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Submitted URL: https://jobiak.my/
Effective URL: https://jobiak.ai/
Submission: On November 11 via api from BE — Scanned from DE
Effective URL: https://jobiak.ai/
Submission: On November 11 via api from BE — Scanned from DE
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* About Us * Who We Help * Choose Your Business * Enterprises * Partnerships * Staffing Agencies * SMBs * Strategic Alliances * Careers * Blog * Contact Us * About Us * Who We Help * Choose Your Business * Enterprises * Partnerships * Staffing Agencies * SMBs * Strategic Alliances * Careers * Blog * Contact Us WE MAKE HIRING HAPPEN! Up To4xThe Applications Top 20Ranking AI-Powered SEO boosts every job into the top 20 rankings, dramatically increasing your job applicant volume, quality and relevancy UNLEASH THE POWER OF FOR JOBS The industry’s first and only AI platform designed to maximize your recruiting potential on Google for Jobs. Find The Right Candidates, For The Right Jobs-Faster! INCREDIBLE RECRUITMENT TECHNOLOGY. While our HR technology is sophisticated, our solution is simple. Jobiak enables employers and talent acquisition partners to easily publish and optimize job listings on Google for Jobs. Our state-of-the-art Machine Learning (ML) eliminates the technology challenges that previously limited access to this incredible new recruiting channel, empowering clients to achieve extraordinary results that no other recruitment technology can deliver. THE MAKING OF OUR MACHINE LEARNING Over 80,000 man-hours went into developing our patent-pending recruitment technology, which was built by exceptional engineers with deep expertise in the recruiting and Machine Learning industries. Our Artificial Intelligence (AI) model is constantly trained to generate high-performing keywords and make real-time SEO adjustments based on local market demand. TRAINING DATASET 400,000 man-hours of data collection were invested to create our AI-model, which has scoured million of job descriptions to ensure a high degree of accuracy 3.5 MILLIONJob Listings 600,000Job Titles 58,000Competencies (e.g., data analytics, UX design) MACHINE LEARNING EXPERTISE 50 Years of Machine Learning Expertise More than 20 specific machine-learning algorithms PATENT-PENDING TECHNOLOGY More than 100 Engineers involved in product dev Over 60 years of industry experience in recruiting and intellectual property (IP) development RELATIONAL MODEL 118 million occupational associations 600,000 nodes and 27 million edges between title and descriptions 127 million associations between titles and skills THE MOST POWERFUL PREDICTIVE TECHNOLOGY FOR JOB POST OPTIMIZATION Jobiak’s AI-platform accounts for over 25 “signals” that factor into Google for Jobs rankings and uses sophisticated modeling to implement the optimal code to achieve top search results for your job posts MACHINE LEARNING GOOGLE FOR JOBS RANKING FACTORS KEY SEO SIGNALS (Company name in domain, keyword presence, SEO meta tags) JOB PERSONALIZATION SIGNALS (High-ranking titles, title and job description associations) COMPANY REVIEWS SIGNALS (Number of reviews, ratings, similar jobs) ON-PAGE SIGNALS (Occupational category, company logo, salary estimates) REAL-TIME, MARKET-BASED SIGNALS (Most-searched queries by job-seekers, commonly used job-search keywords, frequency of re-posting) LOCATION SIGNALS (Location accuracy, nearby locations, population size, address and zip code) THE ANATOMY OF AN OPTIMIZED JOB POST Jobiak automatically optimizes your job posts for high ranking using machine-generated keywords, titles and descriptions, based on analysis of both real-time information and learnings from millions of monitored postings. Our AI-platform executes over 25 specialized SEO techniques both on the front-end of the post that job-seekers see on Google for Jobs, and in the background, to optimize the underlying code. FRONT-END OPTIMIZATIONS Url JOB TITLE COMPANY LOGO COMPANY NAME LOCATION DIRECT APPLY OCCUPATIONAL CATEGORY FREQUENT REPOSTING SKILLS & SPECIALTIES JOB DESCRIPTION SALARY ESTIMATES COMPANY REVIEWS BACK-END OPTIMIZATIONS SEO META TAGS ML GENERATED KEY WORDS REAL-TIME UPDATES NEARBY LOCATIONS OUR MACHINE LEARNING ENGINE JOBIAK SCANS YOUR JOBS AND IDENTIFIES THE 11 ATTRIBUTES THAT GOOGLE REQUIRES FOR GOOGLE FOR JOBS POSTS THE RECRUITMENT TECHNOLOGY USED TO PROCESS THESE 11 ATTRIBUTES: SKIP SKIP * Job Identifier * Company * Title * Location * Description * Salary * Job Type * Posting Date * Valid Through * Common * Optimization Job Identifier Identify distinct components of JOB IDENTIFIER (Ref Job, Job Id etc) Job IDs are hard to recognize since a job page is usually littered with various types of IDs that resemble a job ID. Jobiak’s learning algorithms can accurately separate and extract the correct job ID from the rest. Company HTML Structure Analysis Weighting Heuristics NLP Random Decision Forest N-Gram Model X-Paths Hiring company name