1,720,962 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Connection discovery through user-shared images : from multimedia big data characterization, analytics to applications
No full textHuman beings are born social. In the social media era, we share and interact with others digitally, forming online social graphs and sharing billions of images. Many social media applications, such as recommendation, virality prediction, and marketing, make use of social graphs as similar users (e.g., users with similar interests) tend to be friends. However, the social graph may not be explicitly specified by users or may be kept private due to privacy concerns. Meanwhile, billions of user-shared images are shared by individuals, and the images are widely accessible to others due to their sharing nature. These user shared images are proved to be a more effective alternative to discover user connections. This thesis introduces a novel way to detect social signals from low level visual features, and to represent them with unbiased machine-generated labels to discover user connections. Based on 11 million user-shared images from 11 real social media platforms, a phenomenon exists that related users who have online friendships or follower/followee relationships on those platforms share more similar images. This phenomenon is independent of the network origins, the content sharing mechanisms and the image processing/computer vision techniques that encode the images. Hence, an analytic framework is proposed to measure, formulate and utilize the phenomenon for follower/followee recommendation. The framework is optimized for social signal detections using deep learning. Different applications are also discussed. To the best of our knowledge, this framework is the first attempt to discover connections by detecting social signal from user-shared images.</p
Kernel-based multiple-instance learning
No full textIn recent years, the Multiple-Instance Learning (MIL) problem is becoming more and more popular in the machine learning community. Each training object (bag) of the MIL problem is a set of patterns (instances). Label information is only associated with the bags, but not with their constituent instances. Moreover, a positive bag must have at least one positive instance, but may have many neg-ative instances. Since we can only access the label information of a bag and a positive bag may have many negative instances, MIL is more challenging than the traditional supervised learning (or single-instance learning). On the other hand, it is fruitful to study MIL, since many real-world problems such as drug activity prediction are inherently MI problems which cannot be generalized well under the traditional single-instance learning model. In addition, the generaliza-tion performance of many single-instance learning problems, e.g., Content-based Image Retrieval (CBIR), are found to be improved when they are casted into an appropriate MIL representation.In this thesis, I study MIL algorithms based on kernel methods. In particular, I focus on support vector machines, which have been highly successful in many machine learning problems. This thesis first discusses how to re-formulate the SVM to adapt to the MI problem setting by utilizing both the bag and instance information at the same time. After that, I propose how to define a MI kernel over bags based on the marginalizing kernel. The resulted bag kernel can then be used in a standard SVM. I also extend this marginalized kernel to the real-valued regression setting, which is more and more popular in the MIL community. Empirical results show that the proposed methods have better performance over various traditional methods.</p
MCMC-based human tracking with stereo cameras under frequent interaction and occlusion
No full textHuman Tracking in a video sequence is an important task in civilian surveillance. Successful human tracking provides data for security-purposes and personal monitoring systems. The trajectories of humans are one of the indications of potential criminal activity.However, human tracking in video sequences is always a challenging problem. Due to rapid changes in shape with irregular motion, typical methods may not have satisfactory results, especially under frequent occlusion and interaction. Occupancy which makes use of the foreground pixels is one of the possible solutions. With a single camera, the lack of 3D information on humans makes the problem more challenging under frequent occlusion and interaction. Recently, methods based on multiple cameras have been proposed. These make use of views shot from different locations. The tracking is based on a 2D occupancy map built from the different views. Occlusion can be handled well, but it requires a high computation cost and suffers from the need for synchronization.In this thesis, an approach with stereo cameras is proposed. The setting required is easier to implement than the one in the multi view approach, and the run time required is much shorter than in the multi view approach, which makes the stereo cameras approach suitable for real time tracking. A similar 2D occupancy map to the one in the multi view approach can be built. Without views from different locations, an occlusion and an interaction model are required to obtain a similar performance to the multi view approach.The proposed algorithm combines the occlusion and interaction model and Markov Chain Monte Carlo (MCMC) such that humans can be tracked under frequent interaction and occlusion. The number of failures has been reduced successfully by 78%. This thesis presents an efficient and effective algorithm under frequent interaction and occlusion.</p
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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