期刊：
FRONTIERS IN PSYCHOLOGY,2025年16:1502112 ISSN：1664-1078
作者机构：
[PENG, QIAO] School of Humanities, Hunan City University, Yiyang, China;[Li, Shuhong] Institute of Foreign Languages, Ocean University of China, Qingdao, China
关键词：
Emotional intelligence1;emotional factor2;language achivement3;second language acquisition4;Meta-analysis5
摘要：
Emotional intelligence (EI) has garnered sustained theoretical and empirical attention over recent decades. Within the domain of linguistics, a growing body of research has investigated the relationship between EI and language achievement. Publication trends in this area reveal two distinct phases: a period of lukewarm attention (2009-2017), followed by a phase of rapid growth (2018-present). The present meta-analysis aims to determine whether EI significantly influences language achievement. Drawing on data from 47 independent studies, comprising 63 effect sizes and a total sample of 18,649 participants, this study found a small but significant correlation between EI and subjective language achievement (r = 0.24), and a moderate correlation with objective language achievement (r = 0.41). Moderator analyses revealed that the relationship between EI and objective language achievement varied significantly by educational level, target language, language skill assessed, and publication year. In contrast, no significant moderation effects were found for research type, learning context, students' major, first language, or the measurement instruments employed. These findings underscore the important role of EI in language learning and highlight the need for emotionally responsive and supportive pedagogical environments that contribute to the sustainable development of foreign language education.
摘要：
Pb contamination is a serious environmental concern, posing significant threats to ecosystems and human health. Biochar-based functional materials have attracted considerable attention owing to their great potential for practical application. In this study, a novel N-functionalized tourmaline-biochar composite (TNBC) from pomelo peels with co-modifications using urea and tourmaline was developed. The immobilization of Pb in solution and soil by TNBC was investigated, and influencing factors and mechanisms were also analyzed. The experimental maximum adsorption capacity of Pb 2+ on TNBC was 600.60 mg/g. Analysis of morphologies and surface functional groups revealed that precipitation regulated Pb 2+ adsorption on TNBC, followed by cation exchange, complexation, and metal-π interaction. The effect of co-existing cations in the solution on adsorption was marginal. Correlation analysis disclosed that enriched plenty of minerals and N-functional groups on TNBC surface were the main reasons for improving Pb 2+ adsorption on TNBC compared with pristine biochar. Moreover, TNBC exhibited potential for soil remediation and could be an alternative amendment for Pb contamination. The TNBC increased the pH, electroconductivity, and residual Pb content of the polluted soil; therefore, it can ameliorate the effects of Pb contamination in the soil. This study provides an alternative viewpoint on developing functionalized biochar composites for soil remediation.
Pb contamination is a serious environmental concern, posing significant threats to ecosystems and human health. Biochar-based functional materials have attracted considerable attention owing to their great potential for practical application. In this study, a novel N-functionalized tourmaline-biochar composite (TNBC) from pomelo peels with co-modifications using urea and tourmaline was developed. The immobilization of Pb in solution and soil by TNBC was investigated, and influencing factors and mechanisms were also analyzed. The experimental maximum adsorption capacity of Pb 2+ on TNBC was 600.60 mg/g. Analysis of morphologies and surface functional groups revealed that precipitation regulated Pb 2+ adsorption on TNBC, followed by cation exchange, complexation, and metal-π interaction. The effect of co-existing cations in the solution on adsorption was marginal. Correlation analysis disclosed that enriched plenty of minerals and N-functional groups on TNBC surface were the main reasons for improving Pb 2+ adsorption on TNBC compared with pristine biochar. Moreover, TNBC exhibited potential for soil remediation and could be an alternative amendment for Pb contamination. The TNBC increased the pH, electroconductivity, and residual Pb content of the polluted soil; therefore, it can ameliorate the effects of Pb contamination in the soil. This study provides an alternative viewpoint on developing functionalized biochar composites for soil remediation.
