International Journal of Crowd Science最新文献

{"title":"Home-Purchase Restriction, Urban Population, and Industry Development: Evidence from Beijing","authors":"Depei Yang;Leiju Qiu","doi":"10.26599/IJCS.2023.9100009","DOIUrl":"https://doi.org/10.26599/IJCS.2023.9100009","url":null,"abstract":"With the rapid economic development, megacities have gathered a large number of population and industries, and a series of “urban diseases” have also emerged. To alleviate these problems, various administrative measures have been taken to control population and optimize industrial distribution. Meanwhile, home-purchase restriction (HPR) has been introduced to control the soaring housing prices. Existing research focuses on the impact of policy on its own market, without paying attention to the linkage between markets and spillover effect. We take Beijing, the capital of China, as an example to study the impact of the HPR on the population distribution and industry development of megacities. By analyzing the industry location quotient and population economy matching degree, we conclude that HPR effectively promotes the efficiency of population and industry dispersal, but increases the mismatching between industry and population. City is a typical intelligent system that gathers various intelligent agents, and the development of its population and industry is the fundamental evolution of the system. This paper explores the role of policies in the evolution of urban intelligent systems, and therefore has important theoretical and practical significance for intelligent systems.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"7 3","pages":"137-147"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9736195/10269816/10269821.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67844789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cross-Domain Credit Default Prediction via Interpretable Ensemble Transfer","authors":"Zhida Shang;Hefeng Meng;Yibowen Zhao;Ronghua Xu;Yonghui Xu;Lizhen Cui","doi":"10.26599/IJCS.2023.9100011","DOIUrl":"https://doi.org/10.26599/IJCS.2023.9100011","url":null,"abstract":"The evaluation and prediction of credit risk have always been a research hotspot to ensure the healthy and orderly development of the credit market. Most researchers use deep learning to predict credit risk. However, when training data are too small, deep learning models often lead to overfitting. Although we have a large amount of available training data, we often cannot ensure that the data are evenly distributed, which is still not conducive to model training. In addition, deep learning is often difficult to explain, and the unexplained model is often difficult to gain the trust of users, thus reducing the usefulness of the model. To solve these problems, we propose an integrated cross-domain credit default prediction network, called Transfer Light Gradient Boosting Machine (TrLightGBM), based on interpretable integration transfer. This network considers the weight of data from different domains in training and implements cross-domain credit default prediction by adjusting the weight. The experiment shows that our method TrLightGBM not only achieves the interpretability of the model to a certain extent but also has good performance.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"7 3","pages":"106-112"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9736195/10269816/10269817.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67844792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Product Map Analysis from a Crowd of Small- and Medium-Sized E-Commerce Sites: A Bottom-Up Approach","authors":"","doi":"","DOIUrl":"https://doi.org/","url":null,"abstract":"","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"7 3","pages":"1-3"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9736195/10269816/10271249.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67844788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Music Intervention in Human Life, Work, and Disease: A Survey","authors":"Jia Gu;Youyang Du;Chi Zhang;Yunsen Tang;Huiguo Zhang;Yonghui Xu;Lizhen Cui","doi":"10.26599/IJCS.2023.9100003","DOIUrl":"https://doi.org/10.26599/IJCS.2023.9100003","url":null,"abstract":"Digital music has various characteristics, such as melody, rhythm, timbre, and harmony. According to these characteristics, music can be classified using artificial intelligence (AI). Music can reduce cognitive dissonance and improve memory in humans; however, occasionally, dissonant music can cause negative effects, such as aggravating depression. Therefore, music can be classified using technical methods and used selectively for human mood regulation, sleep improvement, disease relief, and treatment. Herein we present a survey of the fields of music, AI, and health to shed light on the digitization of music. In this survey, we (1) summarize the various characteristic elements of music, such as melody, rhythm, timbre, and harmony; (2) discuss the role of neural networks in classifying music based on these musical characteristics; (3) summarize the positive and negative effects of music with respect to five areas: sleep, memory, attention, mood, and movement; (4) summarize the therapeutic effect of music intervention with respect to various illnesses; and (5) present the future of music therapy as well as provide a few suggestions with respect to music therapy.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"7 3","pages":"97-105"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9736195/10269816/10269820.