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Hotel full-room prediction method, system and device and storage medium

A forecasting method, hotel technology, applied in forecasting, instrumentation, character and pattern recognition, etc., can solve problems such as customer withdrawal, affecting customer experience, etc.

Pending Publication Date: 2020-10-30
CTRIP COMP TECH SHANGHAI
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the above reasons, the existing booking process often causes some customers to be withdrawn after placing an order, which seriously affects the customer experience

Method used

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  • Hotel full-room prediction method, system and device and storage medium
  • Hotel full-room prediction method, system and device and storage medium
  • Hotel full-room prediction method, system and device and storage medium

Examples

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Embodiment Construction

[0036] Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art. The same reference numerals denote the same or similar structures in the drawings, and thus their repeated descriptions will be omitted.

[0037] figure 1 It is a flow chart of the hotel full room prediction method of the present invention. Such as figure 1 As shown, the embodiment of the present invention provides a kind of hotel room full prediction method, comprises the following steps:

[0038] S110. Obtain historical order data of the hotel;

[0039] S120. Perform data indexing on the historical order data, including at least full rooms after booking...

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Abstract

The invention provides a hotel full-room prediction method, system and device, and a storage medium. The method comprises the steps: obtaining the historical order data of a hotel; performing data indexing on the historical order data, at least including taking a reserved full room as a positive sample and taking a reserved normal check-in as a negative sample, inputting the historical order dataas a learning sample into a prediction model, and predicting the probability of the reserved full room of the hotel; obtaining a hotel set according to the current retrieval condition of the user, taking the retrieval condition and the name of each hotel in the hotel set as a data set to be sequentially input into the trained prediction model, and obtaining the probability that each hotel is fullafter reservation; and only displaying hotel information of which the probability of room fullness after reservation is lower than a preset threshold to the user. The method can accurately and efficiently predict the full-house probability, thereby reducing the full-house proportion, effectively preventing the customer from being withdrawn after ordering, and obviously enhancing the user experience.

Description

technical field [0001] The invention relates to the field of hotel reservations, in particular to a method, system, device and storage medium for predicting full rooms in a hotel. Background technique [0002] In the process of users booking hotels, some users will receive a message that the order is full after placing the order, which will not only seriously affect the user experience, but may also lead to the loss of users. Seriously, users will also spread the word through social networks, affecting the purchases of other groups of people, which will greatly affect the brand image of the room reservation platform. The reason for the full room is mainly because the hotel supplier does not maintain the room status information in time, and at the same time, some hotels are oversold. From a technical point of view, each hotel will greatly protect its own room data, and will not synchronize the room data to the reservation platform in real time to a large extent. Because of ...

Claims

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Application Information

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IPC IPC(8): G06Q50/12G06Q10/04G06K9/62
CPCG06Q50/12G06Q10/04G06F18/2415G06F18/214
Inventor 黎建辉吉聪睿李巍
Owner CTRIP COMP TECH SHANGHAI
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