[Purpose/Significance] The emergency management during emergency incidents is one of the focuses of governments.In a big data environment,how to enable the power of crowds to participate in emergency rescue activities is a research hotspot in the domain of emergency management.[Methods/Processes] Based on literature study,this paper introduced a crowdsourcing model for emergency management and provided in-depth analysis on this model.[Results/Conclusion] It proposed an emergency management model integrated with crowdsourcing for all the phases in emergency management,and constructed a crowdsourcing-based emergency management intelligence system.In addition,it elaborated on the factors that affected the quality of crowdsourcing in emergency management.This study complemented the state-of-the-art research on emergency management.

[Purpose/Significance] Safety & security-related intelligence(SI) plays a key role in safety & security management(SM).And the safety & security-related intelligence system(SIS) is the organizational guarantee and physical infrastructure for the SI work.Therefore,it is of great theoretical and practical importance to study SIS.[Method/Process] At first,according to the general characteristics and functions of intelligence system,and the characteristics of SM,this article analyzed the connotation of SIS,and proposed the definition of SIS.Then,based on the definition and connotation of SIS,this paper constructed and analyzed the overview model of SIS on the theoretical level.Finally,this article constructed and analyzed the sub-models of the SI process implementation system on the theoretical level.[Result/conclusion] The results showed that SIS was a new type of SM system and intelligence system through the organic combination of SM system and intelligence system,and its basic framework could be summed up as "one organization,one intelligence source,two institutions,two big systems and three networks".

[Purpose/Significance] In the context of big data's drive,technological standardization knowledge management is facing new opportunities and challenges.In the areas of public,economic and social diversity,with the help of big data technology,the role of the main alliances of government,enterprises and the public in the management of technical standardization knowledge is fully utilized.This is of great significance in promoting the rational allocation of knowledge resources,pushing forward the evolution of technological standardization,and enhancing the knowledge management capabilities.[Method/Process] Based on the theory of life cycle and synergetic theory,this paper analyzed the influence of big data driving on technology standardization and knowledge management,and established the eelationship model of knowledge management in technical standardization.Besides,it discussed the mechanism of knowledge management and technology standardization driven by big data from the basic layer,flow layer and driving layer.[Result/conclusion] The alliance of knowledge management subject was established by government,enterprise and public level,which provided safeguard measures for big data driven technology standardization knowledge management.

[Purpose/Significance] Several national projects have carried out a series of in-depth study on knowledge fusion.Based on the published papers of these projects,we can systematically sum up the progress of knowledge fusion,which not only can reveal the research characteristics of those important domestic research teams,but also can help summarizing the commonness of knowledge fusion studies.[Method/Process] This paper analyzed papers of national projects related to knowledge fusion in library and information science(LIS) since 2011,based on which we summarized the characteristics of 9 national projects on the perspective of conceptual relations(including domain ontology), linked data,folksonomy,users,social network analysis and bibliometrics.[Result/conclusion] The resources,methods and knowledge association of knowledge fusion have developed to multiple-dimension,and the semantic relations to field-divided and fine-grained.

[Purpose/Significance] On the basis of the self-organizing operation of the social tagging system,the multi-dimensional fusion and optimization model of personalized information recommendation was constructed to provide accurate personalized information recommendation service for users under the big data environment,thus further enriching the theoretical system of personalized information recommendation and expanding the research methods of personalized information recommendation.[Method/Process] Firstly,the advantages and disadvantages of each personalized information recommendation method were analyzed in depth.Then,three personalized information recommendation methods based on graph theory(social network relationship),collaborative filtering and content-based(topic-based) were fused in depth to construct a personalized information recommendation multi-dimensional fusion model.Finally,the multi-dimensional fusion model of personalized information recommendation in social annotation system was optimized to solve the problems of cold start,data sparsity and users' preference drift in personalized recommendation process.[Result/conclusion] By considering the respective contributions and shortcomings of graph theory(social network relationship),collaborative filtering and content-based(topic-based) personalized information recommendation methods,the multi-dimensional and deep fusion among the three methods was realized.Finally,a multi-dimensional fusion and optimization model of personalized information recommendation in social annotation system was constructed by combining psychological cognition,user context,time and space.

