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Job match software: how it works

Matchdragon is a web application based on eggMatch© software, which utilizes artificial intelligence algorithms to compare coherent pieces of information in a variery of formats (text, documents, images, databases etc.).

Although eggMatch©'s design is covered by industrial secret, a short introduction to its implementation on Matchdragon job portal is presented below.

Matchdragon collects both structured and full-text information. Structured information basically consists in a set of fields with a pre-defined set of values, which every user can pick up to define her/himself or what she/he needs (for example, "study degree", "work experience", etc.). Full-text information is rather a free text input by either employers or job seekers (such as "job description" or "resumé summary", or the resumé pdf file to be uploaded by job seekers).

Matchdragon's engine analyses both types of information and evaluates them by passing each job offer/resumé through a pipeline of "filters" based on artificial intelligence analysis, relevance estimation, machine learning and natural language processing techniques. Finally, when interrogated by a user, it compares the whole user profile (both structured and full-text information) with all available jobs/resumés, and calculates an accurate match rate for each of them.

Matchdragon's filter pipeline is based on the concept of context and proximity, which allows to point out not only "perfect matches" (i.e. the same skill or expression appearing in both a job offer and a resumé) but also "close" matches (by ponderating the meaning of certain pieces of information instead of their spelling). Thanks to the very nature of its underlying technologies, the accuracy of the auto-match improves over time while the amount of information known by the system grows.

Long story short, it works like a very advanced search engine, except that it doesn't require you to make any search, as it considerates the whole resumé/job offer profile for you, instead of responding to few "keywords".