Keyword searches are commonplace in databases, search engines and social media. But often, users are frustrated because the words searched show up many irrelevant results. These results are often not what the users might be looking for. They are often not worthwhile or helpful, rather just pages and pages of irrelevant data.
We are living in the era of data boom. However, technologies are yet to match the existing pace of data being generated world over – in servers, clouds, social media, transactions … et all. Technologies are yet to be able to unearth information from all the unexplored data out there. Why does much of this data remain unexplored? The reason for this is the format in which it exists. Data in the digital age is mostly unstructured i.e., in the form of alphabets and random words that computers cannot comprehend adequately vis-à-vis quantifiable numeric types of data.
We have software which easily compute and process numbers but not textual data. Even if so, with limitations. Technologies have to evolve to incorporate the intricacies of human language communication and all its nuances and reflect the same when processing random textual data.
Spire is a pioneer of contextual intelligence technology which works around two core strengths. It can comprehend and interpret any type of data – structured or unstructured. Additionally, it uses the power of 'contextualizing' to analyze the data. The core platform is so powerful that it gives 95% accuracy in contextual search and 80% accuracy in contextual matching of search results to search terms. These accuracy levels are the maximum levels ever made possible in machine computing till date.
For instance, this technology has been instantiated in the HR domain which is characterized by the maximum amount of unstructured data - resumes, job descriptions, applications, social data, appraisals, skills profiles, achievements, academic details and references. Only contextual technology can comprehend these massive amounts of HR data with intelligence that is human-like.
Acqura™ is a talent hiring tool. Using smart algorithms, Acqura finds only specific skills mentioned in the resumes of candidates, scoring them against job descriptions. These weighted matches form the Profile Richness Index score. With Richness Index, Acqura scans resumes, cover letters and profiles for the 'context' that matches a job description far better than using simple keyword search. The contextual search function can search for more than 1,300 parameters in mere seconds and return only relevant results with a 95% accuracy rate. Acqura can scan thousands of resumes in a few hours.
The social sourcing tool - TalentVista™ uses the Richness Index feature to find potential active and passive job seekers from the entire internet. Candidates are located and shortlisted based on their skills and personality dispositions. TalentVista allows recruiters to then engage with potential candidates using an interactive interface. The Engagement Index score measures the engagement levels and professional relationship scores that recruiters develop with the candidates. It reflects how probably a particular candidate is likely to become an applicant. All this information gives never-before-seen analytics and insights to recruiters.
With Spire's Richness Index, recruiters and hiring managers can harness the power of contextual search, delivering only relevant candidates in less time and saving costs.