Corporations' Owned Social Media Narrative

Ya, Sun; Zhai, Limei; Yang, Kaiwen

doi:10.1109/tpc.2022.3155917

Cited by 8 publications

(2 citation statements)

References 55 publications

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“…Realizing cross-media knowledge discovery and regeneration and generating innovative knowledge [1][2]. The cross-media knowledge service parses, mines, and reorganizes knowledge from cross-media knowledge resources with multiple sources and heterogeneous modalities and provides knowledge with a large perspective that is thoroughly linked to the user's task background [3][4]. In a cross-media environment, cross-source and cross-modal knowledge may have the same theme or deeply related content and be uniquely valuable for problem-solving from different perspectives concerning the task context [5][6].…”

Section: Introductionmentioning

confidence: 99%

Research and Application of Cross-media Knowledge Discovery Service Based on Deep Learning Model

Li,

Liu

et al. 2023

Applied Mathematics and Nonlinear Sciences

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With the diversification and complexity of multimedia data on big data, it becomes increasingly important to realize accurate and effective mutual retrieval among cross-media knowledge service data. In this paper, we first improve the structure of cross-media knowledge deep relevance analysis and apply it to cross-media data to construct cross-media relevance learning evaluation metrics. Then deep learning is commonly used for training classification labels or mapping vectors to another vector space by supervision, and with the rapid growth of data size and hardware resources, the advantages of deep learning in handling large-scale complex data will become more and more obvious. According to the experimental scheme to extract the features of the original data of Wikipedia and NUS-WIDE and the comparative analysis of the results based on the CCA extension method, the performance of CMC-DCCA on the dataset is 0.319, 0.338, 0.363, and 0.372, respectively, and it outperforms the other four algorithms. This study constructs a correlation analysis model between different media data to mine the correlations between cross-media data, thus realizing cross-media knowledge discovery service research while spawning more intuitive and concrete multimedia information carriers so that users can obtain more comprehensive information.

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Section: Introductionmentioning

confidence: 99%

Research and Application of Cross-media Knowledge Discovery Service Based on Deep Learning Model

Li,

Liu

et al. 2023

Applied Mathematics and Nonlinear Sciences

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“…The website is created with a CMS (content management system) or framework or professionally programmed by yourself (Saxena & McDonagh, 2021).The website that has been created is then optimized through SEO (search engine optimization) to increase the ranking of the website so that it makes it easier for search engines (search engines) such as Google, Yahoo, or other search engines to find the page/website and place it on the first page. search engine with keywords specified by the user (Sun, 2022). Like searching for hotels in Jogja in figure 1.3, the website contains content information, images or videos such as tourist attractions in Jogja, hotel facilities, promos and others in figure 1.4.…”

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confidence: 99%

Digital marketing model on Hospitality business’s social media

Carla Puspita,

Prayudi,

Arief Sosiawan

2024

J. Commun.

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The increasing growth of hotels from year to year has resulted in increasingly tight competition in the hotel business in Yogyakarta. In order to win competitive business competition, Indoluxe Hotel Jogjakarta carries out digital marketing through social media in its promotional activities. Social media in the current digital era has no doubt about its existence and has an important role in building relationships between hotels and customers. The aim of this research is to find a digital marketing model on Indoluxe Hotel Jogjakarta social media. The method used in this research uses a qualitative approach by collecting data through interviews, documents and analysis on Indoluxe Hotel Jogjakarta social media. The object of this research is Indoluxe Hotel Jogjakarta's social media with the research subject being the sales & marketing department which manages Indoluxe Hotel Jogjakarta's social media. Overall, digital marketing on social media that has been carried out by Indoluxe Hotel Jogjakarta has implemented the right steps. This can be seen from the results of analysis and evaluation using Forrester's 5I model so that hotels can find out whether the social media they run has an impact on business or vice versa. The results of this research found a digital marketing model on Indoluxe Hotel Jogjakarta social media by dividing the model into three aspects, namely planning, action and involvement. Planning phase to build brand, product and service awareness. The action phase is the stage where the brand, in this case the Indoluxe Hotel Jogjakarta, can interact with customers. Lastly, namely engagement where Indoluxe Hotel Jogjakarta maintains relationships to create customer loyalty.

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