Artificial intelligence is a term describing processes of intelligent automation and can be overused nowadays, but the market is flourishing and the power of the AI technologies available today is undeniable. In a continuous effort to provide the Rakuten Aquafadas employees with the latest insights, we had the honour of receiving Stella Zevio, a French PhD student from Paris 13 university.
Stella specialises in machine learning, semantic web and graph theory, and came all the way from the LIPN (computer science laboratory of northern Paris) to give a talk at the Rakuten Crimson House of Montpellier, where she took the time to introduce her thesis’ subject “Knowledge discovery and enrichment from text for expertise finding” and answer Rakuten Aquafadas employees’ questions, including developers, managers and interns!
How can artificial intelligence benefit enterprises today?
The latter is quite a recent research topic and is being used in both the academic and professional world. One of the main aspects of Stella’s research is to help enterprises figure out a way to automate their search and organisation of expertise (“i.e. an individual’s skill, knowledge, aptitude or behaviour”). This way, they can save time spent on such processes, and reduce costs.
This can be particularly interesting when an organisation is looking to allocate a specific task or project to an expert, making it more efficient and less costly to do so. Let’s say you want a team to work on an app development project on Android, thanks to expertise finding, you can make sure the selected employees have the required technical skills, such as knowledge of the Java language, C++ and others depending on your project’s needs.
How does it work?
Expertise finding relies on an array of work documents, ranging from resumes, activity reports and so on. Which will be analysed thanks to natural language processing (NLP), a technology that supports text mining by enabling the understanding of sentence structure, meaning, themes as well as author identification through statistical and machine learning methods.
After the text mining process is complete, an expert profile is created, which consists an individual’s profile with his or her skills, abilities and more, organised in a hierarchical way.
What other applications are there for AI?
Stella’s previous experience goes to show that artificial intelligence offers a wide range of possibilities, be it health data mining to design and implement medical prediction algorithms in France, the integration of NLP techniques for electronic health records in the U.S or metadata for manga and video games in Japan.
It is clear today that artificial intelligence technologies can free up time for higher-level strategic work that most likely leads to greater business results. Digital marketing is no exception, and the most common AI applications comprise:
- Content curation: which allows visitors to find content that is more relevant to them, Amazon and Netflix recommendation systems are a good example of content curation. There’s also room for content production but it is still very limited.
- Email automation: tools that use machine learning to analyse consumers’ data and determine the best timing to contact them as well as the amount of time to do so and choose email subjects that generate the most clicks.
- Chatbots: they use natural language processing and machine learning to give users the correct response, even to open questions. They can be particularly useful for customer service as they’re available 24/7 and answer different customers instantaneously.
- Mobile apps: the adoption of artificial intelligence in mobile app development has helped businesses in the last couple of years engage customers and drive more revenue. Thanks to better predictions and recommendations, in addition to better analytical capabilities and customer interactions. It also helped improve digital content management thanks to advanced in-app search features.
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