Search results

This paper aims to establish a theoretical search model on academic social networking sites (ASNSs).

Based on the characteristics of ASNSs and a previous extended sense-making model, this paper first presented an initial model of searching on ASNSs. Next, an online survey was conducted on ResearchGate to understand the search processes and outcomes with the help of a survey questionnaire. In total, 359 participants from 70 countries participated in this online survey. The survey results provided a basis for modifying the initial model.

Results showed that the theoretical model of searching on ASNSs included motives for searching on ASNSs, identification of needs, search triggered by information needs, search triggered by social needs and outcomes. The search triggered by information needs was significantly positively correlated with learning outcomes. Besides learning outcomes, searching on ASNSs could help user amplify their social networks and promote research dissemination.

Understanding users’ search habits and knowledge acquisition can provide insights for ASNSs to design an interface to support searching and enhance learning. Moreover, the proposed model can help users recognize their knowledge status and learning effects and improve their learning efficiency.

This paper contributes to establishing a theoretical model to understand users’ search process and outcomes on ASNSs.

The study focused on online public access catalog (OPAC) users’ cross-device search behavior. The purpose of this paper is to understand the characteristics of cross-device OPAC searches, and to identify query reformulation (QR) patterns during device transitions.

The transaction log from a university library, spanning six months, was used to conduct the quantitative analysis. The query vocabulary richness, which refers to the average number of unique words each query contains in a search session, can evaluate query diversity, and contribute to the analysis of QR.

The results show that PC-PC transition is the most important pattern of device transition. The time interval of device transition was different to the time interval of transitions in web searches. Short device transitions mainly occurred in daytime, and the number of transitions that occurred in less than one minute was higher than on the web. Searches for Industry and Technology triggered the most device transitions, and the users tended to choose the same search field. In addition, the authors made a detailed analysis of the reasons for same-type device transitions and different-type device transitions. Furthermore, the authors focused on the characteristics of adjacent QR patterns. The authors not only refined the concept of cross-device to include the same-type device transition, but also summarized the characteristics of the cross-device QR patterns, which can be used to predict post-switch queries.

This study extends research into cross-device interaction and cross-device search to the domain of digital library research. The authors also introduced QR perspective on cross-device interaction on OPAC.

This paper discusses the differences in search pattern transitions for mobile phone, tablet and desktop devices by mining the transaction log data of a library online public access catalogue (OPAC). We aimed to analyze the impacts of different devices on user search behavior and provide constructive suggestions for the development of library OPACs on different devices.

Based on transaction logs which are 9 GB in size and contain 16,140,509 records of a university library OPAC, statistics and clustering were used to analyze the differences in search pattern transitions on different devices in terms of two aspects: search field transition patterns and query reformulation patterns.

Search field transition patterns are influenced by the input function and user interfaces of different devices. As reformulation times increase, the differences between query reformulation patterns among different devices decrease.

Mobile-side libraries need to optimize user interfaces, for example by setting web page labels and improving input capabilities. Desk-side libraries can add more suggestive content on the interface.

Unlike previous studies, which have analyzed web search, this paper focuses on library OPAC search. The search function of mobile phones, tablets and desktops were found to be asymptotic, which was a good illustration of how devices have a large impact on user search behavior.

Currently, countries worldwide are struggling with the virus COVID-19 and the severe outbreak it brings. To better benefit from open government health data in the fight against this pandemic, this study developed a framework for assessing open government health data at the dataset level, providing a tool to evaluate current open government health data's quality and usability COVID-19.

Based on the review of the existing quality evaluation methods of open government data, the evaluation metrics and their weights were determined by 15 experts in health through the Delphi method and analytic hierarchy process. The authors tested the framework's applicability using open government health data related to COVID-19 in the US, EU and China.

The results of the test capture the quality difference of the current open government health data. At present, the open government health data in the US, EU and China lacks the necessary metadata. Besides, the number, richness of content and timeliness of open datasets need to be improved.

Unlike the existing open government data quality measurement, this study proposes a more targeted open government data quality evaluation framework that measures open government health data quality on a range of data quality dimensions with a fine-grained measurement approach. This provides a tool for accurate assessment of public health data for correct decision-making and assessment during a pandemic.

This paper aims to identify consumers' health information consultation patterns by analyzing information sources to better understand consumers' health information needs and behavior in the context of multisource health information.

Haodaifu Online, an online health consultation (OHC) website in China, was used as a research data source, and 20,000 consultation cases were collected from the website with Python. After screening and cleaning, 1,601 consultation cases were included in this study. A content analysis-based mixed-methods research approach was applied to analyze these cases.

