Description:Technical field of invention:

The present invention relates to provide a deep learning based models for digital management and optimization of tourism information resources.

Background:

The tourism industry heavily relies on accurate and up-to-date information to offer tailored experiences to travelers. However, managing and optimizing the vast amount of tourism data can be challenging.

Existing approaches often lack the capability to efficiently handle the complexities and nuances of tourism information.

Therefore, there is a need for innovative solutions that leverage deep learning techniques to address these challenges.

Hence, our present invention discloses a deep learning based models for digital management and optimization of tourism information resources.

Groupings of alternative elements or embodiments of the invention disclosed herein are not to be construed as limitations. Each group member can be referred to and claimed individually or in any combination with other members of the group or other elements found herein. One or more members of a group can be included in, or deleted from, a group for reasons of convenience and/or patentability. When any such inclusion or deletion occurs, the specification is herein deemed to contain the group as modified thus fulfilling the written description of all Markush groups used in the appended claims.

The recitation of ranges of values herein is merely intended to serve as a shorth and method of referring individually to each separate value falling within the range. Unless otherwise indicated herein, each individual value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context.

The use of any and all examples, or exemplary language (e.g., “such as”) provided with respect to certain embodiments herein is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention otherwise claimed. No language in the specification should be construed as indicating any non-claimed element essential to the practice of the invention.

The above information disclosed in this Background section is only for enhancement of understanding of the background of the invention and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art.

Objective of the invention

The primary object of the present invention is to provide a deep learning based models for digital management and optimization of tourism information resources.

Summary of the invention:

The present invention relates to provide a deep learning based models for digital management and optimization of tourism information resources.

More specifically, these models encompass advanced algorithms that enable the efficient handling of large-scale tourism data, extracting valuable insights, and optimizing the information for enhanced decision-making and personalized recommendations.

The management and utilization of tourism information by using deep learning techniques, is improved tourism experiences for travelers and stakeholders.

Detailed description of invention:

The following description includes the preferred best mode of one embodiment of the present invention. It will be clear from this description of the invention that the invention is not limited to these illustrated embodiments but that the invention also includes a variety of modifications and embodiments thereto. Therefore, the present description should be seen as illustrative and not limiting. While the invention is susceptible to various modifications and alternative constructions, it should be understood, that there is no intention to limit the invention to the specific form disclosed, but, on the contrary, the invention is to cover all modifications, alternative constructions, and equivalents falling within the spirit and scope of the invention as defined in the claims.

In any embodiment described herein, the open-ended terms "comprising," "comprises,” and the like (which are synonymous with "including," "having” and "characterized by") may be replaced by the respective partially closed phrases "consisting essentially of," consists essentially of," and the like or the respective closed phrases "consisting of," "consists of, the like.

The present invention relates to provide a deep learning based models for digital management and optimization of tourism information resources.

More specifically, these models encompass advanced algorithms that enable the efficient handling of large-scale tourism data, extracting valuable insights, and optimizing the information for enhanced decision-making and personalized recommendations.

The management and utilization of tourism information by using deep learning techniques, is improved tourism experiences for travelers and stakeholders.

The system comprises several components and methodologies that work in conjunction to achieve efficient digital management and optimization of tourism information resources.

The system comprises of following components:

Data Acquisition and Preprocessing: Tourism data from various sources, such as online booking platforms, social media, and tourism agencies, is collected and preprocessed to ensure consistency and quality.

This step involves data cleaning, normalization, and integration to create a unified representation of the information.

Deep Learning Models: The invention employs state-of-the-art deep learning models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformer networks, to process and analyze the tourism data.

These models learn complex patterns and relationships within the data, enabling accurate predictions, sentiment analysis, and personalized recommendations.

Information Storage and Retrieval: Efficient storage and retrieval mechanisms are implemented to handle the large-scale tourism data.

The system is used advanced indexing techniques and distributed storage systems to ensure fast and reliable access to the information.

Optimization and Decision-making: The deep learning models are utilized to optimize tourism information resources.

This includes tasks such as dynamic pricing optimization, resource allocation, demand prediction, and sentiment-based decision-making.

The models continuously adapt and improve based on user feedback and evolving trends.

Method: the system having the following steps:

Step 1: Data acquisition and preprocessing of tourism information from diverse sources.

Step 2: Training deep learning models using the preprocessed data.

Step 3: Storing the processed information in an efficient and scalable manner.

Step 4: Utilizing the deep learning models for optimization and decision-making in the tourism industry.

In conclusion, the system encompass advanced algorithms that enable the efficient handling of large-scale tourism data, extracting valuable insights, and optimizing the information for enhanced decision-making and personalized recommendations.
, Claims:1. A deep learning based models for digital management and optimization of tourism information resources.

2. A deep learning based models for digital management and optimization of tourism information resources claimed in claim 1, the system encompass advanced algorithms that enable the efficient handling of large-scale tourism data, extracting valuable insights, and optimizing the information for enhanced decision-making and personalized recommendations.