With the popularity of self-media such as Logic Show and Dedao,social learning as a new model is emerging.How to attract and facilitate users' continuous participation and their retention is critical for enterprises to achieve competitive advantage.Based on the social capital theory,this paper examined the determinants of social learning users' continuous participation behavior.Structural equation model was used to analyze 402 valid questionnaires.The results showed that social interaction ties,shared language and shared vision significantly influence sense of virtual community,which in turn affected continuous participation behavior.Therefore,communities needed to promote users' social interaction and improve the professionalism of content in order to enhance the sense of community and promote the sustainable development of the community.

[Purpose/Significance] This study aimed to explore the impact of different task situations on users' mobile medical information search behavior,and provide improved methods and strategies for product and service innovation of mobile medical information based on comparative analysis.[Method/Process] Factual task,explanatory task and exploratory task were selected as three most representative task situations."situation experiment+questionnaire interview" was adopted to obtain behavioral characteristics data of the research samples and the experimental process was recorded through the screen recording software.The collected questionnaire text and video data were processed through manual coding,data cleaning and data preprocessing,and 36 valid samples and 108 valid data were obtained and Mann-Whitney nonparametric test was performed using SPSS22.0.[Result/conclusion] Different task situations had a significant effect on search process variables.Compared with factual tasks,explanatory tasks and exploratory tasks not only significantly increased the number of query string modifications,the number of visited pages and the number of click links,but also tended to use more search channels in search strategies;Task type had significant influence on perceived task difficulty before and after experiment,perceived task completion degree and objective task completion degree.Among them the factual task was the least difficult and the objective completion degree was the highest.However,task type had no significant effect on task cognition and perceived usefulness of multichannel search.

[Objective/Significance] In view of the online user review habits in China,exploring the factors affecting the user comment behavior on the comment time,it has important potential commercial value for e-commerce operators to explore the behavior of user comments and explore the potential user comment time preference.[Methods/Process] Based on the TAM model,the influencing factors of the online user comment behavior time characteristic law were extracted and the model was constructed.The time interval was extracted by extracting the time interval between the consumer purchase behavior and the comment behavior,and the hypothesis verification was performed by the multiple linear regression model.[Result/conclusion] Through the example verification of the online comment data,the model constructed in this paper could well discover the influence of online user comments on the comment time,and have a supporting effect on the time feature law discovery and prediction of consumer comment behavior.

[Purpose/Significance] This paper discussed the factors that affected the continuous usage intention of dominant and browsing users of mobile social networks,provided a theoretical basis for mobile social network information services and reference for mobile social network providers.[Method/Process] This paper analyzed the influencing factors of the continuous usage intention of the dominant and browsing users in mobile social networks,introduced relevant variables,built the continuous usage intention model of mobile social network information service based on user behavior perception and put forward the hypothesis,and finally used the structural equation model to conduct empirical analysis.[Results/Conclusions] The results showed that perceived usefulness,perceived ease of use,perceived entertainment,perceived quality and other factors had a significant impact on dominant and browsing users of mobile social networks;quality of service,perceived risk,knowledge acquisition,personal innovation,social recognition,perceived trust,perceived transformation Costs and other factors had different degrees of impact on two types of users.

