scholarly journals A Multi-RNN Research Topic Prediction Model Based on Spatial Attention and Semantic Consistency-Based Scientific Influence Modeling

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Mingying Xu ◽  
Junping Du ◽  
Zeli Guan ◽  
Zhe Xue ◽  
Feifei Kou ◽  
...  
Keyword(s):  
Prediction Model ◽  
Computer Science ◽  
Spatial Attention ◽  
Research Field ◽  
Research Topic ◽  
Research Topics ◽  
Semantic Consistency ◽  
Model Based ◽  
Research Fields ◽  
Model Research

Computer science discipline includes many research fields, which mutually influence and promote each other’s development. This poses two great challenges of predicting the research topics of each research field. One is how to model fine-grained topic representation of a research field. The other is how to model research topic of different fields and keep the semantic consistency of research topics when learning the scientific influence context from other related fields. Unfortunately, the existing research topic prediction approaches cannot handle these two challenges. To solve these problems, we employ multiple different Recurrent Neural Network chains which model research topics of different fields and propose a research topic prediction model based on spatial attention and semantic consistency-based scientific influence modeling. Spatial attention is employed in field topic representation which can selectively extract the attributes from the field topics to distinguish the importance of field topic attributes. Semantic consistency-based scientific influence modeling maps research topics of different fields to a unified semantic space to obtain the scientific influence context of other related fields. Extensive experiment results on five related research fields in the computer science (CS) discipline show that the proposed model is superior to the most advanced methods and achieves good topic prediction performance.

scholarly journals The First Brazilian Symposium on Computer Music presents Brazilian computer music potentials - Caxambu, MG, 1994

2019 ◽  
Author(s):  
Mauricio Loureiro
Keyword(s):  
Computer Science ◽  
Computer Music ◽  
Traditional Music ◽  
Research Field ◽  
Academic Community ◽  
Research Fields ◽  
Discussion List ◽  
Music Research ◽  
One Year ◽  
The City

The main objective of this talk is to report on the First Brazilian Symposium on Computer Music, which occurred in August 1994, at the city of Caxambu, Minas Gerais, promoted by the UFMG. The meeting occurred one year after the creation of NUCOM, a group of young academics dedicated to this emerging research field in Brazil gathered as a discussion list. This quite exciting and fancy event at Hotel Gloria in Caxambu was able to imposingly launch the group to the national, as well as to the international academic community. First, due to the excellency of the event’s output and its daring program, that included 34 selected papers by researchers from various institutions from Argentina, Brazil, Canada, Denmark, France, Hong Kong, Mexico, UK, and USA, five lectures an two panels of discussion offered by researchers from the most advanced computer music research centers all over the world. The program also included eight concerts, two of them featuring traditional music, such as Bach, Mozart, and Brazilian music.Six computer music concerts presented 48 selected compositions submitted to the symposium. Second, as the symposium happened as apart of the 14th Congress of Brazilian Computer Science Society (SBC), the excellency of its output was able to attract the interest of SBC’s board of directors. They invited NUCOM to integrate the society as a Special Committee, which are sub-groups of SBC dedicated to specific computer science topics. At the end of the description, this report aims at raising questions, arguments, and debates about today’s format of NUCOM meetings, considering more seriously the interdisciplinary character of the methodologic approaches adopted by the field. Interdisciplinarity should be pursued by striving to contaminate a growing number of different topics of musical sciences, as well as of other research fields.

scholarly journals TrendNets: mapping emerging research trends from dynamic co-word networks via sparse representation

2019 ◽  
Vol 121 (3) ◽  
pp. 1583-1598 ◽  
Author(s):  
Marie Katsurai ◽  
Shunsuke Ono
Keyword(s):  
Traditional Approach ◽  
Synthetic Data ◽  
Matrix Decomposition ◽  
Research Field ◽  
Research Trends ◽  
Research Topics ◽  
Decomposition Approach ◽  
Research Fields ◽  
The Matrix ◽  
Word Representation

Abstract Mapping the knowledge structure from word co-occurrences in a collection of academic papers has been widely used to provide insight into the topic evolution in an arbitrary research field. In a traditional approach, the paper collection is first divided into temporal subsets, and then a co-word network is independently depicted in a 2D map to characterize each period’s trend. To effectively map emerging research trends from such a time-series of co-word networks, this paper presents TrendNets, a novel visualization methodology that highlights the rapid changes in edge weights over time. Specifically, we formulated a new convex optimization framework that decomposes the matrix constructed from dynamic co-word networks into a smooth part and a sparse part: the former represents stationary research topics, while the latter corresponds to bursty research topics. Simulation results on synthetic data demonstrated that our matrix decomposition approach achieved the best burst detection performance over four baseline methods. In experiments conducted using papers published in the past 16 years at three conferences in different fields, we showed the effectiveness of TrendNets compared to the traditional co-word representation. We have made our codes available on the Web to encourage scientific mapping in all research fields.