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67844791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Erratum to “Individual Behavior Modeling and Transmission Control During Disease Spread: A Review”","authors":"","doi":"10.26599/IJCS.2023.9100016","DOIUrl":"https://doi.org/10.26599/IJCS.2023.9100016","url":null,"abstract":"","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"7 3","pages":"148-148"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9736195/10269816/10271251.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68006870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Part Deviation Correction Method Based on Geometric Feature Recognition","authors":"Guoqing Zhang;Hongbo Sun","doi":"10.26599/IJCS.2023.9100005","DOIUrl":"https://doi.org/10.26599/IJCS.2023.9100005","url":null,"abstract":"To realize the automatic loading process of parts, one of the core tasks is to identify the geometric contour of the part's surface and the angular direction. Since the angular direction of each part is not the same when it arrives at the loading position, for example, there are two same types of parts with the same pattern, when they arrive at the loading position, the pattern on one part may be on the right side of the part surface, and the pattern on the other part may be on the left side of the part surface, the gripper of the mechanical arm needs to rotate above the parts in order to grab the parts during each loading process. If the rotation angle is wrong, there will be an impact between the gripper and the parts. Therefore, in order to solve the problem of different angles, this paper proposes a method of parts deviation correction based on geometric features. In this work, firstly, the acquired image is preprocessed, the image background is separated, and the geometric features of the parts are obtained. Then edge detection is used to obtain the set of edge pixels to obtain the contour in the image. Finally, the image moment and measurement model are used to output angular direction. Through 500 repeated detection experiments, the results show that this method can perform better angular direction correction. The maximum angular direction difference is 0.073°, which is 0.856° and 1.793° higher than the Least square method and Hough transform circle detection accuracy, respectively. The average detection time is 1.89 s and is 0.336 s and 1.39 s less than the Least square method and Hough transform circle detection, which meets the requirements of industrial applications.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"7 3","pages":"113-119"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9736195/10269816/10269818.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68006871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Product Map Analysis from a Crowd of Small- and Medium-Sized E-Commerce Sites: A Bottom-Up Approach","authors":"Xin Li;Tongda Zhang;Xiao Sun;Yongsheng Ma","doi":"10.26599/IJCS.2023.9100006","DOIUrl":"https://doi.org/10.26599/IJCS.2023.9100006","url":null,"abstract":"The study of product maps in e-commerce has garnered significant attention from academics and practitioners, as they provide insights into the relationship between products, such as complementarity and competition. However, existing studies have focused on the perspectives of large manufacturers and retailers, using data from these central sources. This paper adopts a bottom-up approach based on crowd intelligence, with small- and medium-sized e-commerce (SME) sites serving as independent data providers. This approach allows for the decentralized processing of data and enables the aggregation of diverse perspectives and insights from a large number of independent sources. A graph term frequency-inverse document frequency method is proposed, which can measure the similarities of products and build a product map. The method was employed to find a hierarchical community structure using data from over 90 000 products from 52 SME sites. The results showed that products within the same site tend to be distributed across the same community. Our findings can assist e-commerce sites in making informed decisions about pricing and product offerings, leading to more diversified production.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"7 3","pages":"131-136"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9736195/10269816/10269822.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68006872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Turning the Cacophony of the Internet's Tower of Babel into a Coherent General Collective Intelligence","authors":"Andy E. Williams","doi":"10.26599/IJCS.2022.9100035","DOIUrl":"10.26599/IJCS.2022.9100035","url":null,"abstract":"Increasing the number, diversity, or uniformity of opinions in a group does not necessarily imply that those opinions will converge into a single more “intelligent” one, if an objective definition of the term intelligent exists as it applies to opinions. However, a recently developed approach called human-centric functional modeling provides what might be the first general model for individual or collective intelligence. In the case of the collective intelligence of groups, this model suggests how a cacophony of incoherent opinions in a large group might be combined into coherent collective reasoning by a hypothetical platform called “general collective intelligence” (GCI). When applied to solving group problems, a GCI might be considered a system that leverages collective reasoning to increase the beneficial insights that might be derived from the information available to any group. This GCI model also suggests how the collective reasoning ability (intelligence) might be exponentially increased compared to the intelligence of any individual in a group, potentially resulting in what is predicted to be a collective superintelligence.