公开(公告)号：US20210117873A1

公开(公告)日：2021-04-22

申请号：US16736284

申请日：2020-01-07

Applicant: Oracle International Corporation

Inventor： Andrew VAKHUTINSKY ,  Setareh Borjian BOROUJENI ,  Saraswati YAGNAVAJHALA ,  Jorge Luis Rivero PEREZ ,  Dhruv AGARWAL ,  Akash CHATTERJEE

IPC: G06Q10/02 ,  G06Q10/04 ,  G06Q50/12 ,  G06Q10/06

Abstract: Embodiments provide optimized room assignments for a hotel in response to receiving a plurality of hard constraints and soft constraints and receiving reservation preferences and room features. The optimization includes determining a guest satisfaction assignment cost based on the reservation preferences and room features, determining an operational efficiency assignment cost, generating a weighted cost matrix based on the guest satisfaction assignment cost and the operational efficiency assignment cost, and generating preliminary room assignments based on the weighted cost matrix. When the preliminary room assignments are feasible, the preliminary room assignments are the optimized room assignments comprising a feasible selection of elements of the matrix. When the preliminary room assignments are infeasible, embodiments relax one or more constraints and repeat the performing optimization until the preliminary room assignments are feasible.

公开(公告)号：US20210118071A1

公开(公告)日：2021-04-22

申请号：US16719040

申请日：2019-12-18

Applicant: Oracle International Corporation

Inventor： Dhruv AGARWAL ,  Akash CHATTERJEE ,  Anirban BANERJEE

IPC: G06Q50/12 ,  G06N5/04 ,  G06Q30/06 ,  G06Q30/02

Abstract: Embodiments provide recommendations to a guest of a hotel or other type of service industry. Embodiments receive input data including demographics data and preference data for a plurality of guests of the hotel, and receive a plurality of guest interest categories. Embodiments assign one or more keywords to each of the guest interest categories and extract a plurality of attributes from the input data concerning the guest. Embodiments perform semantic analysis to map the attributes to the guest interest categories and determine a plurality of guest similarity calculations comprising a similarity value each of the plurality of guests with every other plurality of guests. Embodiments then generate a plurality of guest interest categories predictions for each of the guests based on the determined guest similarity calculations.