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Résumé Parsing
Resume parsing, also known as CV parsing, resume extraction, or CV extraction, allows for the automated storage and analysis of resume data. The resume is imported into parsing software and the information is extracted so that it can be sorted and searched. Principle Resume parsers analyze a resume, extract the desired information, and insert the information into a database with a unique entry for each candidate.“What Is CV/Resume Parsing?” ''Daxtra'', Daxtra Technologies Ltd, 18 Oct. 2016, https://info.daxtra.com/blog/2016/10/18/what-is-cvresume-parsing. Once the resume has been analyzed, a recruiter can search the database for keywords and phrases and get a list of relevant candidates. Many parsers support semantic search, which adds context to the search terms and tries to understand intent in order to make the results more reliable and comprehensive. Machine learning Machine learning is extremely important for resume parsing. Each block of information needs to be give ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Résumé
A résumé, sometimes spelled resume (or alternatively resumé), also called a curriculum vitae (CV), is a document created and used by a person to present their background, skills, and accomplishments. Résumés can be used for a variety of reasons, but most often they are used to secure new employment. A typical résumé contains a "summary" of relevant job experience and education. The résumé is usually one of the first items, along with a cover letter and sometimes an application for employment, which a potential employer sees regarding the job seeker and is typically used to screen applicants, often followed by an interview. The curriculum vitae used for employment purposes in the UK (and in other European countries) is more akin to the résumé—a shorter, summary version of one's education and experience—than to the longer and more detailed CV that is expected in U.S. academic circles. In South Asian countries such as India, Pakistan, and Bangladesh, biodata is of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Named-entity Recognition
Named-entity recognition (NER) (also known as (named) entity identification, entity chunking, and entity extraction) is a subtask of information extraction that seeks to locate and classify named entities mentioned in unstructured text into pre-defined categories such as person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages, etc. Most research on NER/NEE systems has been structured as taking an unannotated block of text, such as this one: And producing an annotated block of text that highlights the names of entities: In this example, a person name consisting of one token, a two-token company name and a temporal expression have been detected and classified. State-of-the-art NER systems for English produce near-human performance. For example, the best system entering MUC-7 scored 93.39% of F-measure while human annotators scored 97.60% and 96.95%. Named-entity recognition platforms Notable NER platforms include: ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
GitHub
GitHub, Inc. () is an Internet hosting service for software development and version control using Git. It provides the distributed version control of Git plus access control, bug tracking, software feature requests, task management, continuous integration, and wikis for every project. Headquartered in California, it has been a subsidiary of Microsoft since 2018. It is commonly used to host open source software development projects. As of June 2022, GitHub reported having over 83 million developers and more than 200 million repositories, including at least 28 million public repositories. It is the largest source code host . History GitHub.com Development of the GitHub.com platform began on October 19, 2007. The site was launched in April 2008 by Tom Preston-Werner, Chris Wanstrath, P. J. Hyett and Scott Chacon after it had been made available for a few months prior as a beta release. GitHub has an annual keynote called GitHub Universe. Org ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Job Hunt
Job hunting, job seeking, or job searching is the act of looking for employment, due to unemployment, underemployment, discontent with a current position, or a desire for a better position. The immediate goal of job seeking is usually to obtain a job interview with an employer which may lead to getting hired. The job hunter or seeker typically first looks for job vacancies or employment opportunities. Steps Locating jobs Common methods of job hunting are: * Finding a job through a friend or an extended business network, personal network, or social media * Using an employment website * Job listing search engines * Looking through the classifieds in newspapers * Using a private or public employment agency or recruiter * Looking on a company's web site for open jobs, typically in its applicant tracking system * Going to a job fair * Using professional guidance such as outplacement services that give training in writing a résumé, applying for jobs and how to be successful a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Text Mining
Text mining, also referred to as ''text data mining'', similar to text analytics, is the process of deriving high-quality information from text. It involves "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources." Written resources may include websites, books, emails, reviews, and articles. High-quality information is typically obtained by devising patterns and trends by means such as statistical pattern learning. According to Hotho et al. (2005) we can distinguish between three different perspectives of text mining: information extraction, data mining, and a KDD (Knowledge Discovery in Databases) process. Text mining usually involves the process of structuring the input text (usually parsing, along with the addition of some derived linguistic features and the removal of others, and subsequent insertion into a database), deriving patterns within the structured data, and finally evaluation and int ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Applicant Tracking System
An applicant tracking system (ATS) is a software application that enables the electronic handling of recruitment and hiring needs. An ATS can be implemented or accessed online at enterprise- or small-business levels, depending on the needs of the organization; free and open-source ATS software is also available. An ATS is very similar to customer relationship management (CRM) systems, but are designed for recruitment tracking purposes. In many cases they filter applications automatically based on given criteria such as keywords, skills, former employers, years of experience and schools attended. This has caused many to adapt resume optimization techniques similar to those used in search engine optimization when creating and formatting their résumé. Principle A dedicated ATS is not uncommon for recruitment-specific needs. On the enterprise level it may be offered as a module or functional addition to a human resources suite or human resource information system (HRIS). The ATS is ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Microsoft Word
