The Design And Implementation Of Mobile Meals-ordering System Based On Recomme-nded System

With the development of information technology,people are increasingly dependent on the network,shopping without leaving home has become a reality,meanwhile ordering-online has become increasingly common.After lots of investigation,I found that the meals-ordering and meals-recommending system will bring great convenience to people in the community.The distinctive features of our meals-ordering system is recommending users meals which they may like based on their preferences.This system will help users make a quick and enjoyable option when ordering meals,further facilitate the lives of people especially office workers,and improve social and working efficiency.Recommended system,also known as personalized recommendation system,will recommend users objects that match their interest based on their preferences.Most of the meals-ordering system at resent can not recommend meals based on user preferences.Help users make right choice will give their a better using experience when they have the choice phobia disorder facing a large number of businesses and meals.Some recommended systems may not make sense or the recommendation is not accurate for choosing a inappropriate recommended algorithm.Some recommended systems is not real-time,that is the speed of response is not optimistic which will affect the using experience;Some recommended systems have a weak ability on automated recommendation,which can only recommend based on user's preferences label,can not get the potential preferences based on user's behavior(history order).We use collaborative filtering algorithm when solving the problem.Collaborative filtering algorithm is often used to distinguish what may interested a given customer by analyzing other similar customers' preferences.Collaborative filtering is very hot in the field of global Internet for its excellent speed and robustness.Unlike traditional recommendation analyzing the contents directly based on content filtering,collaborative filtering analyzes users preferences to find similar users on,combine those similar users' evaluation to the given projects,then form a prediction of how many the similar users enjoy each project.Collaborative filtering algorithm based on projects can be divided into two steps: A.compute the similarity between the projects.We use adjusted cosine similarity in our system.B.generate a recommendation list based on similarity of projects and history of users behavior.This paper focuses on the design and implementation of mobile meals-ordering system based on collaborative filtering algorithm.We details the model,algorithm and architecture of system.The final version of our meals-ordering system has function as follow: registration and login,meals display,cart,settlement,orders management,settings management,meals management,complaints management,data analysis,etc.Then,we design a set of test cases to test the function and performance of our meals-ordering system.The test results indicate that our design meet the initial requirements,and there is no obvious defects.