Design And Implementation Of Personalized Restaurant Recommendation System Based On Word2Vec

With the rapid development of Internet and information technology,people came into the era of information overload.In order to helping people find what they want in a large amount of information,the recommendation system is appearing.Although the recommendation system relieves the problem of information overload to a certain extent,there are still some hard problems such as sparseness of data,through the user behavior is difficult to associate similar items,recommend to the users' items are more single,and it is difficult to find the users' new points of interest.These problems severely constrain the performance of the recommendation system.To optimize the existing recommendation algorithm from different aspects such as accuracy,coverage and diversity,this paper presents a recommendation model based on Word2 Vec model.The core idea of the recommendation model is to treat the restaurant that users' visited as the context of a word,then train the Word2 Vec model to get the vectors of every restaurant.And then according to the user's score of the restaurants and the restaurants' vectors to get the users' vectors.And then calculate the restaurant similarity and user similarity.Combined with the traditional recommendation algorithm to get the final recommendation results.The main work of this paper is as follows:(1)Introduced the background of the personalized restaurant recommendation system,the state of recommendation system in the world.(2)Research and analysis of the related techniques and algorithms,such as recommendation system theory and algorithm,Word2 Vec language model,the engineering technology of recommendation system,evaluation of indicators and so on.(3)A recommendation model based on Word2 Vec is proposed.In order to verify the feasibility of the recommended model,six algorithms are compared from three aspects: accuracy,coverage and diversity.The experimental results show that the recommendation model is improved compared with the traditional recommendation.(4)Designed the client and server side of personalized restaurant recommendation system based on Word2 Vec for the recommendation model.The client is used to collect the users' evaluation data of the restaurant,display the recommendation results,the server is used to manage the data,recommendation processing engine and so on.(5)Built the client and server of the personalized restaurant recommendation system based on Word2 Vec model,and reveal the user interface of the system.