Case Studies

Utilizing the Google Cloud Language API on a job listing site for optimized search results

The company Persol Career Co., Ltd. is operating various popular job listing sites in Japan, covering a lot fields such as full-time employment, part-time employment, training services, job consulting services and more.

Among their sites "doda" is very successful as it is one of the most popular job recruitment sites in Japan. In order to deliver a good search experience to their users, they are utilizing a Google Cloud Platform API which improves the search results.

We asked Mr. Hitoshi Baba and Mr. Akane Oto from the product development supervision department why they decided to use Google Cloud Platform, what benefits they have from using the API service and about the implementation process and architecture building.

What did you want to achieve and why did you choose Google Cloud Platform?

When it comes to job listing sites it's up to the company what categories, job functions and keywords they choose. Whether you find the job offerings you are looking for depends on how much you are familiar with the industry and relevant categories, keywords etc. In other words: If you don't know the exact search terms for what you are looking for you won't find the right job offerings. This is especially a problem for changing jobs across industries. Our goal was to improve the search results for people who experience these kind of difficulties.

Our idea was to automatically scan job descriptions for job characteristics, convert them into searchable tags and display them as recommendations to the users while they are searching, thus guiding them to the job offerings they are looking for and improving the overall user experience.

They looked at various open-source software and APIs from a development speed and cost perspective and came to the conclusion that using an API is the best choice. After that we looked for services that offer language processing APIs and based on the performance and long usage possibility we chose GCP.

We also tried some open-source software but it didn't even recognize fairly easy words. However, when we tested the "Google Natural Language API" on Google Cloud Platform we were impressed by the results and decided that is suited for the purpose of this project. The "Google Natural Language API" is a service on Google Cloud Platform that provides sentiment analysis, syntax and word analysis to understand human written natural text and is accessible through an API.

Benefits of using Google Cloud Platform

The Natural Language API can quickly process data and make it available for further analysis and usage. We valued excellent performance in detecting words that express characteristics of the jobs as well as automatically finding and adding category tags. Especially the precise analysis of sentence structures is impressive and makes us excited to see how it will perform and further improve in the future.

We have the mission to consistently and quickly develop new services and release them. A cloud that is able to handle a big amount of personal data is becoming more and more essential for this business-critical task. Google Cloud Platform enables flexible development and we feel that it's the most suitable platform for us.

Future outlook on GCP and working together with Cloud Ace

Right now we are planning to use the Natural Langauge API on our website "doda" to automatically analyze the description texts as well as company name and similar key information of the all the job submissions that are being submitted and improve our services.

As Google's services can support a lot of different languages such as Russian or Urdu we consider adding these language options to our page as well as soon as the Natural Language API receives these functions.

(The interview was held before Google released its "Cloud AutoML Natural Language" which gives the Natural Language API multi-language support.)

This is a translation of an article published by Cloud Ace, Inc.

Available online: https://www.cloud-ace.jp/case/detail21/