23,589 research outputs found
A principal component analysis of 39 scientific impact measures
The impact of scientific publications has traditionally been expressed in
terms of citation counts. However, scientific activity has moved online over
the past decade. To better capture scientific impact in the digital era, a
variety of new impact measures has been proposed on the basis of social network
analysis and usage log data. Here we investigate how these new measures relate
to each other, and how accurately and completely they express scientific
impact. We performed a principal component analysis of the rankings produced by
39 existing and proposed measures of scholarly impact that were calculated on
the basis of both citation and usage log data. Our results indicate that the
notion of scientific impact is a multi-dimensional construct that can not be
adequately measured by any single indicator, although some measures are more
suitable than others. The commonly used citation Impact Factor is not
positioned at the core of this construct, but at its periphery, and should thus
be used with caution
Exploratory study to explore the role of ICT in the process of knowledge management in an Indian business environment
In the 21st century and the emergence of a digital economy, knowledge and the knowledge base economy are rapidly growing. To effectively be able to understand the processes involved in the creating, managing and sharing of knowledge management in the business environment is critical to the success of an organization. This study builds on the previous research of the authors on the enablers of knowledge management by identifying the relationship between the enablers of knowledge management and the role played by information communication technologies (ICT) and ICT infrastructure in a business setting. This paper provides the findings of a survey collected from the four major Indian cities (Chennai, Coimbatore, Madurai and Villupuram) regarding their views and opinions about the enablers of knowledge management in business setting. A total of 80 organizations participated in the study with 100 participants in each city. The results show that ICT and ICT infrastructure can play a critical role in the creating, managing and sharing of knowledge in an Indian business environment
Contextual Sequence Modeling for Recommendation with Recurrent Neural Networks
Recommendations can greatly benefit from good representations of the user
state at recommendation time. Recent approaches that leverage Recurrent Neural
Networks (RNNs) for session-based recommendations have shown that Deep Learning
models can provide useful user representations for recommendation. However,
current RNN modeling approaches summarize the user state by only taking into
account the sequence of items that the user has interacted with in the past,
without taking into account other essential types of context information such
as the associated types of user-item interactions, the time gaps between events
and the time of day for each interaction. To address this, we propose a new
class of Contextual Recurrent Neural Networks for Recommendation (CRNNs) that
can take into account the contextual information both in the input and output
layers and modifying the behavior of the RNN by combining the context embedding
with the item embedding and more explicitly, in the model dynamics, by
parametrizing the hidden unit transitions as a function of context information.
We compare our CRNNs approach with RNNs and non-sequential baselines and show
good improvements on the next event prediction task
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