A Case-based Reasoning System Based On Ontology For Knowledge Workers In Corporates

As the world moves towards a more technologically advanced means of recruitment,intelligent human resource management,social networking platforms such as electronic employment service technology application in post matching,these technologies along with theories such as data mining,machine learning knowledge ontology,and case-based reasoning,personalized recommendation and artificial intelligence such as cloud based computing and big data computing become increasingly embedded and widely used in the field of humanities,social science and development.Concurrently,the arrival of the era of knowledge economy,knowledge workers as the endogenous economic growth and promoting enterprise core competitiveness of main engine,in a contradictory and turbulent/changing environment,faced with a variety of professional challenges,the difficulty of career success is increasing.The knowledge workers need timely by means of a kind of artificial intelligence required in the employment market trends,and through the positive behavior change and the way of lifelong learning to constantly improve their own competence,keep you up with time can be hired through Labor market ability and the ability to better career life.In this background,how to build a model to implement intelligent person-post matching system,make vast amounts of knowledge workers need for their jobs to multiply semantic resource sharing and reuse,and accurately measure the similarity is the key to intelligent person-post matching.Ontology and case-based Reasoning(CBR)technology can solve this problem,the case-based Reasoning technology Based on Ontology can provide technological support for semantic matching.The previous traditional resume screening,online recruitment techniques,such as man of the match,case-based reasoning ontology technology can enhance person-post matching intelligent integration of knowledge,simplify and speed up the person-post matching process,to enable the organization(enterprise)to match specific job situations to employee attributes,characteristics and competencies more accurately and on this basis predict and match the best employee to a specific task,this will enable the organization to keep track of staff information and to keep the best data on staff.At the same time,it also enables knowledge workers to timely grasp the job competency requirements in the labor market,and continuously improve their own competency,and continue to be able to be employed in the job market,this research has important theoretical significance and application value.Based on ontology theory and case-based reasoning theory,this dissertation focuses on the practical problem of person-post matching for knowledge workers in enterprises,and studies the key problems in decision-making such as knowledge sharing,feature recognition,prediction and matching between person and posts.The main research contribution and achievements are summarized as follows:(1)Ontology construction of job competency characteristics of enterprise knowledge workers.For the characterstics of person-post matching knowledge as polyphyly,heterogeneous,uncertainty,and the semantic inconsistency,this research focus on the internet IT knowledge workers,using the Python web crawler tools and Jieba participle technology to collect and analyze the mass recruitment information of enterprise,set up post demand competence characteristics of knowledge ontology model,implements the employers need to post demand knowledge of unified structured expression competence characteristics,solved the position requirements competencies characteristics storage,organization and reuse of knowledge problem,it provides a semantic foundation for further research of ontology-based knowledge sharing,case representation,case retrieval and case-based reasoning.(2)Ontology-based person-post matching case representation of enterprise knowledge workers.Based on domain ontology building post competence characteristics,has been clear about the enterprise knowledge workers hillock matching case representation of the problem description,a description,solution three components,defines the post match case ontology knowledge model,and set up the person of the match case knowledge based on ontology,putted forward modeling system,realized the unification of person-post matching case structured specification,said as the case similarity calculation and accurate matching,and putted forward the effective application and maintenance.(3)Ontology-based similarity calculation and retrieval of enterprise knowledge workers person-post matching cases.According to person-post matching case,for a specific post problems and situation of the target case and putted forward the case of the source name and attribute similarity calculation based on the concept,and draw a specific problem and situation according to the results of the retrieval of post best match user portrait,as the target case evaluation criteria of candidate solutions and enterprise,the similarity calculation and retrieval quality determines the candidate of tacit knowledge is calculated and the case-based reasoning system precision and intelligence.(4)The calculation of job candidates' tacit knowledge based on case-based reasoning retrieval results and the knowledge sharing of talent community development.According to person-post matching the case-based reasoning retrieval results,through the social network,work logs,Bayesian network method,the candidate's personality preferences,work behavior,a particular task reflects the measurement and evaluation of tacit knowledge,and through the development of talent community knowledge sharing platform to optimize the structure of the user's network with professional communication,a hillock match better approach for knowledge sharing,better help knowledge workers continued by means of lifelong learning can be hired Labour market ability.(5)Design and implementation of ontology-based enterprise knowledge workers person-post matching case-based reasoning system.On the basis of the above research results,combined the case-based reasoning system and work mechanism,design and implementation of a complete enterprise knowledge workers of the matching case reasoning prototype system,were discussed in this dissertation,based on ontology matching of enterprise knowledge staff person,intelligent,dynamic,precise and perpetual research purposes,such as a post-match knowledge prediction,identification,matching the consultation and evaluation after matching with decision support services.