can appear anywhere on a job description page. Sometimes part of a large blob of text, sometimes as a image logo on the page or simply implied by the URL. The presence of other company names (like the hosting job board) or company name like entities make it even more difficult to accurately identify the hiring company. Jobiak’s sophisticated natural language processing and modeling techniques are capable of automatically distinguishing the correct company name from others. This is aided by Jobiak’s proprietary visual/structural parsing technology as well as millions of carefully curated and labelled data. Title Patterns/Regular Expressions Remove Non-relevant sections(similar jobs, more jobs etc) HTML Structure Analysis Text Mining (Tf-Idf) Random Decision Forest NLP Weighting Heuristics Lookup table N-Gram Model Identify distinct components of Job titles(Ref Job, Job Id etc) Job titles are unstructured and can appear anywhere on a job description page often along with other entities like job location, requisition number etc. making it extremely difficult to automatically extract. Jobiak’s sophisticated natural language processing and modeling techniques utilize 100s of visual, structural and semantic features to recognize and extract job titles with a high degree of accuracy from any unstructured web page. This is aided by Jobiak’s proprietary visual/structural parsing technology as well as millions of carefully curated and labelled data items. Location Patterns/Regular Expressions Random Decision Forest Weighting Heuristics Identify Location Component(Cities, states, Regions, Countries) XPaths N-Gram Model Locations are unstructured, can appear anywhere on the page, often incomplete and along with other entities like job title or in the middle of a large description making it difficult to extract . Jobiak’s sophisticated natural language processing and modeling techniques are capable of automatically identifying job locations anywhere on the page with a high degree of accuracy as well as canonicalizing it based on contextual information. This is aided by Jobiak’s proprietary visual/structural parsing technology as well as millions of carefully curated and labelled data. Description Unsupervised Topic Model(Latent Dirichlet Allocation)/span> Sentence classification Model(Random Decision Forest) Decision Hints Job Description Detector(density based algorithm) Accurately identifying description is a hard task. Descriptions are made up of large portions of text, often with multiple sections. Accurately identifying text that is part of a job description and identifying the beginning and end of description sections becomes hard, even for human reviewers. Jobiak employs sophisticated machine learning techniques to identify various sections and topics that are part of the description and accurately classify sections that are part of the description. The technology also uses various algorithms to determine the boundaries of the description so as to accurately extract a description in it’s entirety, no more or no less than what is actually the description. Salary Weighting Heuristics N-Gram Model Xpaths Identify Salary Components(periodic, range, simple, descriptive etc) Jobiak’s algorithms can accurately identify salaries in job descriptions usually written in various formats (ranges), currencies and units (hourly, annually). Job Type Weighting Heuristics Identify distinct components of Job type(Full Time, Contractor, Part time etc) NLP N-Gram Model Xpaths Deep Neural Network Various job types associated with a job are identified whether it is explicitly present in the job page or inferred through context. Posting Date Identify distinct components of posting date(Posted Date, Posted since etc) N-Gram Model Xpaths Jobiak’s algorithms can accurately detect and distinguish between various kinds of dates like posted dates, validity dates, age etc Valid Through Identify distinct components of valid through date(Closes on, Valid through etc) N-Gram Model Xpaths Common SUPERVISED MODEL FOR CERTAIN TAGS N-Gram Model Xpaths Optimization Identify Location, JOB ID & SKILL ComponentS Supervised model for certain tags Power mean & graph embeddings 10 convolutional neural networks Jobiak’s optimization technology is built using sophisticated machine learning algorithms trained using millions of job postings and their online performance over a long period of time. Jobiak has built knowledge structures such as association graphs of titles, skills, descriptions using sophisticated text processing techniques. Convolutional models trained on this data accurately recommend proven job optimizations required to improve online visibility for job listings. Contact Us to Get Started 11 Boxwood Road Westford, MA 01886 JOBIAK * About Us * Blog * News DISCOVER * Strategic Alliances * Enterprises * SMBs HELP * Contact Us * FAQ LEGAL * Privacy Policy * Terms of Service * Cookie Policy © 2023. Jobiak. All Rights Reserved