隨著電子商務的蓬勃發展，線上商家陸續林立，線上購物亦成為消費者購物時的熱門選擇之一。然而，根據研究報告指出，由於「可以親自實際接觸商品」此優勢，多數的消費者依然偏好在實體商店購物。因此，甚至連電子商務的巨擘──亞馬遜也在2015年展開了第一間實體商店。在如此眾多的商店選擇之下，能提供消費者購物建議的服務便成為一個新興的應用趨勢。現今的購物推薦服務主要可分為「提供消費者可能感興趣的商品項目」，以及「提供某項商品最低價格選擇」兩大類。此論文提出的服務屬於後者，為一個可以提供消費者購物商家建議的行動應用程式，可針對使用者的「購物清單」進行商家篩選，而非僅只於單項商品做比較；進行篩選的商家則是以消費者位置周邊一定範圍內的商家為對象。除了提供消費者最低價的購物選擇，本論文亦提出了「最少購物商家總數」以及「最短購物距離」兩種推薦演算方式供消費者選擇。應用程式實作的部分則以Android 系統完成。

Resulting from the flourish of electronic commerce and the growing of online retailing, online shopping becomes a popular choice for consumers to shop. However, it is reported that most of consumers still prefer to shop in-store rather than shopping online due to the fact that consumers can "touch and feel" the products while shopping in a physical store. In particular, even Amazon, an online retailing giant, opened its first brick-and-mortar store in 2015. With the multiple choices for shopping, it becomes an emerging service trend to provide consumers shopping recommendations. Existing applications for shopping recommendation can be broadly divided into two categories. One is providing consumers the products which they may be interested in. The other is comparing product prices at different stores for consumers. This thesis proposes a mobile app, which belongs to the latter group, to recommend consumers the stores to shop. Different from current existing recommending services, this application sorts the stores based on the shopping list of consumers instead of one product only. Stores are filtered by the location information of consumers before the sorting process, i.e., a store which is near to the consumer is selected into the sorting process. In addition to providing the stores where the consumers can purchase their items at the lowest price, this app provides another two store-sorting choices for consumers, including "least shopping store amount" and "shortest traveling distance". The implementation of this app was implemented on Android system.

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