Battlefield: with the development of enterprise information management, using information technology to improve the efficiency of enterprise management has become the consensus of contemporary enterprises.
#HUMAN RESOURCE MACHINE ENDING HOW TO#
How to make efficient and full use of massive information has become the main focus of human resources for each company's department. HR is faced with a large amount of unstructured data every day, such as various resumes, recruitment requirements of employers, and interview feedback reports. In the human resources industry, with the development of online recruitment, hundreds of millions of resumes and tens of millions of enterprise recruitment information have been accumulated through online recruitment channels.
The first step of person post matching is to start from personnel recruitment. However, it is difficult to do a good job in human resources, and various management problems also occur from time to time, resulting in the dislocation between people and posts, resulting in a great waste of human capital. Otherwise, it will only lead to increased internal friction, increased management costs, and brain drain. The maximum benefit of human capital can only depend on effective human resource management. To truly form capital, the human resources of enterprises must be effectively allocated and reasonably used. The core competitiveness of an enterprise depends not only on sufficient capital and advanced technology but also on the human capital it has. The development of the market has accelerated the competition among enterprises. The system can better overcome the cold start problem and provide real-time recommendation results, improving the quality of HR personalized recommendation results. Based on the main workflow of the recommender system, this paper designs the overall architecture of the human resources recommendation system and implements a human resources recommendation prototype system based on deep learning. Faced with this problem, people propose recommender systems to solve the problem of obtaining preference information, which can better increase the user's experience and meet their own needs more easily. However, in many cases, most users cannot clearly recognize the content they need or how to accurately express their needs. As long as the search engine is clear about the direction of the search, it is indeed very convenient for the retrieval of massive data. After that, experts developed search engines to deal with the retrieval problem, and the first ones were Google and Baidu. Especially with the gradual increase of the amount of information, this method is not enough for the acquisition and classification of massive data.
For each puzzle, the player is told of a specific task, such as adding two numbers as they come in on the inbox, or sorting a zero-terminated string of characters, delivering these results in the proper order to the outbox.With the advent of the Internet era, the frequency and proportion of candidates obtaining recruitment information through the Internet is getting higher and higher, and the amount of human resource information, such as talent information and job information, has also increased unprecedentedly, which makes human resource services face information overload. The office floor typically also includes a number of marked number spaces that can hold one box each. In each puzzle, the player creates a list of instructions from rudimentary commands to control the movements of their avatar on an overhead view of an office the office includes two conveyor belts, one an inbox that sends in either an integer or a single alphabetic character represented as a small box, the other an outbox to receive these. The game includes approximately 40 programming puzzles, each considered one "year" of the player's avatar tenure in a corporate structure. The player works through several puzzles in constructing a program to complete a specific task. Human Resource Machine uses the concept of a corporate office worker assigned to perform tasks that involve moving objects between an inbox, an outbox, and to and from storage areas as a metaphor for assembly language concepts.
#HUMAN RESOURCE MACHINE ENDING FOR ANDROID#
The game was released for Microsoft Windows, OS X and Wii U in October 2015, being additionally released for Linux on March 29, 2016, for iOS on June 1, 2016, and for Android on December 1, 2016. Human Resource Machine is a visual programming-based puzzle game developed by Tomorrow Corporation.
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