Online Prediction Model Based on New Kernel Method

2014 ◽  
Vol 7 (1) ◽  
pp. 107
Author(s):  
Ilyes Elaissi ◽  
Okba Taouali ◽  
Messaoud Hassani
Keyword(s):  
Prediction Model ◽  
Kernel Method ◽  
Model Based ◽  
Online Prediction

Research of Software Defect Prediction Model Based on ACO-SVM

2011 ◽  
Vol 34 (6) ◽  
pp. 1148-1154 ◽  
Author(s):  
Hui-Yan JIANG ◽  
Mao ZONG ◽  
Xiang-Ying LIU
Keyword(s):  
Prediction Model ◽  
Defect Prediction ◽  
Software Defect Prediction ◽  
Model Based ◽  
Software Defect

Structure-Bioactivity Relationship Study of Xanthene Derivatives: A Brief Review

2020 ◽  
Vol 16 (8) ◽  
pp. 1071-1077
Author(s):  
Aref G. Ghahsare ◽  
Zahra S. Nazifi ◽  
Seyed M.R. Nazifi
Keyword(s):  
Biological Activities ◽  
Cyclic Compound ◽  
Research Field ◽  
Pharmaceutical Chemistry ◽  
Therapeutic Effects ◽  
Main Research ◽  
Research Fields ◽  
Xanthene Derivatives ◽  
Anti Cancer ◽  
Heterocyclic Derivatives

: Over the last decades, several heterocyclic derivatives compounds have been synthesized or extracted from natural resources and have been tested for their pharmaceutical activities. Xanthene is one of these heterocyclic derivatives. These compounds consist of an oxygen-containing central heterocyclic structure with two more cyclic structures fused to the central cyclic compound. It has been shown that xanthane derivatives are bioactive compounds with diverse activities such as anti-bacterial, anti-fungal, anti-cancer, and anti-inflammatory as well as therapeutic effects on diabetes and Alzheimer. The anti-cancer activity of such compounds has been one of the main research fields in pharmaceutical chemistry. Due to this diverse biological activity, xanthene core derivatives are still an attractive research field for both academia and industry. This review addresses the current finding on the biological activities of xanthene derivatives and discussed in detail some aspects of their structure-activity relationship (SAR).

scholarly journals Landscape and Tourism: Evolution of Research Topics

Land ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 488
Author(s):  
Mercedes Jiménez-García ◽  
José Ruiz-Chico ◽  
Antonio Rafael Peña-Sánchez
Keyword(s):  
National Parks ◽  
Web Of Science ◽  
Software Tool ◽  
Research Topics ◽  
Science Mapping ◽  
Research Fields ◽  
Complete Knowledge ◽  
Mapping Analysis ◽  
Landscape Research ◽  
Emerging Themes

Tourism and landscape are broad and complex scientific research fields, as is the synergy between them has given rise to a volume of articles diverse in nature, subject matter and methodology. These difficulties mean that, at present, there is no complete theoretical framework to support this tourism and landscape research, nor complete knowledge of its structure and organization. This motivates the present work, which constitutes the first attempt at mapping this research topic by applying bibliometric techniques using VOSviewer and Science Mapping Analysis Software Tool (SciMAT) software. A total of 3340 articles from journals indexed in Web of Science were analyzed. The results obtained confirm that interest in the study of these concepts has been growing, especially in the last decade. The main contribution of this work lies in the identification of work themes that were basic to the construction of the field but that are currently in decline, such as “cultural heritage” and other themes important to the field that should continue to be dealt with, such as “national parks” or “geotourism”. The transversal nature of sustainability that appears in the network of keywords related to currently emerging themes, such as “planning” and “environment”, is also highlighted and reinforced.

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