摘要：
Enhancing the stability and durability of superhydrophobic wood remains a significant challenge for its long-term application in various fields. This study presents a novel approach to developing durable superhydrophobic wood by regulating wood structure. The analyses of the mechanism revealed that Si-Ti@PDMS prepolymer infiltrated wood’s pores and cell walls, forming a highly cross-linked micro-nanoscale superhydrophobic coating extending from the exterior to the interior. The resulting superhydrophobic wood exhibited excellent hydrophobic characteristics on both its surface and various cutting surfaces. Furthermore, the water contact angles (WCA) measured on the various cut surfaces of the wood consistently exceeded 150°, thereby confirming its superhydrophobicity. Additionally, the water contact angles (WCA) at wood depth surfaces remained above 130°. This observation indicates that the non-wettability characteristic of the superhydrophobic wood extends from the surface to the interior. Consequently, even in the event of surface structural damage, the wood retains its robust hydrophobic performance. This study provides a theoretical foundation for regulating durable superhydrophobic wood, and it was beneficial to the efficient use of superhydrophobic wood in construction and furniture fields.
Enhancing the stability and durability of superhydrophobic wood remains a significant challenge for its long-term application in various fields. This study presents a novel approach to developing durable superhydrophobic wood by regulating wood structure. The analyses of the mechanism revealed that Si-Ti@PDMS prepolymer infiltrated wood’s pores and cell walls, forming a highly cross-linked micro-nanoscale superhydrophobic coating extending from the exterior to the interior. The resulting superhydrophobic wood exhibited excellent hydrophobic characteristics on both its surface and various cutting surfaces. Furthermore, the water contact angles (WCA) measured on the various cut surfaces of the wood consistently exceeded 150°, thereby confirming its superhydrophobicity. Additionally, the water contact angles (WCA) at wood depth surfaces remained above 130°. This observation indicates that the non-wettability characteristic of the superhydrophobic wood extends from the surface to the interior. Consequently, even in the event of surface structural damage, the wood retains its robust hydrophobic performance. This study provides a theoretical foundation for regulating durable superhydrophobic wood, and it was beneficial to the efficient use of superhydrophobic wood in construction and furniture fields.
摘要：
Sepiolite (SEP), a naturally abundant and environmentally friendly clay mineral, possesses various active sites and a large specific surface area. In this work, peroxymonosulfate (PMS) was activated to remove tetracycline (TC) using modified Sepiolite (MSEP), which was synthesized by ball milling and calcination techniques. According to the findings, MSEP efficiently stimulated PMS to produce 1 O 2 and ·OH radicals for the degradation of TC, with 1 O 2 being a key component of this process. The findings demonstrated that the carbonate on the MSEP surface encouraged the production of singlet oxygen. ( 1 O 2 ). Under the conditions of pH 6.5, 0.2 g/L MSEP, 2 mmol/L PMS and 25 °C, a 10 mg/L TC concentration was reduced by 93.3 % after 30 min. The presence of Cl − and NO 3 − did not inhibit TC degradation, while HCO 3 − promoted it, and H 2 PO 4 − exhibited an inhibitory effect. This work offers a novel method for using clay minerals to activate PMS and degrade organic contaminant without secondary pollution.
Sepiolite (SEP), a naturally abundant and environmentally friendly clay mineral, possesses various active sites and a large specific surface area. In this work, peroxymonosulfate (PMS) was activated to remove tetracycline (TC) using modified Sepiolite (MSEP), which was synthesized by ball milling and calcination techniques. According to the findings, MSEP efficiently stimulated PMS to produce 1 O 2 and ·OH radicals for the degradation of TC, with 1 O 2 being a key component of this process. The findings demonstrated that the carbonate on the MSEP surface encouraged the production of singlet oxygen. ( 1 O 2 ). Under the conditions of pH 6.5, 0.2 g/L MSEP, 2 mmol/L PMS and 25 °C, a 10 mg/L TC concentration was reduced by 93.3 % after 30 min. The presence of Cl − and NO 3 − did not inhibit TC degradation, while HCO 3 − promoted it, and H 2 PO 4 − exhibited an inhibitory effect. This work offers a novel method for using clay minerals to activate PMS and degrade organic contaminant without secondary pollution.
