Checked-in hotel surrounding life recommending system and method based on machine learning statistical model

A statistical model and machine learning technology, applied in transmission systems, instruments, computing, etc., can solve problems such as time-consuming and troublesome

Active Publication Date: 2017-10-24
苏州发飚智能科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Consciously doing some strategies

Method used

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  • Checked-in hotel surrounding life recommending system and method based on machine learning statistical model
  • Checked-in hotel surrounding life recommending system and method based on machine learning statistical model
  • Checked-in hotel surrounding life recommending system and method based on machine learning statistical model

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Embodiment Construction

[0074] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will be described in detail in conjunction with the accompanying drawings and specific embodiments;

[0075] The main idea of ​​the present invention is that after the user books a room on the system platform and checks in, the system platform will recommend to the user the living surroundings, eating, drinking, and entertainment business circles, urban characteristic locations, characteristic food, entertainment, office and other location information near the hotel, To facilitate users to travel.

[0076] Based on the user's historical behavior data, the data near the housing, and the local data of the housing city, the platform calculates the relevant content that should be recommended to the user, and then displays it on the platform. This scheme believes that the longer the user stays in a place, the more interesting the place is t...

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Abstract

The embodiment of the invention provides a checked-in hotel surrounding life recommending system based on a machine learning statistical model. The system is characterized by comprising an information acquisition module for acquiring user data, corresponding related information of urban geological positions and POI (point of interest) data of a map APP (application); a data storage module for storing data based on class in formatted manner, storing data acquired by the information acquisition module, and data calculated via an algorithm module; the algorithm module for calculating and training data via the algorithm DBScan; a matching strategy module for executing a user-residence and user-city POI matching strategy, wherein the matching strategy performs different strategies or a combination of the strategies according to service logic, user interest or user-fed city weather; a recommending engine module for displaying to a user, matched POI coordinate data. The invention also provides a checked-in hotel surrounding life recommending method based on the machine learning statistical model.

Description

technical field [0001] The present invention relates to the technical field of e-commerce data processing, in particular to the technical field of location-based data push; Background technique [0002] For many people looking for short-term rental housing, they need to make some travel strategies and itinerary arrangements by themselves. Living in an unfamiliar city, I don’t know what places to eat, drink and have fun near the residence, and I don’t know what places to eat, drink and have fun in the whole city and the characteristics of the city. Consciously doing some strategies is time-consuming and troublesome. Based on the user's historical travel behavior habits, the travel habits of the previous local users and other information, the system provides the user with travel information such as eating, drinking and playing places near the hotel, staying in the city for tourism, office, and characteristic places. [0003] Many current mobile APPs only send local travel ch...

Claims

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Application Information

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IPC IPC(8): G06F17/30H04L29/08
CPCG06F16/9537H04L67/52H04L67/55
Inventor 刘洋
Owner 苏州发飚智能科技有限公司
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