[Purpose/Significance] Wechat has become the main channel for daily information acquisition,sharing,entertainment and social intercourse.Many individual and enterprises start to perform customer service marketing,brand building and maintenance,product promotion etc via Wechat official account.Meanwhile,user interaction behavior with Wechat official account shows diversely affected by information quality.[Method/Process] Based on literature research of user behavior study,Wechat official account and information quality,this paper established Wechat official account information quality evaluation index and probed into the influence mechanism of Wechat official account information quality on user behavior through qualitative and quantitative analysis.[Result/conclusion] As for the influence of information quality on user behavior,the hypothesis was based on the analysis of Wechat official account user behavior data.First of all,data was standardized to get index of interaction,then hypothesis was testified.We could find that the indicator of authority,originality,effectiveness,interesting,efficiency etc have a significant positive impact on user interaction behavior.[Revelation/Discovery] This paper brought the analysis of user behavior data in the background of Wechat official account into the research scope,explored the differences and reasons of information quality behind behavior,provided a new research perspective for the research of social media information quality and user behavior,and studied the strategies and methods to improve the information quality of Wechat official account,which were available to all stakeholders.

[Purpose/Significance] In the new era of micro-government,good reputation is a unique resource for the government service,It is also an important driving force to urge the government to improve the quality of government information service.[Method/Process] Based on the reputation theory,this paper constructs the optimal dynamic incentive mechanism of the superior and subordinate governments,which is made up of the explicit incentive and the implicit incentive.And this paper take the "micro-government" as an example,to explore the role of reputation effects in government information service quality optimization.[Result/conclusion] The research found that the reputation has a positive effect on the behavior of the governments through the internal effect and the external effect.Compared with the single explicit incentive mechanism,the dynamic incentive mechanism that considers the theory of reputation can effectively reduce the incentive pressure of the superior governments,and promote the efforts of the subordinate governments.

[Purpose/Significance] The quality of open government data(OGD) is an important factor that affects people's access to data.It is significant to study the OGD quality control mechanism,which is helpful to optimize the quality of OGD the government,promote wider public participation.and achieve the goals of OGD.[Methods/Procedures] In this paper,evolutionary game theory was used to construct a copy dynamic model of boundedly rational open government data providers and users,to analyze the evolutionary stability strategies of both sides of the game and equilibrium conditions of the OGD quality under different data quality supervision conditions.[Results/Conclusion] It was found that regulatory incentives above a certain threshold could effectively control the OGD quality.In addition,it established scientific data quality assessment standards and data quality filtering mechanisms,reduced the additional cost of providing quality data and enhanced the data release mechanism which would improve data quality control efficiency.

Maturity model is an important aspect of measuring government open data.This paper expounded the meaning and the importance of model building of open government data maturity,and reviewed on the types of government open data maturity models of foreign governments.From the perspective of government itself,the paper constructed the model of Chinese government open data maturity model,analyzed the immaturity status and put forward some suggestions to improve the maturity capacity of government open data in China.

[Purpose/Significance] Patent is an important achievement of technical innovation activities in enterprises,which being analyzed is conducive to evaluating the technological innovation ability of enterprise objectively.[Method/Process] Analyzed the enterprise patent data from the perspective of measurement,combined the methods of machine learning to carry out content mining of patent summary text through LDA model to construct evaluation indicators based on patent text content,and established a technical innovation evaluation system based on the number of patents,patent trends and patent content.[Result/conclusion] Entropy method was used to determine the indicators weight influence on domestic manufacturing enterprises.It was proved that practical significance of the evaluation method was to evaluate the capability of the domestic manufacturing enterprise by experiment.

[Purpose/Significance] The technology-based SMEs are the important forces of the science and technology innovation,but they are faced with many problems in the process of the science and technology innovation.Competitive intelligence is an important way for technology-based SMEs to successfully carry out scientific and technological innovation activities.[Method/Process] From the angle of competitive intelligence,the connotation of scientific and technological innovation of technology-based SMEs is defined,and the role of competitive intelligence in scientific and technological innovation of enterprises was put forward.Construction of Science and Technology Innovation process Chart for technology-based SMEs with competitive Intelligence process and Analysis of the role of competitive Intelligence in each stage[Result/conclusion] The process of scientific and technological innovation of technology-based SMEs consisted of four stages:knowledge innovation,technological innovation,technology application and business innovation.It pointed out the specific ways of using competitive intelligence to carry out scientific and technological innovation activities by competitive intelligence,and provided theoretical guidance and basis for scientific and technological innovation of technology-based SMEs.

