An Efficient Methodology Designed for Designing Travel Package

Experimental results demonstrate that the TAST model can capture the unique characteristics of the travel packages, the cocktail approach can lead to better

The final result indicate that the TAST model can effectively capture the key characteristics of the travel data and the cocktail approach is much more

In this system, we proposed a personalized travel sequence recommendation system by learning topical package model from enormous multi source social media: travelogs.

To solve the problem of providing personalized and sequential travel package recommendation, a topical package model is created using social media data in which

In this framework, we proposed a personalized travel sequence recommendation framework by taking in topical package show from colossal multi source social media: travelogues. The

Experimental results demonstrate that the TAST model can capture the unique characteristics of the travel packages, the cocktail approach can lead to better

To solve the problem of providing personalized and sequential travel package recommendation, a topical package model is created using social media data in which automatically

The TAST model can effectively grabs the individual characteristics of travel data and hybrid approach, so it is more efficient than old recommendation techniques for