Libraries tagged by date_search

# Introduction **INDA (INtelligent Data Analysis)** is an [Intervieweb](https://www.intervieweb.it/hrm/) AI solution provided as a RESTful API. The INDA pricing model is *credits-based*, which means that a certain number of credits is associated to each API request. Hence, users have to purchase a certain amount of credits (established according to their needs) which will be reduced at each API call. INDA accepts and processes a user's request only if their credits quota is grater than - or, at least, equal to - the number of credits required by that request. To obtain further details on the pricing, please visit our [site](https://inda.ai) or contact us. INDA HR embraces a wide range of functionalities to manage the main elements of a recruitment process: + [**candidate**](https://api.inda.ai/hr/docs/v2/#tag/Resume-Management) (hereafter also referred to as **resume** or **applicant**), or rather a person looking for a job; + [**job advertisement**](https://api.inda.ai/hr/docs/v2/#tag/JobAd-Management) (hereafter also referred to as **job ad**), which is a document that collects all the main information and details about a job vacancy; + [**application**](https://api.inda.ai/hr/docs/v2/#tag/Application-Management), that binds candidates to job ads; it is generated whenever a candidate applies for a job. Each of them has a specific set of methods that grants users the ability to create, read, update and delete the relative documents, plus some special features based on AI approaches (such as *document parsing* or *semantic search*). They can be explored in their respective sections. Data about the listed document types can be enriched by connecting them to other INDA supported entities, such as [**companies**](https://api.inda.ai/hr/docs/v2/#tag/Company-Management) and [**universities**](https://api.inda.ai/hr/docs/v2/#tag/Universities), so that recruiters may get a better and more detailed idea on the candidates' experiences and acquired skills. All the functionalities mentioned above are meant to help recruiters during the talent acquisition process, by exploiting the power of AI systems. Among the advantages a recruiter has by using this kind of systems, tackling the bias problem is surely one of the most relevant. Bias in recruitment is a serious issue that affect both recruiters and candidates, since it may cause wrong hiring decisions. As we care a lot about this problem, we are constantly working on reduce the bias in original data so that INDA results may be as fair as possible. As of now, in order to tackle the bias issue, INDA automatically ignores specific fields (such as name, gender, age and nationality) during the initial processing of each candidate data. Furthermore, we decided to let users collect data of various types, including personal or sensitive details, but we do not allow their usage if it is different from statistical purposes; our aim is to discourage recruiters from focusing on candidates' personal information, and to put their attention on the candidate's skills and abilities. We want to help recruiters to prevent any kind of bias while searching for the most valuable candidates they really need. The following documentation is addressed both to developers, in order to provide all technical details for INDA integration, and to managers, to guide them in the exploration of the implementation possibilities. The host of the API is [https://api.inda.ai/hr/v2/](https://api.inda.ai/hr/v2/). We recommend to check the API version and build (displayed near the documentation title). You can contact us at [email protected] in case of problems, suggestions, or particular needs. The search panel on the left can be used to navigate through the documentation and provides an overview of the API structure. On the right, you can find (*i*) the url of the method, (*ii*) an example of request body (if present), and (*iii*) an example of response for each response code. Finally, in the central section of each API method, you can find (*i*) a general description of the purpose of the method, (*ii*) details on parameters and request body schema (if present), and (*iii*) details on response schema, error models, and error codes.

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It's a plugin allows to dress and search data on HTML page at realtime built using the library jquery

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Data indexing and for search engine

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Structured Data (schema.org) is a set of extensible schemas makes it easier for webmasters and developers to embed structured data on their web pages for use by search engines and other applications.

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A tool to allow BelongsTo searchable fields to be pre-populated with data

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A library to extract, serialize and store data scraped on Search Engine result pages.

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This library provides an API to perform binary search operations on a sorted index. The index can be a XML document, a CSV document, or an arbitrary text file where the key has a fixed position. You can easily implement your own index. This API comes handy on any sorted data structure where realtime search operations are necessary without the detour of a DBS import.

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the package is for filtering data for EXP you have search bar/page with multi filters option this package will help you to do that filters easily and fast this package using pipeline technology and it will check the request part by part

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Tree data structures for PHP – containing general tree, binary tree, and AVL tree

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Automatic url parameter mapping to sort, filter, include and select data in an easy to use fluent api within Laravel 5. The default parameter structure is compatible to the http://jsonapi.org specification.

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Easy access to array data using dot notation

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Introducing a powerful and flexible dynamic search, push notifications, file upload, alpha numeric generator functions for Laravel applications, designed to simplify complex queries with nested and recursive relationship conditions. This package provides an elegant solution to dynamically search across multiple models and their related data, offering developers the ability to handle various levels of relationships in a single, streamlined query.

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Bundle for creating data tables for symfony application.

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Define data by IP Address

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Library for implementing Ratsit API - Personal data search

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