1,720,954 research outputs found
AI-Powered Investment Decision Support Systems: Building Smart Data Products with Embedded Governance Controls
Get PDFThis paper explores some of the possible investment decision support systems powered by artificial intelligence, what components they include and how they operate. Progressing further, we analyze how different artificial intelligence and machine learning bases algorithm types, using different initial data and solving different tasks from simple classification of predefined assets to high-level algorithmic decision generation and implementing task can be combined together and layered to obtain a hierarchical multi-module architecture of the investment decision support system, which would maximize the advantages and minimize the disadvantages of utilizing artificial intelligence methods in the context of generating synthetic market predictions by the investment decision support system. Another critical aspect of investment decision support systems is the aggregation and optimization of the raw signals received from the prediction modules into trading signals, actionable within the high-frequency trading framework and deployable by algorithmic trading systems. We muse upon the possible trading signals aggregation function types and optimization traffic routing from the aggregated trading signals up to the algorithmic trading systems.
Within the next decade or so, investment decision support systems, generating synthetic market predictions and supporting traders dealing with tradeable assets, financial markets and instruments, will be heavily augmented and empowered with Artificial Intelligence and Machine Learning innovative algorithms and techniques, much the same way as classical industrial production architectures operated and supervised within the boundaries of the predetermined parameters are augmented and supported by Industrial AI and Machine Learning algorithms nowadays. Some of the main stages of decision making on the part of such systems follow the stages of cognitive vision and cognitive speech to some extent, observing the abstraction level ontology from raw primary inputs, such as images, sounds and other sensory data information for cognitive vision and cognitive speech systems to more complicated systems patterns formed on the system cognitive level
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
Designing Scalable Data Product Architectures With Agentic AI And ML: A Cross-Industry Study Of Cloud-Enabled Intelligence In Supply Chain, Insurance, Retail, Manufacturing, And Financial Services
Get PDFThe emergence of industrial product lines enabled the creation of the most complex products ever. Product models are necessary to design, configure and maintain this complexity. The systems at the core of current scalable product based software development are usually realized as rigid to change data models embodied in relational databases. This makes it expensive to exploit product model data and hampers innovation. Semantic technologies remove many of these problems but until recently lacked the performance and scalability to be put into production for large product lines. With the advent of linked data platforms this has changed. This paper outlines our design considerations for a product model framework based on the linked data principle and motivated by both business and technical needs. We present our architectural blueprint for product models and show how we apply this to three different domains. These domain models cover conventional data products, devising interaction with humans, and facilitating cooperative distributed creation of data collections. Our chosen level of generalization enables us to expose important ideas factored into our framework. It also sets the stage for open collaboration on the development and extension of product model ontologies.
Currently our data products exist as independent implementations to a varying degree addressing their respective business needs. We plan to join forces with partners to realize a family of linked data products describing different fields of human endeavor. Case studies are the ideal method to get involved in such an endeavor. To that end we invite readers to contribute to our effort. In the remainder of the paper we first outline design rationales in Section 1. Section 2 presents a blueprint for a linked data product family. Domain models, realizing components of the product blueprint, are then described in Section 3. The paper is concluded in Section 4
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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