Open AccessGraph Based Personalized Travel Recommendation Using Data Mining Technique Collaborative Filtering Algorithm
Author(s) -
Miss. Samradni Deshmukh,
Prof. K. R. Ingole
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.40739
Subject(s) - collaborative filtering , recommender system , computer science , tourism , metadata , information retrieval , graph , similarity (geometry) , data mining , world wide web , image (mathematics) , geography , artificial intelligence , theoretical computer science , archaeology
The recommendation system has growth choices in recent years. The recommendation system is exist 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. Keywords: Travel package, recommender systems, cocktail, topic modeling, and collaborative filtering