Authors: Miss. Samradni Deshmukh, Prof. K. R. Ingole
DOI Link: https://doi.org/10.22214/ijraset.2022.41415
Certificate: View Certificate
The recommendation system has growth choices in recent years. The recommendation system is existing in many applications which gives online travel information for individual travel package. A new model named travel recommendation using data mining techniques which extracts the features like locations, travel seasons of various landscapes. Thus, it possesses the material of the travel packages and interests of tourists. Further extending E-TRAST model with the tourist-relation-area season topic model includes relationship with tourists. It includes mining significant tourist locations based on the user search trajectories of users on web and also derives a personalized travel algorithm recommendation system using travelogues and users contributed photos with metadata of this photo by comparing existing different technique. To suggest personalized POI sequence, first famous routes are stratified as per the similarity between user package and route package.
I. INTRODUCTION
As an emerging growth in travel companies provide which now provides online services. However, the rapid rush of online travel information imposes an increasing challenge for tourists who want to choose from a large number of available travel packages for satisfying their individual needs. Moreover, to increase the profit, the travel companies have to understand the preferences from different tourists and publish more affordable packages to tourist. Therefore, the demand for intelligent travel services is expected to increase dramatically. Since recommender systems have been successfully applied to enhance the quality of service in a number of fields it is the natural choice to provide travel package recommendations
II. LITERATURE SURVEY
III. SYSTEM DIAGRAM
IV. PROPOSED WORK
The system should be designed in such a way that only authorized people should be allowed to access some particular modules. The records should be modified by only administrators and no one else. The user should always be in control of the application and not the vice versa. The user interface should be consistent so that the user can handle the application with ease and speed. The application should be visually, conceptually clear.
V. SYSTEM DESIGNS
VI. ALGORITHM
Tourist Area Collaborative Relation Topic (TACRT)
A. Steps
User set {u1, u2……….un}.
2. Each user record saves into the system with security.
3. The request comes from various nodes with their ip addresses. The server sends the notification to each user set {Um1…….Umn}.
4. The system records interest of each user according to searching pattern.
User set {u1……………... un} U Interest Set {I1……… In}
5. Package recommendation phase activated according to mutual user account
Package Set { p1…………. Pn }
If( u1 = = I1)
Then
u1= p1
6. The step 5 repeat every time for each and every new and existing user.
Where,
u1……un indicates user list,
Um1…Umn indicates registration confirmation message
I1……In indicates user interested set
p1……pn indicates packages set
VII. MODULES
A. Admin Module
B. User Module
C. Travel Company Module
VIII. ACKNOWLEDGEMENT
First and foremost, I would like to express my sincere gratitude to my Prof. K. R. Ingole who has in the literal sense, guided and supervised me. I am indebted with a deep sense of gratitude for the constant inspiration and valuable guidance throughout the work.
In this paper the interests of the tourists and extract of the spatialtemporal correlations among landscapes are discovered by Data mining techniques. The output of Data mining techniques. i.e. topic distributions for developing a recommended approach on personalize travel package recommendation. The Data mining techniques captures the relationships among tourists in each travel group. The so far problem analysis is related to the drawbacks in previous works and also going to be used in the proposed system
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Copyright © 2022 Miss. Samradni Deshmukh, Prof. K. R. Ingole. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Paper Id : IJRASET41415
Publish Date : 2022-04-12
ISSN : 2321-9653
Publisher Name : IJRASET
DOI Link : Click Here