[Purpose/Significance] Analyzing the basic information of the papers of the Chinese Competitive Intelligence Annual Conference from 2007-2016,the paper revealed the hotspots of competition intelligence research and its evolution pattern,and it explored the future trend of competitive intelligence;[Method/Process] The paper selected the papers of Chinese Competitive Intelligence Annual Conference from 2007-2016 to analyze high frequent key words with co-word analysis,cluster analysis,and strategic coordinate diagram;[Result/conclusion] The demonstration of the evolution of the theme of competitive intelligence research showed that the competitive intelligence system was the basic and active theme of domain research.The research of big data and think tanks would be a new challenge to the development of competitive intelligence in China.The integrated intelligence research based on intelligence pools would be the trend of future competitive intelligence research.

Online privacy concerns are regarded as an important influencing factor to prevent users from disclosing personal information.Given that privacy is associated with the situational multidimensional,dynamic concepts,the change of situation would affect users' understanding of privacy.Combining with the practical background and multidimensional development theory in e-commerce environment,the paper put forward the theoretical concept of online privacy concerns on the basis of previous studies,and it determined the composition of the online privacy concerns dimensions,developed the initial measurement,and then conducted the exploratory factor analysis,validation,factor analysis and validity analysis through three sets of independent sample data.The results showed that the scale had good reliability and validity,and the online privacy concerns consisted of control,collection,secondary use,error,improper access and remedy of 5 dimensions and 19 items.

With the improvement of network operation in pension,information security has already become one of the most important issues of insurance company in the Big Dataera.This paper,built on the purpose of increasing the information security management ability and protecting the security of pension,the pension information management system was analyzed.Five sources of information security issues were discussed in the view of construction.It was found that the pension management information should be protected through the entire operation flow.A information security system should be developed by using the theory of PDCA.These strategies could also be used on management of occupational pension.

This paper developed a method of detecting research hotspots and frontier based on Altmetrics indicators to improve the timeliness and accuracy of the result.Evaluation system including Altmetrics indicators and citation counts was established,and high impact papers of Scientometrics were selected by factor analysis.Mapping Knowledge Domain was conducted on these papers to detect research hotspots and frontiers in the field.The results showed that Altmetrics indicators could contribute to filter and select literatures in the process of research hotspots and frontier detecting,so as to reveal the development dynamics of academic journal and specific research field with higher timeliness and accuracy.

[Purpose/Significance] Finding the evaluation methods to identify high value scholarly book.[Method/Process] This article systematically reviewed the existing research work of evaluating the quality of scholarly book from three perspectives of theory,method and practice,found out the existing problems and proposes some measures.[Result/conclusion] The quality evaluation of scholarly book was the refinement of book evaluation,and its core lied in revealing the unique knowledge contribution and value.This study found that although the existing evaluation methods were diverse,they generally lacked a solid theoretical foundation and ignored or evaded the problem of revealing the value of books to varying degrees.In the future,the research work in the fields of natural language processing,semantic analysis,and book tagging was expected to bring inspiration to solve the problems in scholarly book quality evaluation research.

The focus of attention is to choose rational and scientific evaluation index.Based on the p-index idea,this paper put forward P_y-index for researcher evaluation under the condition of time effect and citation distribution.In view of paper citation distribution feature,paper cited threshold and paper cited half-period,literature organized in categories which include ordinary papers,potential papers,hot papers,classic papers.Different weights were given successively to those papers according to the increasing influence of them,the P_y-index was put out correctly.In this research,the top 100 scholars of library and information science in china were sorted by citations as a sample and the data about citing and cited literature were retrieved in the database of CNKI from 2000 to 2017.It was clarified that P_y-index could reflect the academic achievements of scholars based on the value and impact of the paper itself,and showed greater academic value-added effect highlighted by high quality papers compared to ordinary papers.In addition,compared with H-index and P-index,the P_y-index,with higher discrimination and sensitivity,more fair and equitable,was highly scientific and effective evaluation index.