. 1-14
Author(s):  
Xinfang Liu ◽  
Xiushan Nie ◽  
Junya Teng ◽  
Li Lian ◽  
Yilong Yin
Keyword(s):  
Natural Language ◽  
Fixed Number ◽  
Single Shot ◽  
Semantic Matching ◽  
Matching Network ◽  
Attention Model ◽  
Semantic Relationships ◽  
Natural Language Query ◽  
Benchmark Datasets ◽  
Short Memory

Moment localization in videos using natural language refers to finding the most relevant segment from videos given a natural language query. Most of the existing methods require video segment candidates for further matching with the query, which leads to extra computational costs, and they may also not locate the relevant moments under any length evaluated. To address these issues, we present a lightweight single-shot semantic matching network (SSMN) to avoid the complex computations required to match the query and the segment candidates, and the proposed SSMN can locate moments of any length theoretically. Using the proposed SSMN, video features are first uniformly sampled to a fixed number, while the query sentence features are generated and enhanced by GloVe, long-term short memory (LSTM), and soft-attention modules. Subsequently, the video features and sentence features are fed to an enhanced cross-modal attention model to mine the semantic relationships between vision and language. Finally, a score predictor and a location predictor are designed to locate the start and stop indexes of the query moment. We evaluate the proposed method on two benchmark datasets and the experimental results demonstrate that SSMN outperforms state-of-the-art methods in both precision and efficiency.

scholarly journals Mobility Trends before and after the Pandemic Outbreak: Analyzing the Metropolitan Area of Barcelona through the Lens of Equality and Sustainability

2021 ◽  
Vol 13 (14) ◽  
pp. 7908
Author(s):  
Lucía Mejía-Dorantes ◽  
Lídia Montero ◽  
Jaume Barceló
Keyword(s):  
Metropolitan Area ◽  
Spatial Arrangement ◽  
Individual Characteristics ◽  
Sources Of Information ◽  
Mobility Patterns ◽  
Multiple Sources ◽  
Temporal Dimension ◽  
Population Groups ◽  
Highly Educated ◽  
Before And After

The spatial arrangement of a metropolis is of utmost importance to carry out daily activities, which are constrained by space and time. Accessibility is not only shaped by the spatial and temporal dimension, but it is also defined by individual characteristics, such as gender, impairments, or socioeconomic characteristics of the citizens living or commuting in this area. This study analyzes mobility trends and patterns in the metropolitan area of Barcelona before and after the COVID-19 pandemic outbreak, with special emphasis on gender and equality. The study draws on multiple sources of information; however, two main datasets are analyzed: two traditional travel surveys from the transport metropolitan area of Barcelona and two coming from smartphone data. The results show that gender plays a relevant role when analyzing mobility patterns, as already highlighted in other studies, but, after the pandemic outbreak, some population groups were more likely to change their mobility patterns, for example, highly educated population groups and those with higher income. This study also highlights that e-activities may shape new mobility patterns and living conditions for some population segments, but some activities cannot be replaced by IT technologies. For all these reasons, city and transport planning should foster sustainable development policies, which will provide the maximum benefit for society.

scholarly journals DRr-Net: Dynamic Re-Read Network for Sentence Semantic Matching

2019 ◽  
Vol 33 ◽  
pp. 7442-7449 ◽  
Author(s):  
Kun Zhang ◽  
Guangyi Lv ◽  
Linyuan Wang ◽  
Le Wu ◽  
Enhong Chen ◽  
...  
Keyword(s):  
Natural Language ◽  
Small Region ◽  
Psychological Research ◽  
Attention Mechanism ◽  
Semantic Relations ◽  
Semantic Matching ◽  
Close Attention ◽  
Original Sentence ◽  
Benchmark Datasets ◽  
Sentence Matching

Sentence semantic matching requires an agent to determine the semantic relation between two sentences, which is widely used in various natural language tasks such as Natural Language Inference (NLI) and Paraphrase Identification (PI). Among all matching methods, attention mechanism plays an important role in capturing the semantic relations and properly aligning the elements of two sentences. Previous methods utilized attention mechanism to select important parts of sentences at one time. However, the important parts of the sentence during semantic matching are dynamically changing with the degree of sentence understanding. Selecting the important parts at one time may be insufficient for semantic understanding. To this end, we propose a Dynamic Re-read Network (DRr-Net) approach for sentence semantic matching, which is able to pay close attention to a small region of sentences at each step and re-read the important words for better sentence semantic understanding. To be specific, we first employ Attention Stack-GRU (ASG) unit to model the original sentence repeatedly and preserve all the information from bottom-most word embedding input to up-most recurrent output. Second, we utilize Dynamic Re-read (DRr) unit to pay close attention to one important word at one time with the consideration of learned information and re-read the important words for better sentence semantic understanding. Extensive experiments on three sentence matching benchmark datasets demonstrate that DRr-Net has the ability to model sentence semantic more precisely and significantly improve the performance of sentence semantic matching. In addition, it is very interesting that some of finding in our experiments are consistent with the findings of psychological research.

scholarly journals COVID-19 as an “Infodemic” in Public Health: Critical Role of the Social Media

