[Purpose/significance] In the new research environment, research achievements are available on diverse formats and show different impacts. This paper compares impact of books and papers in artificial intelligence from various angles, and provides reference for comprehensive academic evaluation in the new environment. [Method/process] The paper combines bibliometrics and Altmetrics, and selects academic pa-pers and books in artificial intelligence, then compares them from aspects of country/author/age distribution, impact indicators, and subject content. [Result/Conclusion] In the field of artificial intelligence, for the number of published papers and books, the distributions of countries are relatively similar; the high-yield authors of both formats overlap little. In general, whether citation or altmetric indicators, the values of these indicators in papers are higher than those in books. In the aspect of subject, In the aspect of subject, topic words of papers are more novel and specific, reflecting the current research hotspots; but those of books are more general and explore the hotspots in the ascending stage. Both are important to analyse development stage of the field. [Limitations] This paper only focused on the field of artificial intelligence. In the future, we can expand the scope of research, obtain more data, combine more altmetric indicators to evaluate the impact of academic achievements more comprehensively.

The evaluation of the social influence of scientific research output is an important topic concerned by the government and the fund. Altmetrics has long been recognized as having the potential to measure social impact, but its application in the field of scientific output social impact assessment is still in the theoretical and empirical exploration stage. Firstly, this paper explains the concept and connotation of social impact assessment of scientific research output, common methods and typical international social impact assessment projects. Secondly, the research status of Altmetrics in evaluating the social impact of scientific research output is summarized. Finally, the future challenges of Altmetrics in the application of social impact assessment are pointed out from four aspects: the development of Altmetrics platform and indicators based on domestic data sources, the construction of the data tracking and collection framework for localizing Altmetrics, the normalization of Altmetrics and the multi-dimensional subdivision of social impact.

The study, based on analysis of user cases of Altmetric.com company, has summarized the successful experience of application of altmetrics data by various stakeholders including research institutions, publishers, libraries, funders and enterprises. Three major ways of using altmetrics data are identified, i.e. Facilitate promotion, support claim of impact and benefit scientific collaboration. As regards facilitating promotion, altmetrics data can be used to improve user experience, broaden the audiences and satisfy readers' interest. In terms of demonstrating the impact value, alternative measurement data can expand the scope of influence, improve the timeliness of impact, provide feedback on funding efficiency, and be used for scientific and technological assessment. These successful use methods can provide reference for the rational use of alternative measurement data by domestic research institutions and funding agencies.

This paper collects the index data of Top100 hot papers in 2017 from Altmetric.com platform. First of all, it analyzes the hot papers statistically, then combines the citation index data in Web of Science, through the coverage and correlation index screening, using the principal component analysis method to construct the paper influence model. The research results show that: (1) High-producing countrie is the United States; research institutes are mostly universities; the overall frequency of authors varies widely, and the directions of research are mostly in medicine, science and technology, and biology. (2) Twitter,Facebook, Blog, Mendeley, News and Wikipedia are the main indicators that make up the annual Altmetrics hot papers; It is more reasonable to introduce comprehensive evaluation of hot papers after citations; Chinese scholars and research institutes should also pay attention to their social influence while improving the academic influence of high-quality dissertations.

[Purpose] In order to scientifically evaluate the social influence of academic papers and comprehensively evaluate the influence of academic papers, this paper explores the Altmetrics indicator evaluation system under Chinese environment. [Method] This paper takes the literature in the field of Library information and digital library as the research object, uses Python language to compile Internet worm program, traces the origin of relevant literature in social network platform, obtains relevant data and carries out indicator research.[Result/conclusion] This paper analyses and explores the data sources and specific indicators of Altmetrics, and preliminarily constructs an indicator evaluation system of Altmetrics in the field of library information and digital library under the Chinese environment. However, due to the subject limitations, the applicability of the indicator evaluation system to other academic fields still needs further research to verify and compare.

This paper investigated research assessment of UK, reviewed the development of the British research assessment profile, including Research Selectivity Exercise, Research Assessment Exercise and Research Excellence Frame, analyzed the evolution process of the British research assessment in four aspects, namely, units, methodology, submissions, elements, results and effect of Assessment. On the basis of these works, this paper studied the evolution trend of the British research assessment from the perspectives of the process, methodology, elements and results of assessment, proposed enlightenment and recommendations for the construction of research assessment system in China.

[Purpose/Significance]Aimed at the user cold start problem that prevent the university smart library from accurately recommending books to new readers, a personalized recommendation method for new college readers is proposed to provide practical solutions for carrying out personalized recommendation service and increasing new readers' borrowing rate.[Method/Process]Through data mining on borrowing circulating big data in Beihua university library, the conclusion is reached that new readers and existing readers with similar attributes have similar borrowing and reading preferences;Then, the singular value decomposition is used to solve the data sparse problem and the Euclidean distance and ant colony algorithm are used to cluster the new readers and existing readers, which building a bridge between new readers and existing readers. Finally, the Top-N algorithm is adopted to recommend the books borrowed by existing readers to new readers. [Result/Conclusion]Take the readers from grade 2017 as experiment subject, the proposed algorithm was tested on 44 readers from three academies. The results show that the proposed algorithm is effective and easy to operate, which lays a foundation for the subsequent personalized recommendation work.

[Purpose/Significance] The establishment of government data openness mechanism can promote knowledge sharing in national economy, information technology and other fields, and provide theoretical reference and practical guidance for the government to open the public. [Method/Process] This paper builds a logical framework of government data openness mechanism based on three dimensions of government data content, object of government data utilization and government data open format, and uses the framework as a theory to guide the practice of opening government data, so as to improve the strategy and action of government data openness. [Results/Conclusion] As a part of the process of exploring open government, it is necessary to interact with practice to construct open government data system. According to feedback, we can improve the theory, measure performance and accept public evaluation, and improve the government data classification system.

By analyzing the main service modes of university mobile libraries and the user behavior of university mobile libraries under the social network environment, this paper further develops and perfects the theoretical research on the user information behavior of university mobile libraries based on social network. When analyzing the information behavior of users in mobile libraries in colleges and universities, based on the self-efficacy theory and user portrait theory, this paper reveals the different behavior needs of users, uses concept lattice method and superstar mobile libraries as data sources to analyze users' behavior, so as to consider users' basic attributes and users'needs and preferences in many ways, and move for colleges and universities. The study of information behavior of mobile library users provides a reference for the improvement of information service of mobile library, which has important theoretical significance and practical value.

As the coming of the big data era, the digital resources growth dramatic Traditional storage has many problems, such as hard to expand, low security and so on,the cloud storage has the characteristics of easy to expand, low cost and high security which can solve the massive storage problem. Taking the National Museum Library as an example, this paper combs and reviews the general situation of data and the present situation of storage, analyzes the problem of the traditional storage, proposes the necessity of cloud storage. This paper constructs a digital resource preservation system based on cloud storage technology and puts forward solutions and corresponding construction strategies for such library cloud storage, in order to provide some reference for library to use cloud storage.