异构信息网络(Heterogeneous Information Network, HIN)凭借其丰富的语义信息和结构信息被广泛应用于推荐系统中,虽然取得了很好的推荐效果,但较少考虑局部特征放大、信息交互和多嵌入聚合等问题。针对这些问题,提出了一种新的用于top-...异构信息网络(Heterogeneous Information Network, HIN)凭借其丰富的语义信息和结构信息被广泛应用于推荐系统中,虽然取得了很好的推荐效果,但较少考虑局部特征放大、信息交互和多嵌入聚合等问题。针对这些问题,提出了一种新的用于top-N推荐的多嵌入融合推荐(Multi-embedding Fusion Recommendation, MFRec)模型。首先,该模型在用户和项目学习分支中都采用对象上下文表示网络,充分利用上下文信息以放大局部特征,增强相邻节点的交互性;其次,将空洞卷积和空间金字塔池化引入元路径学习分支,以便获取多尺度信息并增强元路径的节点表示;然后,采用多嵌入融合模块以便更好地进行用户、项目以及元路径的嵌入融合,细粒度地进行多嵌入之间的交互学习,并强调了各特征的不同重要性程度;最后,在两个公共推荐系统数据集上进行了实验,结果表明所提模型MFRec优于现有的其他top-N推荐系统模型。展开更多
针对传统序列模式挖掘(SPM)不考虑模式重复性且忽略各项的效用(单价或利润)与模式长度对用户兴趣度影响的问题,提出一次性条件下top-k高平均效用序列模式挖掘(TOUP)算法。TOUP算法主要包括两个核心步骤:平均效用计算和候选模式生成。首...针对传统序列模式挖掘(SPM)不考虑模式重复性且忽略各项的效用(单价或利润)与模式长度对用户兴趣度影响的问题,提出一次性条件下top-k高平均效用序列模式挖掘(TOUP)算法。TOUP算法主要包括两个核心步骤:平均效用计算和候选模式生成。首先,提出基于各项出现位置与项重复关系数组的CSP(Calculation Support of Pattern)算法计算模式支持度,从而实现模式平均效用的快速计算;其次,采用项集扩展和序列扩展生成候选模式,并提出了最大平均效用上界,基于该上界实现对候选模式的有效剪枝。在5个真实数据集和1个合成数据集上的实验结果表明,相较于TOUP-dfs和HAOP-ms算法,TOUP算法的候选模式数分别降低了38.5%~99.8%和0.9%~77.6%;运行时间分别降低了33.6%~97.1%和57.9%~97.2%。TOUP的算法性能更优,能更高效地挖掘用户感兴趣的模式。展开更多
This study aims to determine the key and underlying Leadership and Top Management (LTM) factors that have a significant impact on sustaining the implementation of Total Quality Management (TQM) within the construction...This study aims to determine the key and underlying Leadership and Top Management (LTM) factors that have a significant impact on sustaining the implementation of Total Quality Management (TQM) within the construction industry in Ghana. The research methodology employed in this study was a quantitative technique. Questionnaires were distributed to 641 participants within construction industry in Ghana. Questionnaires retrieved for the analysis were 536. Three steps approached were used for the data analysis. These include Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM) analysis. After conducting the EFA and CFA, SEM was also used to analyze the construct validity. The SEM analysis helps to determine four key indicator variables for the leadership and top management construct. These include Leadership/Top Management approach to employees’ management, Leadership/Top Management understanding of TQM, Leadership/Top Management empowerment of employees to resolve quality issues, and Leadership/Top Management endorsement of TQM. All the four indicator variables were found to be good of fit and closely associated with the dependent variable. The study adds to the body of knowledge by using EFA, CFA and SEM techniques to establish key leadership and top management factors affecting TQM implementation in Ghana’s construction industry. The findings in general suggested that leadership and top Management factors identified have a direct positive impact on sustaining TQM implementation in the Ghanaian construction industry. Consequently, the leadership and top management factors identified in this study can help improve TQM in the Ghanaian construction industry.展开更多
文摘针对传统序列模式挖掘(SPM)不考虑模式重复性且忽略各项的效用(单价或利润)与模式长度对用户兴趣度影响的问题,提出一次性条件下top-k高平均效用序列模式挖掘(TOUP)算法。TOUP算法主要包括两个核心步骤:平均效用计算和候选模式生成。首先,提出基于各项出现位置与项重复关系数组的CSP(Calculation Support of Pattern)算法计算模式支持度,从而实现模式平均效用的快速计算;其次,采用项集扩展和序列扩展生成候选模式,并提出了最大平均效用上界,基于该上界实现对候选模式的有效剪枝。在5个真实数据集和1个合成数据集上的实验结果表明,相较于TOUP-dfs和HAOP-ms算法,TOUP算法的候选模式数分别降低了38.5%~99.8%和0.9%~77.6%;运行时间分别降低了33.6%~97.1%和57.9%~97.2%。TOUP的算法性能更优,能更高效地挖掘用户感兴趣的模式。
文摘This study aims to determine the key and underlying Leadership and Top Management (LTM) factors that have a significant impact on sustaining the implementation of Total Quality Management (TQM) within the construction industry in Ghana. The research methodology employed in this study was a quantitative technique. Questionnaires were distributed to 641 participants within construction industry in Ghana. Questionnaires retrieved for the analysis were 536. Three steps approached were used for the data analysis. These include Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM) analysis. After conducting the EFA and CFA, SEM was also used to analyze the construct validity. The SEM analysis helps to determine four key indicator variables for the leadership and top management construct. These include Leadership/Top Management approach to employees’ management, Leadership/Top Management understanding of TQM, Leadership/Top Management empowerment of employees to resolve quality issues, and Leadership/Top Management endorsement of TQM. All the four indicator variables were found to be good of fit and closely associated with the dependent variable. The study adds to the body of knowledge by using EFA, CFA and SEM techniques to establish key leadership and top management factors affecting TQM implementation in Ghana’s construction industry. The findings in general suggested that leadership and top Management factors identified have a direct positive impact on sustaining TQM implementation in the Ghanaian construction industry. Consequently, the leadership and top management factors identified in this study can help improve TQM in the Ghanaian construction industry.