2021 ◽  
Vol 9 ◽  
Author(s):  
Debanjan Banerjee ◽  
K. S. Meena
Keyword(s):  
Public Health ◽  
Social Media ◽  
Critical Role ◽  
Global Public Health ◽  
Sources Of Information ◽  
Multiple Sources ◽  
Health Crisis ◽  
Digital Platforms ◽  
The Impact

The Coronavirus disease 2019 (COVID-19) pandemic has emerged as a significant and global public health crisis. Besides the rising number of cases and fatalities, the outbreak has also affected economies, employment and policies alike. As billions are being isolated at their homes to contain the infection, the uncertainty gives rise to mass hysteria and panic. Amidst this, there has been a hidden epidemic of “information” that makes COVID-19 stand out as a “digital infodemic” from the earlier outbreaks. Repeated and detailed content about the virus, geographical statistics, and multiple sources of information can all lead to chronic stress and confusion at times of crisis. Added to this is the plethora of misinformation, rumor and conspiracy theories circulating every day. With increased digitalization, media penetration has increased with a more significant number of people aiding in the “information pollution.” In this article, we glance at the unique evolution of COVID-19 as an “infodemic” in the hands of social media and the impact it had on its spread and public reaction. We then look at the ways forward in which the role of social media (as well as other digital platforms) can be integrated into social and public health, for a better symbiosis, “digital balance” and pandemic preparedness for the ongoing crisis and the future.

scholarly journals Revisiting Persistent Neuronal Activity During Covert Spatial Attention

2021 ◽  
Vol 15 ◽  
Author(s):  
Julian L. Amengual ◽  
Suliann Ben Hamed
Keyword(s):  
Spatial Attention ◽  
Neural Representation ◽  
Persistent Activity ◽  
Sources Of Information ◽  
Multiple Sources ◽  
Oscillatory Dynamics ◽  
Attention Orienting ◽  
Related Information ◽  
Attention Tasks ◽  
Reduction Methods

Persistent activity has been observed in the prefrontal cortex (PFC), in particular during the delay periods of visual attention tasks. Classical approaches based on the average activity over multiple trials have revealed that such an activity encodes the information about the attentional instruction provided in such tasks. However, single-trial approaches have shown that activity in this area is rather sparse than persistent and highly heterogeneous not only within the trials but also between the different trials. Thus, this observation raised the question of how persistent the actually persistent attention-related prefrontal activity is and how it contributes to spatial attention. In this paper, we review recent evidence of precisely deconstructing the persistence of the neural activity in the PFC in the context of attention orienting. The inclusion of machine-learning methods for decoding the information reveals that attention orienting is a highly dynamic process, possessing intrinsic oscillatory dynamics working at multiple timescales spanning from milliseconds to minutes. Dimensionality reduction methods further show that this persistent activity dynamically incorporates multiple sources of information. This novel framework reflects a high complexity in the neural representation of the attention-related information in the PFC, and how its computational organization predicts behavior.

scholarly journals Design-Based Research: Definition, Characteristics, Application and Challenges

2019 ◽  
Vol 5 (1) ◽  
pp. 26-35
Author(s):  
Hamed Vaezi ◽  
Hossein Karimi Moonaghi ◽  
Reyhaneh Golbaf
Keyword(s):  
Medical Education ◽  
Practical Knowledge ◽  
Educational Innovation ◽  
Sources Of Information ◽  
Multiple Sources ◽  
Short Term ◽  
Web Based ◽  
Design Based Research ◽  
Definition Of ◽  
New Research

In recent years medical education has developed dramatically, but lecturers often cite the existence of a gap between theoretical and practical knowledge. In the first decade of the present century, new research methodology named “design-based research (DBR)” was developed, which most experts and journals refer to as a fundamental way to make changes in the quality and applicability of studies and educational research as well as to enhance and improve the practice of instruction. The aim of the present study was introducing design-based research and its concepts, features, applications, and challenges. A narrative review was conducted in 2018. For this purpose, authorized English academic database including Web of Science, Science Direct, Google Scholar, international database and library in medical research filed with keywords including “design-based research, definition of DBR, DBR applications, medical education, and DBR challenges” without date limitation until 2018.11.21 were screened. Overall, 68 articles were selected and after careful reading, 21 article with related subjects were selected for material extraction. The conclusion was made that DBR that combines empirical research with design-based theories could be considered as an effective method for understanding quality, time and the cause of the phenomenon of educational innovation in practice. Usually DBR is formed by initial evaluation of a problem that occurs in a particular context, and this assessment continues throughout design and implementation. One of the characteristics of DBR is the guiding team, which includes researchers, professionals, designers, managers, teachers, trainers and others whose expertise and knowledge may in some way help. The application of DBR in web-based training programs is quite evident. The probability of non-returns in short-term projects is one of the main challenges of DBR. Medical education has developed dramatically in recent years, but it has made little progress in promoting innovative research methodologies. DBR can be used as a bridge between theories and practice and provide the basis for close communication between researchers, designers, and participants. By applying sophisticated methods and multiple sources of information, the success rate of an intervention in a particular environment is assessed, which ultimately leads to improved theories.

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