{"id":9495,"date":"2018-10-10T14:32:02","date_gmt":"2018-10-10T14:32:02","guid":{"rendered":"https:\/\/wordlift.io\/blog\/en\/?p=9495"},"modified":"2022-12-29T17:29:17","modified_gmt":"2022-12-29T16:29:17","slug":"knowledge-graphs-travel","status":"publish","type":"post","link":"https:\/\/wordlift.io\/blog\/en\/knowledge-graphs-travel\/","title":{"rendered":"How knowledge graphs can help your travel brand attract more visitors"},"content":{"rendered":"

For the first time this year we can finally say that knowledge graphs<\/a><\/strong><\/span> and semantic technologies<\/strong> are hype. People like me, who played with the semantic web stack for several years now, have long predicted that one day we would have a Graph for Everything. We did wait for long and hopefully not in vain ? until recently Gartner finally shout out loud that 2018 is indeed the “Year of the Graph”<\/span><\/a>. We, here at WordLift, are far beyond the hype. We have built technologies, open source frameworks, companies and products on this vision of semantic web<\/a>, knowledge representation and ontologies. <\/span><\/p>\n

\"Knowledge
Knowledge Graphs in the Gartner’s Hype Cycle for 2018.<\/figcaption><\/figure>\n

For many years, way too many, talking with large enterprises or public institutions like the Italian Parliament about the importance of creating taxonomies and labeling information has been extremely frustrating, and yet I am very thankful to everyone who has listened to me and helped us get to the point of writing an article like this one.<\/span><\/p>\n

Knowledge graphs are real<\/b> and bring a competitive advantage to large enterprises like <\/span>Amazon<\/span><\/a>, <\/span>Google<\/span><\/a>, <\/span>LinkedIn<\/span><\/a>, <\/span>Uber<\/span><\/a>, <\/span>Zalando<\/span><\/a>, <\/span>Airbnb<\/span><\/a>, <\/span>Microsoft<\/span><\/a>, and other internet powerhouses but no, this article is not about giant graphs from large enterprises. It is about our direct experience in helping<\/span> travel brands<\/b> like <\/span>bungalowparkoverzicht<\/b><\/a> in the Netherlands, the largest <\/span>tour operator in Iceland<\/span><\/a> and SalzburgerLand in Austria. <\/span><\/p>\n

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WHAT IS A KNOWLEDGE GRAPH?<\/h6>\n

A knowledge graph is a way of representing human-knowledge to machines. In short, you start by defining the main concepts as nodes and the relationships\u00a0among these concepts as edges in a graph. READ MORE<\/a><\/p>\n

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Not all Graph are created equal and each organization has its own business goals and ways of representing relationships between related entities. We model data and build knowledge graphs to create a context, to improve content findability by leveraging on semantic search engines like Google and Bing and to provide precise answers to certain questions. When you have organized your data semantically and you have built your own taxonomy there are many applications that can be implemented: from classifying items to integrating data coming out of different pipelines, from building complex reasoning systems, to publishing metadata on the web. When we built the knowledge graph for a travel brand like <\/span>bungalowparkoverzicht<\/b><\/a> our main focus was on the type of information that a traveler would need before reaching the destinations.<\/span><\/p>\n

We model data for the so-called \u201cplanning and booking moments\u201d. Planning, accordingly to <\/span>a research from Google<\/span><\/a>, starts when a digital traveler has chosen a destination and is then looking for the right time and place to stay. Then the booking will follow, and that\u2019s the moment when the travelers move into reserving their perfect hotel, choose a room and reserve it. <\/span><\/p>\n

Types of Information to model for the planning and booking moments<\/span><\/h2>\n

When modeling hotel-related information in Web content using the schema.org vocabulary you basically work with three core type of nodes (entity types):<\/span><\/p>\n