The Importance of High-Quality Russian Language Services

"High-level opening up"and"high-quality development"are important development goals and directions of China during the 14th Five-Year Plan period.Heilongjiang,as the largest and oldest province open to Russia,has a long history of communication and plays a vanguard role.However,the province's geographical advantages are weakening under the impact of the COVID-19 pandemic and the rapid development of the internet industry.Facing the new era,maintaining and enhancing the regional advantages of the province has become an urgent issue that requires attention.This study takes the Russian language service in Heilongjiang Province as the subject,combines theory with practice through theoretical elaboration and historical analysis,as well as tries to provide reference for improving the language service system in Heilongjiang Province and enhancing its regional advantages.This study believes that a high-quality language service plays an important role in solving the issue.It is necessary to fully understand and apply the essential power of language,be more aware of the importance of Russian language services,build a sound ecosystem of language services,give full play to the traditional advantages of the"Russian"in this province,and finally assume "Russian language services"as the"golden banner"for the development of language services,economy,and culture in the province.

AN IMPROVED HYBRID SEMANTIC MATCHING ALGORITHM WITH LEXICAL SIMILARITY

In this paper, we proposed an improved hybrid semantic matching algorithm combining Input/Output (I/O) semantic matching with text lexical similarity to overcome the disadvantage that the existing semantic matching algorithms were unable to distinguish those services with the same I/O by only performing I/O based service signature matching in semantic web service discovery techniques. The improved algorithm consists of two steps, the first is logic based I/O concept ontology matching, through which the candidate service set is obtained and the second is the service name matching with lexical similarity against the candidate service set, through which the final precise matching result is concluded. Using Ontology Web Language for Services (OWL-S) test collection, we tested our hybrid algorithm and compared it with OWL-S Matchmaker-X (OWLS-MX), the experimental results have shown that the proposed algorithm could pick out the most suitable advertised service corresponding to user's request from very similar ones and provide better matching precision and efficiency than OWLS-MX.