Due to "Merger": More than Rich

Due to "Merger": More than Rich

The innovative CV parsing module for applicant profile enrichment

 It's not a shame to be rich. And that's also a recruiter's opinion. So why should you settle only with the candidate's CV while an entire application portfolio with a cover sheet, a cover letter, certificates, reports and much more is at your disposal?
By integrating the CVlizer module HRmerger into the capture process of the application documents, this question becomes moot. The Merger enables a comprehensive candidate profile based on the contents of all documents received.

Due to "Merger": More than Rich
  • First, each document is categorized by a multilevel classification procedure using hybrid machine learning techniques. Distinctions are made between "cover sheet", "cover letter", "curriculum vitae", "school certificates", "certificates" and "references".

  • The next step is the semantic analysis of the CV. So we have a first interim result: the semantically normalized, machine-processable candidate profile, which is the base for all subsequent processing steps.

  • Next, the remaining documents are semantically processed and converted into a structured attachment. Therefor, a variety of characteristics are taken into account. In a school report, for example, every single school subject is extracted and the school grade is converted into an internationally comparable value. Additionally, an average mark is determined.

  • Subsequently, all bits of information are assigned to the corresponding phase of the CV. A school or university certificate is assigned to its belonging education phase, a reference to the respective career phase a.s.o. Step by step, each phase of the CV is enriched with all the information, for example learned skills and operation areas. A multiplicity of information which was previously only contained in attachments and would have been lost for further processing without using Merger.

  • Finally, all attachments, regardless of their original format, are classified and added to the underlying CV XML as schema validated XML together with a readable PDF and its plaintext e.g. for full text indexing. As the overall result, the entire application portfolio is returned as one easily processable standard XML document.

The complete applicant's profile, being enriched and extended by the help of the Merger module, is a significantly stronger base for decision-making to recruiters than only the conventionally parsed CV could ever be. With other words: When using CVlizer Merger, the applicant's profile becomes more than rich.

As a matter of course, a "full" candidate profile also has a strong positive impact on semantic matching quality, compared to conventionally parsed profiles...

Take a look at other modular components of our CV parser CVlizer.

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JoinVision is a premier supplier of multi-lingual, semantic recruiting technologies. CVlizer and JOBolizer automatically parse, analyze, and tag job postings and all documents used in job applications. MatchPoint provides a one-click solution for matching relevant job postings to the most suitable candidates and vice versa. In addition, HRexplorer offers online access to global job ads and candidate pools for additional variety and depth in recruiting.

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