Commodity recommendation method compatible with O2O applications in internet plus tourism environment

Abstract

The invention discloses a commodity recommendation method compatible with O2O applications in an internet plus tourism environment. The method can be realized through the following steps. First, a tourist chooses a scenic spot to be visited and accesses all available commodities there from the scenic spot inquiring data base. The weight of each commodity is then initialized by the consideration of their click conversion rate and recorded sales. Records of commodities the tourist has browsed, purchased, added to his favorite or disliked will also be checked so as to update the weights of all the commodities. A collaborative filtering recommendation algorithm will be adopted to further update the weights of the commodities. The commodities are then listed in piles according to their weights from high to low and a certain amount of commodities enjoying the highest weights are then chosen as recommended commodities in a temporary list. Then an Apriori algorithm, a basic algorithm of frequent set of items mining method, will be adopted for possible packages of commodities to be purchased. The temporary list with recommended commodities is divided into two halves where the recommended commodities can be all browsed from high weights to low weights and each commodity will be re-listed so that the commodities at the first top half of the temporary list are the final ones to be recommended to the tourist.

Description

technical field [0001] The invention relates to the field of Internet, especially the data processing field of computer network travel information service, especially the product recommendation method supporting O2O application under the "Internet + travel" environment. Background technique [0002] In recent years, with the progress of society and the improvement of people's living standards, tourism is becoming an increasingly popular way of pastime. However, when people arrive at a scenic spot and face a variety of commodities, it is difficult for tourists to know the commodities they really need, and many people are even deceived when choosing commodities. Therefore, product recommendations based on mobile apps for tourist attractions can just help tourists find the products they may need, and referring to previous product purchases and reviews can also greatly reduce the probability of being deceived. On the other hand, for scenic spots, it can also increase their over...

AI Technical Summary

Problems solved by technology

Chinese patent "A Product Information Recommendation Method and System", application number: 201010273633.1, authorized announcement number 102385601A discloses a product information recommendation method and system, this method only recommends products based on the user's historical records, and does not use similar User preference data for recommendation

Chinese patent "A Product Recommendation Method for E-Commerce Website Based on Keywords", application number: 201210050057.3, authorized announcement number 102629257A discloses a method for recommending products on an e-commerce website based on keywords, which is only based on the user's historical records Commodity recommendation does not perform data processing on the recommended order of commodities, nor does it consider the mutual influence of sales data between commodities

[0005] However, the product recommendation system based on scenic spots will change with the location where tourists arrive each time, instead of only one product collection for the entire recommendation system.

On the other hand, considering that there may be a tendency for multiple products to be purchased together, putting these products together is likely to increase tourists' desire to buy, and these two aspects are exactly what the above-mentioned recommendation systems recommend. Factors not to be considered

Therefore, the existing recommendation system cannot be directly applied to product recommendation based on attractions.

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