期刊：
Systems and Soft Computing,2025年:200269 ISSN：2772-9419
通讯作者：
Hui Tang
作者机构：
College of Architecture and Urban Planning, Hunan City University, Yiyang, 413000, China;[Wenxing You] Beijing Century Chief International Architecture Design Co., Ltd, Beijing, 110000, China;[Lu Ou] School of Architecture, Changsha University of Science & Technology, Changsha, Hunan 410000, China;Hunan Provincial Key Laboratory of Urban Planning Information Technology, Yiyang, 413000, China;School of Architecture and Planning, Hunan University, Changsha, 410000, China
通讯机构：
[Hui Tang] C;College of Architecture and Urban Planning, Hunan City University, Yiyang, 413000, China<&wdkj&>Hunan Provincial Key Laboratory of Urban Planning Information Technology, Yiyang, 413000, China
摘要：
Urban resilience evaluates systems’ capacities to prepare for, adapt to, absorb, and recover from disruptions. Evaluation frameworks incorporate metrics like recovery speed, adaptive ability, and absorptive capacity. Assessing critical infrastructure interdependencies is challenging yet vital to limit failure propagation. While static assessments, multi-layer frameworks, and software like Hazus are used, limitations persist. Machine learning often focuses on infrastructure data for recovery monitoring. A common workflow entails acquiring and organizing data, then applying supervised, unsupervised, or reinforcement learning models. Supervised learning uses labeled data while unsupervised learning detects patterns in unlabeled data. Reinforcement learning optimizes rewards through trial-and-error interactions. Machine learning assists in meeting intensifying urbanization and climate change challenges. Leveraging advances in sensors, IoT, and computing enables tasks like image labeling and semantic segmentation. The techniques facilitate resilience through real-time data analytics for informed decision-making and responsive disaster management.
Urban resilience evaluates systems’ capacities to prepare for, adapt to, absorb, and recover from disruptions. Evaluation frameworks incorporate metrics like recovery speed, adaptive ability, and absorptive capacity. Assessing critical infrastructure interdependencies is challenging yet vital to limit failure propagation. While static assessments, multi-layer frameworks, and software like Hazus are used, limitations persist. Machine learning often focuses on infrastructure data for recovery monitoring. A common workflow entails acquiring and organizing data, then applying supervised, unsupervised, or reinforcement learning models. Supervised learning uses labeled data while unsupervised learning detects patterns in unlabeled data. Reinforcement learning optimizes rewards through trial-and-error interactions. Machine learning assists in meeting intensifying urbanization and climate change challenges. Leveraging advances in sensors, IoT, and computing enables tasks like image labeling and semantic segmentation. The techniques facilitate resilience through real-time data analytics for informed decision-making and responsive disaster management.
摘要：
To overcome the problems of low recognition accuracy, poor recognition recall, and long recognition time in traditional badminton video action recognition methods, a badminton video action recognition method based on an adaptive enhanced AdaBoost algorithm is proposed. Firstly, the badminton video actions are collected through inertial sensors, and the badminton action videos are captured to construct an action dataset. The data in this dataset is normalised, and then the badminton video action features are extracted. The weighted fusion method is used to fuse the extracted badminton video action features. Finally, the fused action features are used as the basis, Construct a badminton video action classifier using the adaptive enhanced AdaBoost algorithm, and output the badminton video action recognition results through the classifier. The experimental results show that the proposed method has good performance in recognising badminton video actions.
期刊：
International Journal of Engineering Systems Modelling and Simulation,2025年16(1):52-62 ISSN：1755-9758
作者机构：
[Lianguang Mo] College of Management, Hunan City University, Yiyang, 413000, China;[Wenying Lu] School of Architectural Decoration, Jiangsu Vocational Institute of Architectural Technology, Xuzhou, 221116, China
关键词：
BIM model;high-rise buildings along the street;building surface;wind load;numerical simulation
摘要：
In order to overcome the problems of poor accuracy and low efficiency in the existing numerical simulation methods of building surface wind load, a new numerical simulation method of high-rise street building surface wind load based on BIM model is proposed. This method obtains the data of high-rise buildings along the street based on BIM model, and selects Realisable k-ε model as the turbulence model. The non-equilibrium wall function method is used to deal with the turbulence state on the building surface, the boundary conditions are set, and the turbulence model is calculated and solved by a separate solver to realise the numerical simulation of the surface wind load of high-rise street buildings. The experimental results show that the average error of the wind pressure coefficient of the proposed numerical simulation method is less than 0.4, which fully shows that the proposed numerical simulation method has good performance.
作者：
Zhang, Liang;Jiang, Hao;Zhang, Sheng;Bei, Zhenghao;Huang, Ning
期刊：
Measurement,2025年253:117561 ISSN：0263-2241
通讯作者：
Jiang, H
作者机构：
[Zhang, Liang; Huang, Ning; Zhang, Sheng] Hunan City Univ, Coll Civil Engn, 518 Yingbin East Rd, Yiyang 413000, Hunan, Peoples R China.;[Bei, Zhenghao; Jiang, Hao] Changsha Univ Sci & Technol, Sch Civil Engn, 960 Wanjiali South RD, Changsha 410114, Hunan, Peoples R China.
