1,721,133 research outputs found
Leveraging Deep Embeddings for Explainable Medical Image Analysis
No full textMachine learning techniques applied to the medical image analysis domain provide valuable tools that improve the diagnostic process. Among the proposed machine learning methodologies, deep neural networks are state-of-the-art in medical domain applications. However, they still have the disadvantage of being black-box methods. On the other hand, the medical field requires approaches that propose decisions based on an explainable mechanism, providing meaningful suggestions to physicians. In this chapter, we propose a general paradigm for an explainable classification of medical imaging data. This paradigm adopts deep metric learning to provide an embedding that enables the representation of images in either two or three dimensions. Metric learning plus dimensionality reduction in 2-3D introduces a first level of explainability. In particular, this is achieved by showing the training images closer to the test ones, consequently allowing for neighbour identification. A subsequent level of explainability is added by an interpretable classifier. This chapter will also present four use cases demonstrating the application of the proposed paradigm, each related to a specific kind of image dataset, such as histopathological or X-ray images
METODE FUZZY TIME SERIES DENGAN FAKTOR PENDUKUNG UNTUK MERAMALKAN DATA SAHAM
Get PDFPada skripsi ini dipaparkan metode baru dengan menggunakan fuzzy time series untuk sebuah peramalan data. Metode baru ini diperkenalkan oleh Chao-Dian Chen dan Shyi-Ming Chen pada tahun 2009. Pada skripsi ini metode yang digunakan akan diaplikasikan pada data saham di Indonesia Stock Exchange dengan faktor pendukung bursa saham singapura (STI) dan bursa saham di amerika serikat (DOW JONES). Langkah awal metode ini adalah mefuzzifikasi data utama dari faktor utama menjadi sebuah himpunan fuzzy dengan interval tertentu, untuk menentukan relasi logika fuzzy. Lalu membentuk relasi logika fuzzy menjadi grup relasi logika fuzzy. Kemudian membentuk grup relasi logika fuzzy antara variasi data historik utama dengan data historik pendukung untuk meramalkan data saham IDX.
Kata Kunci : himpunan fuzzy, fuzzy time series, relasi logika fuzzy, fuzzy varias
In this papper represented a new forecasting method for the Indonesia Stock Exchange with using fuzzy time series. This new method are introduced by Chao-Dian Chen and Shyi-Ming Chen at 2009. In this papper the method that used will be applied to Indonesia Stock Exchange with the secondary factor STI and Dow Jones. First, we fuzzify the historical data of the main factor into fuzzy sets with a fixed length of intervals to form fuzzy logical relationships. Then, we group the fuzzy logical relationships into fuzzy logical relationship groups. Then, we evaluate the leverage of fuzzy variations between the main factor and the secondary factor to forecast the IDX.
Keywords—fuzzy sets, fuzzy time series, fuzzy logical relationships, fuzzy variatio
Probabilistic Approaches for Sentiment Analysis: Latent Dirichlet Allocation for Ontology Building and Sentiment Extraction
No full textPeople’s opinion has always driven human choices and behaviors, even before the diffusion of Information and Communication Technologies. Thanks to the World Wide Web and the widespread of On-Line collaborative tools such as blogs, focus groups, review web sitesorums, social networks, millions of messages appear on the web, which is becoming a rich source of opinioned data. Sentiment analysis refers to the use of natural language processing, text analysis and computational linguistics to identify and extract subjective information in documents, comments and posts. The aim of this work is to show how the adoption of a probabilistic approach based on the Latent Dirichlet Allocation (LDA) as Sentiment Grabber can be an effective Sentiment Analyzer. Through this approach, for a set of documents belonging to a same knowledge domain, a graph, the Mixed Graph of Terms, can be automatically extracted. This graph, which contains a set of Mixed Graph of Terms, can be transformed in a Sentiment Oriented Terminological Ontology thanks to a methodology that involves the introduction of annotated lexicon as Wordnet. The chapter shows how the obtained ontology can be discriminative for sentiment classification. The proposed method has been tested in different contexts: standard datasets and comments extracted from social networks. The experimental evaluation shows how the proposed approach is effective and the results are quite satisfactory
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
Feature Discovery through Hierarchies of Rough Fuzzy Sets
No full textRough set theory and fuzzy logic are mathematical frameworks for granular computing forming a theoretical basis for the treatment of uncertainty in many real-world problems, including image and video analysis. The focus of rough set theory is on the ambiguity caused by limited discernibility of objects in the domain of discourse; granules are formed as objects and are drawn together by the limited discernibility among them. On the other hand, membership functions of fuzzy sets enables efficient handling of overlapping classes. The hybrid notion of rough fuzzy sets comes from the combination of these two models of uncertainty and helps to exploit, at the same time, properties like coarseness, by invoking rough sets, and vagueness, by considering fuzzy sets. We describe a model of the hybridization of rough and fuzzy sets, that allows for further refinements of rough fuzzy sets. This model offers viable and effective solutions to some problems in image analysis, e.g. image compression
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
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