The results indicate that with the participation of OHC, there are 15 patterns of consumer health information consultation. Besides OHC, health information sources reported by consumers included medical institutions family/friends and the Internet. Consumers consult on a wide range of health issues including surgical conditions obstetrical and gynecological conditions and other 20 subjects. Consumers have multiple information needs when using OHC: getting prescriptions, diagnosing diseases, making appointments, understanding illnesses, confirming diagnoses and reviewing costs. Through further analysis it was found that consumers’ health information consultation patterns were also significantly different in health issues and health information needs.

This study broadens one’s understanding of consumer health information behavior, which contributes to the field of health information behavior, and also provides insight for OHC stakeholders to improve their services.

Culture is considered a critical aspect of social media usage. The purpose of this paper is to explore how cultures and languages influence multilingual users' cross-cultural information sharing patterns.

This study used a crowdsourcing survey with Amazon Mechanical Turk to collect qualitative and quantitative data from 355 multilingual users who utilize two or more languages daily. A mixed-method approach combined statistical, and cluster analysis with thematic analysis was employed to analyze information sharing patterns among multilingual users in the Chinese cultural context.

It was found that most multilingual users surveyed preferred to share in their first and second language mainly because that is what others around them speak or use. Multilingual users have more diverse sharing characteristics and are more actively engaged in social media. The results also provide insights into what incentives make multilingual users engage in social media to share information related to Chinese culture with the MOA model. Finally, the ten motivation factors include learning, entertainment, empathy, personal gain, social engagement, altruism, self-expression, information, trust and sharing culture. One opportunity factor is identified, which is convenience. Three ability factors are recognized consist of self-efficacy, habit and personality.

The findings are conducive to promoting the active participation of multilingual users in online communities, increasing global resource sharing and information flow and promoting the consumption of digital cultural content.

The purpose of this study is to solve the problems of poor stability and high energy consumption of the dynamic window algorithm (DWA) for the mobile robots, a novel enhanced dynamic window algorithm is proposed in this paper.

The novel algorithm takes the distance function as the weight of the target-oriented coefficient, and a new evaluation function is presented to optimize the azimuth angle.

The jitter of the mobile robot caused by the drastic change of angular velocity is reduced when the robot is closer to the target point. The simulation results show that the proposed algorithm effectively optimizes the stability of the mobile robot during operation with lower angular velocity dispersion and less energy consumption, but with a slightly higher running time than DWA.

A novel enhanced dynamic window algorithm is proposed and verified. According to the experimental result, the proposed algorithm can reduce the energy consumption of the robot and improves the efficiency of the robot.

Ethnic minorities (EMs), who make up a sizable proportion of multilingual users, are more likely to browse and search in their native language. It is helpful to identify multilingual users' information needs to provide public digital cultural services (PDCS) for making their life better.

The in-context interview is an efficient way to explore EMs' information needs and evoke their daily experience with PDCS. The material from 31 one-on-one interviews with EMs in China was recorded and analyzed using thematic analysis.

The findings reveal that language proficiency is a critical factor influencing multilingual information access (MLIA) and multilingual users' information needs. Moreover, language ability, digital literacy and cultural literacy are important components of multilingual information literacy (MLIL), which is helpful for EMs to access PDCS. In light of Kochen's theory, the information needs of PDCS can be classified into the aroused need of resources, the recognized need of functions and services and expressed need. For the expressed need, it is necessary to develop a one-stop convergence platform of PDCS to process various requests of resources, functions and services in the future.

The findings will be valuable for governments, public institutions and social organizations in identifying, addressing and resolving these issues about PDCS.

The purpose of this paper is to present a simple yet effective force control scheme for collaborative robots by addressing the problem of disturbance rejection in joint torque: inherent actuator flexibility and nonlinear friction.

In this paper, a joint torque controller with an extended state observer is used to decouple the joint actuators from the multi-rigid-body system of a constrained robot and compensate the motor friction. Moreover, to realize robot force control, the authors embed this controller into the impedance control framework.

Results have been given in simulations and experiments in which the proposed joint torque controller with an extended state observer can effectively estimate and compensate the total disturbance. The overall control framework is analytically proved to be stable, and further it is validated in experiments with a robot testbed.

With the proposed robot force controller, the robot is able to change its stiffness in real time and therefore take variable tasks without any accessories, such as the RCC or 6-DOF F/T sensor. In addition, programing by demonstration can be realized easily within the proposed framework, which makes the robot accessible to unprofessional users.

The main contribution of the presented work is the design of a model-free robot force controller with the ability to reject torque disturbances from robot-actuator coupling effect and motor friction, applicable for both constrained and unconstrained environments. Simulation and experiment results from a 7-DOF robot are given to show the effectiveness and robustness of the proposed controller.