通讯机构：
[Jiang, H ] C;Changsha Univ Sci & Technol, Sch Civil Engn, 960 Wanjiali South RD, Changsha 410114, Hunan, Peoples R China.
关键词：
Tunnel lining detection;Cavity filler;Forward simulation;Generalized S -transform;Wavelet packet analysis
摘要：
Tunnel lining cavities and other defects can cause cracks in tunnel structures and damage to concrete, seriously affecting the safety of driving in tunnels. Due to varying geological conditions, the materials filling different cavity areas in tunnels differ. By formulating corresponding repair measures for different fillers in cavity areas, many unnecessary losses can be avoided. Therefore, this paper proposes a method based on multi-parameter information for identifying and extracting the characteristics of different fillers in tunnel cavity areas through forward simulation using gprMax software and field test analysis. Ground penetrating radar (GPR) is used to detect cavities of different shapes filled with various media, focusing on cavity signals while reducing interference from I-beams, and reconstructing radar signals through migration. Statistical parameters are introduced for analysis, and techniques such as Fast Fourier Transform, generalized S-transform, and wavelet packet transform are employed to extract features from the processed radar signals. The characteristics of the filling medium in the cavity area are extracted from three aspects: frequency, time–frequency, and energy. This method can provide a reference for interpreting the GPR data of tunnel lining cavity filling media in actual engineering applications.
Tunnel lining cavities and other defects can cause cracks in tunnel structures and damage to concrete, seriously affecting the safety of driving in tunnels. Due to varying geological conditions, the materials filling different cavity areas in tunnels differ. By formulating corresponding repair measures for different fillers in cavity areas, many unnecessary losses can be avoided. Therefore, this paper proposes a method based on multi-parameter information for identifying and extracting the characteristics of different fillers in tunnel cavity areas through forward simulation using gprMax software and field test analysis. Ground penetrating radar (GPR) is used to detect cavities of different shapes filled with various media, focusing on cavity signals while reducing interference from I-beams, and reconstructing radar signals through migration. Statistical parameters are introduced for analysis, and techniques such as Fast Fourier Transform, generalized S-transform, and wavelet packet transform are employed to extract features from the processed radar signals. The characteristics of the filling medium in the cavity area are extracted from three aspects: frequency, time–frequency, and energy. This method can provide a reference for interpreting the GPR data of tunnel lining cavity filling media in actual engineering applications.
摘要：
The critical width-height ratio is a crucial parameter for defining the fill behind the wall as finite soil. Most existing studies on the critical width-height ratio of finite soil use loose sand as filler, without considering the influence of fill compaction degree on the critical width-height ratio of finite soil. By using of model test and numerical simulation, this paper studies the influence of compaction degree of fill behind the retaining wall on the active failure characteristics and the critical width-height ratio of finite soil under TT mode. The empirical relation between compaction degree and density, as well as the compaction degree and internal friction angle of fill materials is established through geotechnical tests. The dynamic development law on active fracture surface of the soil filling with different compaction degrees and width-height ratios behind the retaining wall is obtained. The method of determining the critical width-height ratio of the finite soil mass based on the morphological characteristics of fracture surface is proposed. The empirical formula of the critical width-height ratio of finite soil mass considering the compaction degree of fill is given. Under the TT mode, for the finite soil, the active fracture surface is a multi-segment broken line, starting from the heel of the movable retaining wall and going back and forth between the fixed retaining wall and the movable retaining wall, and ending at the fill surface; for the semi-infinite soil, the active fracture surface is an approximate straight line from the wall heel to the fill surface. For finite soil with a certain width-height ratio, with the increase of compaction degree, the active fracture surface gradually changes from a broken line to a straight line; the finite soil gradually becomes semi-infinite soil. For semi-infinite soil with a certain width-height ratio, with the increase of the compaction degree, the active fracture surface gradually becomes steeper, and the volume of the broken body gradually decreases; the soil behind the wall is still semi-infinite. When the compaction degree is constant, with the increase of the width-height ratio, the active fracture surface gradually changes from a broken line to a straight line, and the finite soil behind the wall gradually changes to semi-infinite soil. Under the TT mode, the active failure critical width-height ratio of finite soil decreases linearly with the increase of the compaction degree of fill, showing a highly linear correlation. The compaction degree of backfill is one of the important factors affecting the critical width-height ratio, which should be considered in the design and construction of actual support engineering. The study is of great significance for determining the critical width-height ratio of finite soil behind the retaining wall, and can provide a reference for the deformation analysis and earth pressure calculation of the finite soil behind the retaining structure.
