a small-scale, internationalized, and first-class research institution aiming at tackling globally advanced and hard-fought scientific challenges. It focuses its research only on a few selected subject fields in Physical Sciences & Technologies, Biological Sciences and Technologies, and Information Sciences and Technology, and avoids trying to cover complete disciplines. As of June 2019, it has fewer than 200 faculty members, no more than 500 undergraduate and 1000 graduate enrollments yearly. The university evaluates the research performance of itself, its
It is notable that Material Science Multidisciplinary plays a very important role with a much higher nbetweenness value than the other WCs—except for
health information-seeking intention and testing the hypotheses. Studying these factors can be beneficial not only to health information-seeking behavior research, but also to improving the efficiency and accessibility of health information systems.
Effects of Situation on Information-seeking Behavior
As a purposeful activity of attempting to meet information needs, informationseeking behavior has become a hot issue in the field of library and information science (LIS). Belkin (1980) proposed that information needs arise because the
case where a network is damaged by randomly deleting links and/or adding random spurious links We only consider the case where a network is damaged by random deletions and/or additions. The task becomes more challenging if the most important links (e.g. those with high edge betweenness centrality) are targeted first. In other words, we want to test the error tolerance rather than the attack tolerance ( Jalili, 2011 ). . The task is to reconstruct the original network based on the damaged network. We will refer to the given network (i.e. the older snapshot or the
Zhesi Shen, Fuyou Chen, Liying Yang and Jinshan Wu
continuous vector representations for the nodes based on the network structure (Grover & Leskovec, 2016). The core algorithm in node2vec is word2vec ( Mikolov et al., 2013 ). Here we use node2vec to learn 32-dimensional vectors v n for each journal based on the journal citation network. In fact, we also tested 64 and 128-dimensional vector representation and we found similar map of science and similar clusters of journals. Please see the caption of Fig. 2(b) to further details. The underlying mechanism of node2vec is to produce vectors of nodes so that the nodes having
mobile search at least once a day.
Before the experiment, there were short periods of trial operation to test AWARE’s function and output. System operation, application usage, keyboard input, and location information were recorded in the experiment. Voice input, accounts and passwords, information received, and browsing history were not recorded. Since AWARE only recorded keyboard input, which participants could control, there was no privacy issue. Because we told the participants what kind of data we collected, they were reassured regarding the privacy of their data
papers which have received over 4,000 times of citation. She is the Co-Editor of Semantic Web Synthesis by Morgan & Claypool and serves editorial board of several leading international journals.
Scientific discovery revolves around the process of problem solving. It either uses existing well-established methods to explore a new area or invents new methods to solve existing problems. Either way, it is a journey into unknown terrain. Trial- and-error remains the most common approach to testing new ideas, learning from failures, and
Jose A. Moral-Munoz, Manuel Arroyo-Morales, Barbara F. Piper, Antonio I. Cuesta-Vargas, Lourdes Díaz-Rodríguez, William C.S. Cho, Enrique Herrera-Viedma and Manuel J. Cobo
period (1980–2013) was divided into two, three, and four subperiods, in order to test and establish the adequate number of periods to analyze. In that way, although it is common to use periods during the same time span, in the first years, there were low numbers of researchers and publications. Finally, a first subperiod of twenty-eight years (1980–2008), and a second subperiod of five years were established (2009–2013), since there was not enough document count to obtain an appropriate analysis. It allows us to have enough keywords to perform the analysis previously
The decision process for a company must be based on the market preferences, and for this reason, many companies consider that the key to success is to know their customers at a personal level (preferences). A recent study, conducted by IBM, indicates that 48% of consumers want personalized promotions through digital shipments, while 44% expect personalized benefits in physical stores ( Gonzalez, 2015 ).
One critical strategy to renew and stay in the commercial race in today’s competitive market is to know how the market is evolving
; Redner, 2005 ), mathematics ( van Calster, 2012 ), and medical sciences ( Gorry & Ragouet, 2015 ; Ohba & Nakao, 2012 ); the awakening probability of SBs based on a well-known stochastic model ( Burrell, 2005 ) or the citation distribution within the sleeping period ( Li et al., 2014 ); the citation lifecycle of SBs ( Lachance & Larivière, 2014 ); a new type of SB with a short leap immediately after publication ( Li, 2014 ; Li & Ye, 2012 ); the application-oriented tendency of the SBs in physical and engineering sciences ( van Raan, 2015 ). All the above studies