【正文】 The staff will automatically and almost instantly be notified about the new order so that they can act on it. If the establishment allows, the user may even track the status of their order so that they know when to expect their food and drinks to land up on their table. Remendation Overview The remendation algorithm is an innovative feature that we aim to include in our menu. When most tablet menus provide the customers with only a simple menu, this system will provide remendations which will make it easier to build an order considering what other customers have ordered previously or the similarities between various dishes. Remendation systems using sets were considered . We finally decided to use the below methodology, which has been discussed in an earlier study. The algorithm mainly has 5 parts: 1. Users a certain number of people are made to rate individual food items. 2. Entities the food items. 3. Value Dimensions the categories that are formed to rate the food items . Price, quality, meat content, etc. 4. Belief System is personal to each user amp?，F(xiàn)有的程序提供了能讓餐廳把菜單放到基于 IOS 和Android 的設(shè)備上使用的應(yīng) 用，使得用餐者在菜單上能瀏覽、點(diǎn)菜和刷卡。傳統(tǒng)的餐飲服務(wù)要求服務(wù)員與客戶在處理他們的 訂單前直接互動(dòng)?？梢哉f(shuō)電子菜單節(jié)省了成本，且客戶更多地參與到這個(gè)過(guò)程中。 推薦算法基于顧客以前的菜單。 雖然這個(gè)過(guò)程很簡(jiǎn)單，它可能會(huì)顯著增加服務(wù)員的工作量，甚至導(dǎo)致訂餐錯(cuò)誤或客戶優(yōu)先次序混亂，尤其是在客戶數(shù)量突然增加的繁忙時(shí)間，這會(huì)嚴(yán)重降低整體服務(wù)質(zhì)量。這對(duì)顧客和員工來(lái)說(shuō) 是毫無(wú)新意的。它們通過(guò)靜態(tài)網(wǎng)絡(luò)技術(shù)來(lái)訪問(wèn)數(shù)據(jù)庫(kù)。顧客也就可以更快地查看菜單。工作人員馬上就能收到訂單，并開(kāi)始工作。 喜好 根據(jù)顧客喜好推薦菜肴。 Jaccard指數(shù)可以用來(lái)估算相似度。在我們的模型中，我們使用的是 Jaccard系數(shù)。 數(shù)據(jù)庫(kù)使用日益流行的 MySQL作為為數(shù)據(jù)庫(kù)管理系統(tǒng)。它可以被 8 歲到 80 歲的人使用，不管他們的文化和背景是怎么的。 保持服務(wù)器的安全性。廚房端主要是全面地顯示從客戶端發(fā)來(lái)的最新訂單。基于移動(dòng)設(shè)備顧客的訂單通過(guò)互聯(lián)網(wǎng)實(shí)現(xiàn)即時(shí)傳輸?shù)綇N房準(zhǔn)備餐點(diǎn)。集中服務(wù)器可以讓各個(gè)餐廳共享顧客的數(shù)據(jù)，如果顧客和其他餐廳同意的話，然后軟件還能幫助用戶給食客提供更好的建議和體驗(yàn)。這主要是因?yàn)閕pad具有分辨率很高的顯示器和很高的知名度。因此，采用先進(jìn)的技術(shù)來(lái)提高服務(wù)質(zhì)量的話題，近年來(lái)備受關(guān)注。 服務(wù)器停機(jī)。 因?yàn)楹芏嗥髽I(yè)和個(gè)人的私人信息將存儲(chǔ)在我們的數(shù)據(jù)庫(kù)中。 現(xiàn)有的系統(tǒng)與推薦的系統(tǒng)比較 表 系統(tǒng)比較 現(xiàn)有的系統(tǒng) 推薦的系統(tǒng) 操作系統(tǒng) Ios Android 通信通道 客戶身份識(shí)別 RFID用于識(shí)別客戶需要額外的硬件 客戶身份識(shí)別 RFID用于識(shí)別客戶需要額外 的硬件 保持在數(shù)據(jù)庫(kù)服務(wù)器中的用 戶帳戶 服務(wù)器位置 本地化服務(wù)器 集中式服務(wù)器 推薦系統(tǒng) 不推薦 推薦 排他性 獨(dú)立的 可以擴(kuò)展到由多個(gè)場(chǎng)所可以 使用 功能概述 在本節(jié)中，我們將不詳細(xì)介紹系統(tǒng)的功能，而是從宏觀角度來(lái)介紹這個(gè)軟件。我們將使用相同服務(wù)來(lái)保持低成本和維護(hù)的簡(jiǎn)便性。這涉及到用機(jī)器學(xué)習(xí)技術(shù)來(lái)調(diào)整數(shù)據(jù)集。 錄入所有食品的信息后，我們的下一個(gè)任務(wù)是給它們分類。我們最終決定使用下面的，在一項(xiàng)較早的研究中討論過(guò)方法。