Skip to main content

Introducing the MakCorps Hotel Review Summaries

We are happy to announce the release of this new product which uses Big Data and Sentiment Analysis to transform guest reviews into highly relevant, auto-generated content for travel websites and apps.
The travel industry is aware of the important role guest reviews play in the hotel booking process of consumers. Every party wanting to sell hotel rooms online is faced with the same two problems if they don’t want to risk losing visitors to competitors or Google:
  1. Where to get reviews from?
  2. How to present them, so that the offer a real value?

Creating valuable content

With the Hotel Review Summaries we aim to solve both problems. The engine automatically generates highly relevant content based on reviews from dozens of review sites on the web.

Peter Boermans (CPO) describes our approach like this: “Sit down an average traveler, ask them to read a hundred hotel reviews and then have them write a brief summary. Now create an engine which produces the exact same outcome.”
This is not something you build and then never touch again. We are committed to continuously enhancing it.
MakCorps relies on technologies such as Big Data, Natural Language Processing and Sentiment Analysis to extract relevant data from the millions of guest reviews and ratings on the web.

Built as platform

The Hotel Review Summaries engine is built as a platform able to digest any kind of data and to turn it into a dynamic list of interesting statements in a human, hand-written style.
Right now the summaries take ratings and the analyzed review texts into account. We are evaluating which other sources the engine could tap into. Every summary gets updated at least once a day as new reviews get published.

Designed for flexibility

The advantage of the platform is that customers, who want to implement the summaries into their site or app can customize the structure and content. Statements can be filtered out, rewritten or even added making use of data the customers have about their inventory.
Why is this important? Our CEO Kim van den Wijngaard explains it: “Every booking site has unique visitor demographics. Some focus on niche segments and some have specialized inventory. There cannot be the one solution which fits every case. That is why we put so much emphasis on flexibility. ”
We believe the Hotel Review Summaries are primarily interesting for consumer-facing OTAs, deal and meta search sites and apps. We are currently considering how hotels could benefit from it as well.
More information here on our website.

Comments

Popular posts from this blog

30 Amazing Machine Learning Projects for the Past Year (v.2018)

For the past year, we’ve compared nearly 8,800 open source Machine Learning projects to pick Top 30 (0.3% chance). This is an extremely competitive list and it carefully picks the best open source Machine Learning libraries, datasets and apps published between January and December 2017. Mybridge AI evaluates the quality by considering popularity, engagement and recency. To give you an idea about the quality, the average number of Github stars is 3,558.
Do visit our Hotel price comparison api which compares more than 200 hotel websites to get you the best possible price of your dream hotel.
Python Projects of the Year (avg. 3,707 ⭐️): Here(0 duplicate)Learn Machine Learning from Top Articles for the Past Year: Here(0 duplicate) Open source projects can be useful for data scientists. You can learn by reading the source code and build something on top of the existing projects. Give a plenty of time to play around with Machine Learning projects you may have missed for the past year…

Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data

Over the past few months, I have been collecting AI cheat sheets. From time to time I share them with friends and colleagues and recently I have been getting asked a lot, so I decided to organize and share the entire collection. To make things more interesting and give context, I added descriptions and/or excerpts for each major topic. This is the most complete list and the Big-O is at the very end, enjoy… If you like this list, you can let me know here Neural Networks

Neural Networks Cheat Sheet Neural Networks Graphs

Neural Networks Graphs Cheat Sheet



Neural Network Cheat Sheet Ultimate Guide to Leveraging NLP & Machine Learning for your Chatbot
Code Snippets and Github Includedchatbotslife.com
Machine Learning Overview

Machine Learning Cheat Sheet
Machine Learning: Scikit-learn algorithm This machine learning cheat sheet will help you find the right estimator for the job which is the most difficult part. The flowchart will help you check the documentation and rough guide of …

Building a Game using JavaScript : Part-1

Introduction I really wanted to write a tutorial about a game technology I like to use, so here it is. In this story, we will start making a little shoot’em up game with PixiJS, a really simple and cool Javascript library. What we are going to do exactly is to make a spaceship able to move and shoot, enemy waves coming through and a beautiful animated background with moving clouds. The first part (this story) will focus on the background. Ready guys? Let’s nail it! Getting started Let’s start by setting up our project: I uploaded a code structure already set so we are all working with the same base. However if you want to make it yourself, I put a picture of my folder just below: Click here to download the starter project Project folder structure We will need a local server to run the game: I invite you to download WAMP if you’re working with Windows, or MAMP for macOS, they are free and easy to use. Let’s put your game folder in the server one (htdocs for MAMP / www for WAM…