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"7 2","pages":"55-62"},"PeriodicalIF":0.0,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9736195/10159625/10159626.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46559436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of Core Authors in International Education of Chinese and the Evolution of Their Research Topics","authors":"Yue Huang;Kexin Zhang","doi":"10.26599/IJCS.2022.9100036","DOIUrl":"10.26599/IJCS.2022.9100036","url":null,"abstract":"Due to the fast development of Internet, the bibliographic information under “Internet+” era presents obvious big data characteristics. Crowdsourcing strategy can be applied to analyze bibliographic data. By gathering journal papers and conference papers from different sources in a specific field and identifying its core authors as well as the evolution of the hot research topics the core authors chose to work on, we hope to provide a reference for future research topics and research directions. In this paper, we modified an existing core author evaluation system by adding an indicator called the weighted score of every authorship. After gathering the experimental data from International Education of Chinese, we used the Price formula to detect the core author candidates and build a core author evaluation system based on five indicators, which were the publication volumes, the number of citations, h-index, research field normalized citation impact, and weighted score of every authorship. The weight of each indicator and the score of each candidate were calculated based on the comprehensive index and entropy-based method. Thereafter, the Latent Dirichlet Allocation (LDA) model was used to summarize the papers on the hot research topics the core authors worked on for each period, followed by evolution analysis. Using the above methods, experiments were carried out on the bibliographic data of journal papers and conference papers in the discipline of International Education of Chinese between 2001 and 2020 that were included in the CNKI. Scholars whose scores were greater than 50 were identified as the core author(s) of each period. The core authors and the evolution of their hot research topics were conducted in four periods, namely 2001–2005, 2006–2010, 2011–2015, and 2016–2020. It is our conclusion that the compilation of textbooks has always been the focus of the discipline of International Education of Chinese, while the teaching modes have become increasingly diversified, and also research on the training of undergraduates and postgraduates has increased. With the advancement of technology, much relevant knowledge from many other disciplines has been integrated into the International Education of Chinese, and scholars should pay attention to interdisciplinary research.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"7 2","pages":"68-76"},"PeriodicalIF":0.0,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9736195/10159625/10159561.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45183516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction of Students' Innovation Ability Portrait for Cultural Intelligence Computing","authors":"Chunhong Liu;Xiaoniu Li;Jiahu Zhang","doi":"10.26599/IJCS.2023.9100001","DOIUrl":"10.26599/IJCS.2023.9100001","url":null,"abstract":"At the age of artificial intelligence, the inheritance and development of innovation culture are crucial for constructing an innovative country, and they are major components of cultural intelligence computing. The portrait of innovation ability is a digital representation of innovative culture, and its accurate description is the basis for the personalized cultivation of innovation ability. Therefore, how to objectively and accurately design a labeling system for an innovation ability portrait and depict a high-pixel portrait is an urgent problem to be solved for the digital representation of innovation culture. To address this problem, based on innovation theory, our study (1) uses a combination of subjective and objective methods to design an innovation ability evaluation system, (2) constructs a scientific and reasonable portrait label system, (3) represents the system's results as individual students' innovation ability portraits and student groups' innovation ability portraits, and (4) visualizes the portraits' results. Finally, considering resource recommendation as an example, this study (1) adopts a computational model of crowd intelligence computing, (2) designs and implements a personalized recommendation system for educational resources based on the resulting innovation ability portraits, (3) improves the computing efficiency, and (4) expounds the applications of portraits in personalized learning, precise teaching, and smart educational decision-making to promote personalized innovative talent training and realize the core value of innovative culture.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"7 2","pages":"77-86"},"PeriodicalIF":0.0,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9736195/10159625/10159562.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43536936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}