1,720,962 research outputs found
Regular pattern and anomaly detection on corporate transaction time series
Get PDFBusiness applications make extensive usage of time series analysis for the most diverse tasks. By analyzing the development of any phenomena over time we gain some useful insights on the stock market forecast, analyze the risk related to investments, understand the behavior of a company on the market and so on. More specifically, in a corporate investment banking environment, analyzing the transaction history of a customer over the years is crucial to establish a fruitful relationship and adapt to its behavioural changes. In this environment we recognize three macro-categories of phenomena of interest: cyclic events, sudden and significant changes in trend, and isolated anomalous points. In this paper we present a framework to automatically spot these behaviors by means of simple - yet effective - machine learning techniques.We observe that cyclic behaviors and sudden changes can be easily targeted by means of adaptive threshold algorithms, while unsupervised machine learning techniques are the most reliable in detecting isolated anomalies. We design and test our algorithms on actual transactions collected in the past two years from more than 2,000 customers of UniCredit Bank, showing the efficiency of our solution. This work is tested to serve as a decision aid tool for corporate investment banking employees to facilitate the inspection of years of transactions and ease the visualization of interesting events in the customer history
A machine learning application for latency prediction in operational 4G networks
Get PDFMeasuring performance on Internet is always challenging. When it comes to the mobile networks, the variety of technology characteristics coupled with the opaque network configuration make the performance evaluation even a more difficult task. Latency is one of the aspects having the largest impact on the performance and on the end users' Quality of Experience. In this paper, we present a machine learning approach that, exploiting real mobile network data on the end user, try to predict the latency in a real operational network. We consider a large-scale dataset with more than 238 million latency measurements coming from 3 different commercial mobile operators. The presented methodology flattens the RTT values into several bins, turning the latency prediction problem to a multi-label classification problem. Then, three well-known supervised algorithms are exploited to predict the latency. The obtained results highlight the importance of representative dataset from operational network. It calls for further improvements on the algorithm selection, tuning, and their predictive capabilities
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe 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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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