Microsoft Word is a word processing software developed by Microsoft. It was first released on October 25, 1983, under the name ''Multi-Tool Word'' for Xenix systems. Subsequent versions were later written for several other platforms including: IBM PCs running DOS (1983), Apple Macintosh running the Classic Mac OS (1985), AT&T UNIX PC (1985), Atari ST (1988), OS/2 (1989), Microsoft Windows (1989), SCO Unix (1990) and macOS (2001). Using Wine, versions of Microsoft Word before 2013 can be run on Linux. Commercial versions of Word are licensed as a standalone product or as a component of Microsoft Office suite of software, which can be purchased either with a perpetual license or as part of a Microsoft 365 subscription. History Origins In 1981, Microsoft hired Charles Simonyi, the primary developer of Bravo, the first GUI word processor, which was developed at Xerox PARC. Simonyi started work on a word processor called ''Multi-Tool Word'' and soon hired Rich ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Docx
Office Open XML (also informally known as OOXML) is a zipped, XML-based file format developed by Microsoft for representing spreadsheets, charts, presentations and word processing documents. Ecma International standardized the initial version as ECMA-376. ISO and IEC standardized later versions as ISO/IEC 29500. Microsoft Office 2010 provides read support for ECMA-376, full support for ISO/IEC 29500 Transitional, and read support for ISO/IEC 29500 Strict. Microsoft Office 2013 and later fully support ISO/IEC 29500 Strict, but don't use it as the default file format because of backwards compatibility concerns. Background In 2000, Microsoft released an initial version of an XML-based format for Microsoft Excel, which was incorporated in Office XP. In 2002, a new file format for Microsoft Word followed. The Excel and Word formats—known as the Microsoft Office XML formats—were later incorporated into the 2003 release of Microsoft Office. Microsoft announced in November 2005 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistical Analysis
Statistical inference is the process of using data analysis to infer properties of an underlying distribution of probability.Upton, G., Cook, I. (2008) ''Oxford Dictionary of Statistics'', OUP. . Inferential statistical analysis infers properties of a population, for example by testing hypotheses and deriving estimates. It is assumed that the observed data set is sampled from a larger population. Inferential statistics can be contrasted with descriptive statistics. Descriptive statistics is solely concerned with properties of the observed data, and it does not rest on the assumption that the data come from a larger population. In machine learning, the term ''inference'' is sometimes used instead to mean "make a prediction, by evaluating an already trained model"; in this context inferring properties of the model is referred to as ''training'' or ''learning'' (rather than ''inference''), and using a model for prediction is referred to as ''inference'' (instead of ''prediction'' ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Regular Expressions
A regular expression (shortened as regex or regexp; sometimes referred to as rational expression) is a sequence of characters that specifies a search pattern in text. Usually such patterns are used by string-searching algorithms for "find" or "find and replace" operations on strings, or for input validation. Regular expression techniques are developed in theoretical computer science and formal language theory. The concept of regular expressions began in the 1950s, when the American mathematician Stephen Cole Kleene formalized the concept of a regular language. They came into common use with Unix text-processing utilities. Different syntaxes for writing regular expressions have existed since the 1980s, one being the POSIX standard and another, widely used, being the Perl syntax. Regular expressions are used in search engines, in search and replace dialogs of word processors and text editors, in text processing utilities such as sed and AWK, and in lexical analysis. Most ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Stemming
In linguistic morphology and information retrieval, stemming is the process of reducing inflected (or sometimes derived) words to their word stem, base or root form—generally a written word form. The stem need not be identical to the morphological root of the word; it is usually sufficient that related words map to the same stem, even if this stem is not in itself a valid root. Algorithms for stemming have been studied in computer science since the 1960s. Many search engines treat words with the same stem as synonyms as a kind of query expansion, a process called conflation. A computer program or subroutine that stems word may be called a ''stemming program'', ''stemming algorithm'', or ''stemmer''. Examples A stemmer for English operating on the stem ''cat'' should identify such strings as ''cats'', ''catlike'', and ''catty''. A stemming algorithm might also reduce the words ''fishing'', ''fished'', and ''fisher'' to the stem ''fish''. The stem need not be a word, for ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Parsing
Parsing, syntax analysis, or syntactic analysis is the process of analyzing a string of symbols, either in natural language, computer languages or data structures, conforming to the rules of a formal grammar. The term ''parsing'' comes from Latin ''pars'' (''orationis''), meaning part (of speech). The term has slightly different meanings in different branches of linguistics and computer science. Traditional sentence parsing is often performed as a method of understanding the exact meaning of a sentence or word, sometimes with the aid of devices such as sentence diagrams. It usually emphasizes the importance of grammatical divisions such as subject and predicate. Within computational linguistics the term is used to refer to the formal analysis by a computer of a sentence or other string of words into its constituents, resulting in a parse tree showing their syntactic relation to each other, which may also contain semantic and other information ( p-values). Some parsing algo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
