How uses Machine Learning to Inspire Travellers

Applied Machine Learning Meetup

This blog post is about the Applied Machine Learning Meetup which I attended at’s Amsterdam office. They described their use of Latent Dirichlet Allocation to identify patterns in travel and booking data and suggest travel destinations to their users.

Athanasios Noulas, the presenter, has published this paper on the topic, along with Mats Einarsen, where you can find all the details if needed.

Interestingly, the Latent Dirichlet Allocation method was first described in this paper, with one of its contributors being Andrew Ng, whose Stanford University machine learning MOOC course led to the founding of Coursera and who once worked for Google and now works for Baidu in AI research.

I have found this blog post on the topic by Edwin Chen to be a good introduction to the approach.

The method itself is used to analyse text data to identify subject groupings or topics. The method traverses documents, and assigns probabilities of words in the document belonging to certain topics. It then refines these probabilities (learning) iteratively until it has a reasonable topic grouping of words.

At they capture endorsements provided by travellers for destinations they have visited. This takes the format of cities like London or Bangkok and activities people enjoyed there like shopping, dining or surfing.

User Engagement through Topic Modelling in Travel

The document for analysis in this case is the combination of a single booking with the related endorsements the user has made afterwards. The end result of the modelling process is groups of characteristics and cities that match these characteristics. These groupings are ultimately used to make recommendations to people based on a grouping they fit into.

User Engagement through Topic Modelling in Travel

This data is later used on the website and in emails with some success to provide people with destinations they might enjoy.

I found the talk pretty interesting and especially so to learn about LDA (yes, we’re on a first-name basis now) and generally about AI methods we encounter in everyday life. Also interesting was the number of people who signed up (133) and attended the meetup (I counted about 60, could be more) which I thought was pretty impressive. It seems like interest in AI is spiking and it’s quite intriguing to see what the future will hold for this domain.


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