Smart recommendation for tourist hotels based on multidimensional information: a deep neural network model

Xia, Huosong; An, Wuyue; Liu, Genwang; Hu, Runjiu; Zhang, Zuopeng; Wang, Yuan

doi:10.1080/17517575.2021.1959651

Cited by 11 publications

(7 citation statements)

References 79 publications

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“…Retaining talent is as crucial as acquiring it for sustainable business growth [96]. The use of multidimensional data, as demonstrated by Xia et al [97], offers insights into employee needs, thus aiding in the development of sustainable work environments. This data-driven approach is similar to the sustainable strategies in water management discussed by Kenda et al [98], emphasizing the importance of a holistic view in understanding and addressing issues.…”

Section: Impact Of Data Fusion On Core Talent Management Functionsmentioning

confidence: 99%

Fusing talent horizons: the transformative role of data integration in modern talent management

Asfahani

2024

Discov Sustain

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This study elucidates the transformative influence of data integration on talent management in the context of evolving technological paradigms, with a specific focus on sustainable practices in human resources. Historically anchored in societal norms and organizational culture, talent management has transitioned from traditional methodologies to harnessing diverse data sources, a shift that enhances sustainable HR strategies. By employing a narrative literature review, the research traces the trajectory of HR data sources, emphasizing the juxtaposition of structured and unstructured data. The digital transformation of HR is explored, not only highlighting the evolution of Human Resource Information Systems (HRIS) but also underscoring their role in promoting sustainable workforce management. The integration of advanced technologies such as machine learning and natural language processing is examined, reflecting on their impact on the efficiency and ecological aspects of HR practices. This paper not only underscores the imperative of balancing data-driven strategies with the quintessential human element of HR but also provides concrete examples demonstrating this balance in action for practitioners and scholars in sustainable human resources.

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Section: Impact Of Data Fusion On Core Talent Management Functionsmentioning

confidence: 99%

Fusing talent horizons: the transformative role of data integration in modern talent management

Asfahani

2024

Discov Sustain

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“…According to the Eq (27), the accuracy of long word of models is calculated from the statistics of long words.…”

Section: Calculation Of Accuracy Of Long Wordsmentioning

confidence: 99%

“…The word segmentation performance can be further improved by integrating an attention mechanism into the Bi-LSTM-CRF model [24]. Then a transfer learning mechanism was introduced to cope with the problem that a deliberately designed and trained model cannot work well on test data without similar application context and feature distribution to training data [25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

A hybrid Chinese word segmentation model for quality management-related texts based on transfer learning

Wen

Feng²,

Zhang³

2022

PLoS ONE

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Text information mining is a key step to data-driven automatic/semi-automatic quality management (QM). For Chinese texts, a word segmentation algorithm is necessary for pre-processing since there are no explicit marks to define word boundaries. Because of intrinsic characteristics of QM-related texts, word segmentation algorithms for normal Chinese texts cannot be directly applied. Hence, based on the analysis of QM-related texts, we summarized six features, and proposed a hybrid Chinese word segmentation model by means of integrating transfer learning (TL), bidirectional long-short term memory (Bi-LSTM), multi-head attention (MA), and conditional random field (CRF) to construct the mTL-Bi-LSTM-MA-CRF model, considering insufficient samples of QM-related texts and excessive cutting of idioms. The mTL-Bi-LSTM-MA-CRF model is composed of two steps. Firstly, based on a word embedding space, the Bi-LSTM is introduced for context information learning, and the MA mechanism is selected to allocate attention among subspaces, and then the CRF is used to learn label sequence constraints. Secondly, a modified TL method is put forward for text feature extraction, adaptive layer weights learning, and loss function correction for selective learning. Experimental results show that the proposed model can achieve good word segmentation results with only a relatively small set of samples.

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“…In scholarly parlance, a SC can be an integrated city, community, or region (Li et al. , 2011) or an application that uses technology to assist its inhabitants, companies and service organizations (Xia et al. , 2023) to promote economic progression, social benefits (Liu et al.…”

Section: Introductionmentioning

confidence: 99%

“…In scholarly parlance, a SC can be an integrated city, community, or region (Li et al, 2011) or an application that uses technology to assist its inhabitants, companies and service organizations (Xia et al, 2023) to promote economic progression, social benefits (Liu et al, 2020) and environmental sustainability (Ding et al, 2021). Linking users, different devices and apps to build intelligent services, automate service delivery and improve operational efficiency can also be a form of established SC (Sani et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

A contemplative overview of smart communities: a hybrid analytical approach

Sakshi,

Srivastava,

Mangla

et al. 2023

JEIM

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PurposeThis study aims to uncover and develop explicit knowledge of existing smart communities (SCs) to guide services and business solutions for enterprises and serve community users in a well-thought-out manner. These sagacious frameworks will assist in analyzing trends and reaching out to pre-existing setups with different degrees of expertise.Design/methodology/approachA systematic overview is provided in this paper to unify insights and competencies toward building SCs; a hybrid analytical approach is used consisting of machine learning and bibliometric analysis. Scopus and Web of Science (WoS) are the primary databases for this purpose.FindingsSCs implement cutting-edge technologies to enhance mobility, elevating information and communication technology (ICT) skills and data awareness while improving business processes and efficiency. This system of SC is an evolution of the conventional method. It provides a foundation for intelligent community services based on individual users and technologies such as the Internet of Things (IoT), artificial intelligence, cloud computing and big data. Manufacturing-based, service-based, retail-based, resource management and infrastructure-based SCs exist in the literature.Originality/valueThe paper summarizes a conceptual framework of SCs based on existing works around SCs. To the best of the authors’ knowledge, this is the first systematic literature review that uses a hybrid approach of topic modeling and bibliometric analysis to understand SCs better.

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Smart recommendation for tourist hotels based on multidimensional information: a deep neural network model

Cited by 11 publications

References 79 publications

Fusing talent horizons: the transformative role of data integration in modern talent management

Fusing talent horizons: the transformative role of data integration in modern talent management

A hybrid Chinese word segmentation model for quality management-related texts based on transfer learning

A contemplative overview of smart communities: a hybrid analytical approach

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