這是我們系統(tǒng)最重要的一個(gè)部分，不僅提升了客戶的體驗(yàn)，還可以提高業(yè)務(wù)收入。依照這個(gè)信念，軟件的使用者會(huì)被給予大量的重視。 圖 基本的系統(tǒng)架構(gòu)和系統(tǒng)組件 該系統(tǒng)有以下幾部分：由 Web 服務(wù)器和數(shù)據(jù)庫(kù)組成的終端和由客戶端、管理端、廚房端組成的前端。 雖然 相對(duì)于紙和筆來(lái)說(shuō)，它是個(gè)很大的進(jìn)步且在世界上得到廣泛的使用 ， 但這不會(huì)給客戶帶來(lái)太多的好感和只是有益于餐廳管理和收入。 但沒(méi)有的應(yīng)用程序，顧客只能直接到廚房下定單。有了這個(gè)電子菜單，訂單可以在第一時(shí)間被確定。設(shè)備消除一些人為的點(diǎn)錯(cuò)單的問(wèn)題，減少?gòu)N房的混亂，因?yàn)楝F(xiàn)在一切都寫(xiě)得很清楚。 關(guān)鍵詞： 推薦，平板電腦，菜單，智能， Android應(yīng)用，餐廳。 the terminal Customer identification RFID used to identify customers Additional hardware required User accounts maintained in the database server Server location Localized server Centralized server Remendation System Remendations not implemented Remendations implemented Exclusivity Exclusive to every establishment Can be extended to be used by multiple establishments Feature Overview In this section we won’t go into the detailed features of the system, but instead take a bird’s eye look at the same. Intuitive, Beautiful amp。 workshop on Advanced Computing 2020 (ICWAC 2020) 中文 4190字 Intelligent eRestaurant using Android OS ABSTRACT： The simplicity and ease of access of a menu are the main things that facilitate ordering food in a restaurant. A Tablet menu pletely revolutionizes the patron’s dining experience. Existing programs provide an app that restaurants can use to feed their menus into IOS amp。 allows telling the system what ideal value they want each value dimension to have. 5. Ideal candidate set of ideal value dimensions that are formed on the basis of a weighted average. Each User rates a food item on a scale of 1 to 5 with respect to two things: 1. User’s ideal value dimension. 2. The weight or the importance of that value dimension. With the food items set in place, our next task was to analyze the various attributes that were associated with each food item. We applied a food item click counter to the entire data set, which produced a list of the most viewed food item. After listing out the Top N clicked fooditems by the customers, we apply normalization to the retrieved list of fooditems, to filter out redundant clicks. We further investigate the levels of monality that existed between various pairs of food items. Jaccard’s coefficient was used to calculate the degree of similarity. The Jaccard index, also known as the Jaccard similarity coefficient (originally coined coefficient de munaute by Paul Jaccard), is a statistic used for paring the similarity and diversity of sample sets. The Jaccard coefficient measures similarity between sample sets, and is defined as the size of the intersection divided by the size of the