Relevant bibliographies by topics / Restaurant aggregation

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  2. Conference papers

Academic literature on the topic 'Restaurant aggregation'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Restaurant aggregation"

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Abdullah, Lazim, Noor Azzah Awang, and Mahmod Othman. "Application of Choquet Integral-Fuzzy Measures for Aggregating Customers’ Satisfaction." Advances in Fuzzy Systems 2021 (September 21, 2021): 1–8. http://dx.doi.org/10.1155/2021/2319004.

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Choquet integral is a type of aggregation operator that is commonly used to aggregate the interrelated information. Nowadays, this operator has been successfully embedded with fuzzy measures in solving various evaluation problems. Inspired from this new development, this paper aims to introduce a combined Choquet integral-fuzzy measures (CI-FM) operator that uses the Shapley value standard and interaction index to deal with the interactions between elements of information. The proposed operator takes into account not only the importance of elements or their ordered positions but also the inter
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N, Vinoth Kumar, Radhivarma K S, Sachin B, and Guide:Mrs M. Kirubadevi AP. "Food Picky Restaurant Aggregation and Food Ordering Web Application." International Journal of Research Publication and Reviews 5, no. 3 (2024): 5143–248. http://dx.doi.org/10.55248/gengpi.5.0324.0819.

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Gogu, Sandeep, Sudheendra Kurakula, K. Sreekala Dr., Poornima P., Musrat Sultana N., and A. Nagesh Dr. "Online Food Ordering Website." Recent Trends in Information Technology and its Application 8, no. 3 (2025): 46–55. https://doi.org/10.5281/zenodo.15532357.

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<em>In the rapidly expanding internet food ordering platform space, companies such as Swiggy and Zomato have changed the way consumers eat and buy food. But there is one big chokepoint in existing systems: the customer cannot order a composite order of products from more than one restaurant. There must be multiple orders, with a longer delivery cost, increased waiting time, and even fractured customer experience. Our project is intended to fill this gap by creating a new food ordering website online where people can order various foods from various restaurants in one combined order. </em> <em>
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Pérez-Almaguer, Yilena, Edianny Carballo-Cruz, Yailé Caballero-Mota, and Raciel Yera. "Exploring content-based group recommendation for suggesting restaurants in Havana City." JUCS - Journal of Universal Computer Science 30, no. 1 (2024): 106–29. http://dx.doi.org/10.3897/jucs.104838.

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Recommender systems (RSs) are a relevant kind of artificial intelligence-based systems focused on providing users with the information that best fit their preferences and needs in a search space overloaded of possible options. Specifically, group recommender systems (GRSs) are a special type of RS centered on recommending items that are consumed in groups and not individually, being TV program and touristic packages key examples of such items. The current work is focused on proposing a content-based group recommendation approach (CB-GRS) contextualized to the restaurant recommendation domain.
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Pérez-Almaguer, Yilena, Edianny Carballo-Cruz, Yailé Caballero-Mota, and Raciel Yera. "Exploring content-based group recommendation for suggesting restaurants in Havana City." JUCS - Journal of Universal Computer Science 30, no. (1) (2024): 106–29. https://doi.org/10.3897/jucs.104838.

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Recommender systems (RSs) are a relevant kind of artificial intelligence-based systems focused on providing users with the information that best fit their preferences and needs in a search space overloaded of possible options. Specifically, group recommender systems (GRSs) are a special type of RS centered on recommending items that are consumed in groups and not individually, being TV program and touristic packages key examples of such items. The current work is focused on proposing a content-based group recommendation approach (CB-GRS) contextualized to the restaurant recommendation domain.
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Xu, Sheng. "Intelligent Optimization Algorithm for Chain Restaurant Spatial Layout Based on Generative Adversarial Networks." Journal of Industrial Engineering and Applied Science 3, no. 3 (2025): 32–41. https://doi.org/10.70393/6a69656173.333031.