期刊：
FRONTIERS IN EARTH SCIENCE,2025年13:1581090 ISSN：2296-6463
作者机构：
[Wang, Jiaxin] Department of Natural Resources, China;[Yang, Ying] Department of Discipline Inspection and Supervision,, China;[Yang, Xian; Hu, Da] Hunan Engineering Research Center of Structural Safety and Disaster Prevention for Urban Underground Infrastructure, China;[Lu, Yulong; Liu, Yang] School of Earth Sciences and Spatial Information, China;[Hu, Yongjia] School of Resources and Safety Engineering, China
摘要：
Karst collapse, a sudden geological hazard with complex mechanisms and low predictability, presents significant threats to urban safety and sustainable development by jeopardizing human lives and infrastructure. To address the limitations of conventional prediction methods, in this study, we introduce an enhanced predictive model, the improved sparrow search algorithm-optimized extreme learning machine (ISSA-ELM), for accurate karst-collapse susceptibility assessment. The methodology incorporates two key innovations: first, it applies a Singer chaotic mapping technique to enhance the sparrow search algorithm (SSA), effectively mitigating local optima entrapment by increasing population diversity and enhancing global search capabilities. Second, the optimized ISSA automatically adjusts the initial weights and thresholds of the ELM, whereas a five-fold cross-validation is used to determine the optimal hidden layer configuration, forming an adaptive and intelligent prediction framework. When validated against 20 datasets from a representative karst region, the proposed model achieved exceptional performance, with a mean absolute error (MAE) of 0.0544 and a coefficient of determination (R 2 ) of 0.9914, significantly surpassing the prediction accuracy of conventional ELM and SSA-ELM models. The results underscore the ISSA-ELM’s superior nonlinear fitting capability, enhanced generalization performance, and outstanding stability in practical engineering applications. This research offers a solid scientific foundation for risk classification and hazard mitigation strategies while introducing a novel methodological framework through the integration of innovative algorithms. The proposed technical pathway provides significant theoretical advancements and practical engineering values for geological disaster prediction systems.
摘要：
In view of the problems in the existing methods such as large retrieval error, low data positioning accuracy, and long retrieval time, this paper proposes an intelligent retrieval method for book resources in smart libraries based on RFID. First, complete the rough extraction of the features of the book resources in the smart library. Then, set the length rule of book resource features, eliminate ambiguous data, determine the similarity of book resource features, and merge similar features through similar probability mapping. Finally, complete the feature data authentication, set the tag with RFID tag technology, locate the tag data location, build the book resource index tree, and determine the intelligent retrieval model. The test results show that the proposed method can reduce the intelligent retrieval error of book resources in smart libraries, improve the accuracy of data location, and reduce the retrieval time cost.
摘要：
The shear failure of concrete is a sudden brittle failure, which is difficult to be forewarned. To investigate the shear crack mechanisms in concrete, this study first systematic compared acoustic emission (AE) behavior during direct shear tests, compression shear tests (Z-shaped specimens), and three point bending shear tests. AE parameters (amplitude, cumulative count and energy), average frequency (AF)-rise time/amplitude (RA) analysis, K-means clustering, and b-value analysis were integrated to classify cracks and characterize damage progression. The correlation between the shear crack propagation mechanism of concrete and AE parameters was revealed. The AE activity during concrete shear failure was successfully characterized, providing valuable insights into the damage development and evolution processes. The research findings establish a quantitative framework for using AE technology to detect shear cracks and monitor real-time damage evolution in concrete structures.
期刊：
International Journal of Networking and Virtual Organisations,2025年32(1-4):86-101 ISSN：1470-9503
作者机构：
[Fu Peng] School of Fine Arts and Design, Changsha Normal University, Chang Sha, 410148, China;[Yi Liu] Art and Design College\International Education College, Hunan City University, Yi Yang, 413002, China
摘要：
In order to optimise the effectiveness of resource recommendation and improve the coverage of personalised learning resource recommendation results, a personalised learning resource online recommendation method based on multidimensional feature extraction is proposed. Firstly, based on the feature expression and density parameters of user behaviour data, cluster the users. Secondly, extract users' time features, preference features, and learning resource features, and use feature matrices for efficient feature mining. Finally, the extracted personalised learning resource features are input into the self-organising maps (SOM) network, and through the resource scoring mechanism and similarity calculation process, recommendation prediction values are generated and sorted to form a personalised recommendation set. The experimental results show that this method can accurately provide resource solutions that meet user needs when the number of resources and users increase, and the recommendation coverage rate always remains above 90%.
期刊：
POLISH JOURNAL OF ENVIRONMENTAL STUDIES,2025年34(4):3577-3592 ISSN：1230-1485
通讯作者：
Chen, Y
作者机构：
[Chen, Yu] Hunan City Univ, Coll Architecture & Urban Planning, Yiyang 413000, Peoples R China.;[Zhang, Mengmiao; Chen, Yu; He, Shaoyao] Hunan Univ, Sch Architecture & Planning, Changsha 410000, Peoples R China.;[Chen, Yu] Hunan Key Lab Key Technol Digital Urban & Rural Sp, Yiyang 413000, Peoples R China.;[Cai, Yan] Hunan City Univ, Sch Humanities, Yiyang 413000, Peoples R China.
通讯机构：
[Chen, Y ] H;Hunan City Univ, Coll Architecture & Urban Planning, Yiyang 413000, Peoples R China.;Hunan Univ, Sch Architecture & Planning, Changsha 410000, Peoples R China.;Hunan Key Lab Key Technol Digital Urban & Rural Sp, Yiyang 413000, Peoples R China.
关键词：
healthy urban space;long and short term memory;neural network;air quality;pollutant concentration
摘要：
With the improvement of people's living standards, more people are concerned about the air quality and safety of residential cities, and the concept of healthy urban space is gradually becoming deeply rooted in people's hearts. This study is based on long and short term memory neural network algorithms, incorporating AMs into them. The research adjusts the data input to the algorithm according to spatiotemporal characteristics and incorporates a stack-type self-coding network into an improved long and short term memory neural network to predict the concentration of urban air pollutants. The air pollutant data of Changsha-Zhuzhou-Xiangtan is used to test the model, and the test results are as follows: The index values of the mean absolute error and coefficient of determination of the intelligent prediction model with all improvement measures in the test set are 4.0 and 0.94, respectively, which is significantly better than the traditional and partially improved long and short term memory neural network. The algorithm model with complete improvement measures is selected for comparative experiments with other recurrent neural networks. This experimental result shows that the overall fluctuation amplitude of this model is the smallest under various test sample numbers. The mean absolute error and root-mean-square error on the whole test set are 6.7 and 9.2, respectively, which are and the memory consumption is also lower. The experimental data proves that this model, combined with an expert experience system, has the potential to be applied to urban air pollutant prediction and health risk assessment.
期刊：
International Journal of Web Based Communities,2025年21(1):20-35 ISSN：1477-8394
作者机构：
[Aihua Mo] School of Management, Hunan City University, Hunan, 413000, China
关键词：
mobile e-commerce platform;perceived points of interest;dynamic collaborative mining;coarse grained characteristics;binary classification model
摘要：
In the process of dynamic collaborative mining of user perceived interest points on mobile e-commerce platforms, due to the lack of effective feature classification, the recall rate of interest point data in dynamic collaborative mining of interest points is low. Therefore, a dynamic collaborative mining method for user perceived interest points on mobile e-commerce platforms is proposed. Firstly, coarse grained features of user perceived interest points are initially extracted through clustering algorithms, and their feature values are further extracted using sequence feature extraction algorithms. Then, a user perceived interest prediction model is constructed, and fitting methods are used to achieve feature classification of user perceived interest points. Finally, by designing a dynamic collaborative mining model for user perceived interest points on mobile e-commerce platforms, dynamic collaborative mining is achieved. The experimental results show that the dynamic convergence change of method in this paper interest point data mining is relatively small, and the maximum recall rate is 99%, effectively improving mining performance, thereby providing more accurate and accurate personalised recommendations for mobile e-commerce platforms.