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This research presents an intelligent optimization algorithm framework for chain restaurant spatial layout generation based on Generative Adversarial Networks (GANs). Contemporary restaurant design methodologies rely on subjective expertise and static planning approaches that inadequately address dynamic operational requirements and evolving consumer preferences. The proposed GAN-based architecture incorporates a dual-generator framework with progressive upsampling modules and multi-head attention mechanisms specifically designed for restaurant spatial optimization. The multi-objective optimiz
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Megalia, Ujang Sumarwan, and Imam Teguh Saptono. "Analisis Strategi Bauran Promosi terhadap Volume Penjualan Restoran XYZ." MANAJEMEN IKM: Jurnal Manajemen Pengembangan Industri Kecil Menengah 12, no. 2 (2018): 161. http://dx.doi.org/10.29244/mikm.12.2.161-169.

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This study examines the strategic influence of promotion mix on the volume of aggregation and to know whether the marketing mix run by the Restaurant XYZ affect consumer spending. The theory used in this research is the promotion mix. The research design was conduced with a quantitative descriptive approach through an interview using quisionaire. Sampling method used is a purposive sampling technique with the number of respondents counted 200 people. In this study measure the influence caused by the promotion mix variables such as advertising, personal selling, sales promotion, public relation
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Sauper, C., and R. Barzilay. "Automatic Aggregation by Joint Modeling of Aspects and Values." Journal of Artificial Intelligence Research 46 (January 31, 2013): 89–127. http://dx.doi.org/10.1613/jair.3647.

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We present a model for aggregation of product review snippets by joint aspect identification and sentiment analysis. Our model simultaneously identifies an underlying set of ratable aspects presented in the reviews of a product (e.g., sushi and miso for a Japanese restaurant) and determines the corresponding sentiment of each aspect. This approach directly enables discovery of highly-rated or inconsistent aspects of a product. Our generative model admits an efficient variational mean-field inference algorithm. It is also easily extensible, and we describe several modifications and their effect
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Liu, Z., J. Wu, H. Li, and M. Werner. "SPATIO-TEMPORAL ANALYSIS OF URBAN ECONOMIC RESILIENCE DURING COVID-19 WITH MULTILAYER COMPLEX NETWORKS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-1/W2-2023 (December 13, 2023): 361–68. http://dx.doi.org/10.5194/isprs-archives-xlviii-1-w2-2023-361-2023.

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Abstract. The COVID-19 pandemic has impacted the economic growth of almost every country, with many industries facing operational difficulties, and the failures of a large number of restaurants, in particular, have extensively tested the resilience of urban economies. The gastronomy business is one of the most decentralized and location-based consumer business in urban, which is highly related to the economic attributes of cities. However, there are few studies on quantitative analysis of urban economic resilience through the opening and closing of restaurants. Understanding and planning for t
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Pépin, Jean Louis, Rosa Maria Bruno, Rui-Yi Yang, et al. "Wearable Activity Trackers for Monitoring Adherence to Home Confinement During the COVID-19 Pandemic Worldwide: Data Aggregation and Analysis." Journal of Medical Internet Research 22, no. 6 (2020): e19787. http://dx.doi.org/10.2196/19787.

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Background In the context of home confinement during the coronavirus disease (COVID-19) pandemic, objective, real-time data are needed to assess populations’ adherence to home confinement to adapt policies and control measures accordingly. Objective The aim of this study was to determine whether wearable activity trackers could provide information regarding users' adherence to home confinement policies because of their capacity for seamless and continuous monitoring of individuals’ natural activity patterns regardless of their location. Methods We analyzed big data from individuals using activ
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Conference papers on the topic "Restaurant aggregation"

1

Batumalai, Theventharan. "The Influence of Review Richness and Valence on the E-WOM Trustworthiness." In Liberec Economic Forum 2023. Technical University of Liberec, 2023. http://dx.doi.org/10.15240/tul/009/lef-2023-34.

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This study aims to examine the relationship between review richness and valence in the context of the trustworthiness of electronic word-of-mouth when choosing a coffee shop. The study collected data through an experiment on a simulated restaurant aggregator platform involving eight coffee shops and reviews with varying richness and valence. Participants (130 individuals) were asked to rate the cafés based on their preferences for selecting one. The findings highlight the relative importance of review richness compared to the review's positive or negative sentiment in influencing trustworthine
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