1,721,004 research outputs found
Searching in Metric Spaces with User-Defined and Approximate Distances
No full textNovel database applications, such as multimedia, data mining, e-commerce, and many others, make intensive use of similarity queries in order to retrieve the objects that better fit a user request. Since the effectiveness of such queries improves when the user is allowed to personalize the similarity criterion according to which database objects are evaluated and ranked, the development of access methods able to efficiently support user-defined similarity queries becomes a basic requirement. In this article we introduce the first index structure, called the QIC-M-tree, that can process userdefined queries in generic metric spaces, that is, where the only information about indexed objects is their relative distances. The QIC-M-tree is a metric access method that can deal with several distinct distances at a time: (1) a query (user-defined) distance, (2) an index distance (used to build the tree), and (3) a comparison (approximate) distance (used to quickly discard from the search uninteresting parts of the tree). We develop an analytical cost model that accurately characterizes the performance of the QIC-M-tree and validate such model through extensive experimentation on real metric data sets. In particular, our analysis is able to predict the best evaluation strategy (i.e., which distances to use) under a variety of configurations, by properly taking into account relevant factors such as the distribution of distances, the cost of computing distances, and the actual index structure. We also prove that the overall saving in CPU search costs when using an approximate distance can be estimated by using information on the data set only (thus such measure is independent of the underlying access method) and show that performance results are closely related to a novel “indexing” error measure. © 2002, ACM. All rights reserved
Windsurf: Region-based image retrieval using wavelets
No full textIn this paper we present WINDSURF (Wavelet-Based Indexing of Images Using Region Fragmentation), a new approach to content-based image retrieval. The method uses the wavelet transform to extract color and texture features from an image and applies a clustering technique to partition the image into a set of "homogeneous" regions. Similarity between images is assessed by using the Bhattacharyya distance to compare region descriptors, and then combining the results at image level. Experimental results on a testbed of 10,000 general-purpose images show that our approach is very effective in retrieving images that are "semantically" similar to the query image. In particular, we compared results of WINDSURF with the approach by Stricker and Orengo [11], showing that a significant improvement is obtained in the quality of the result
Comparing performances of big data stream processing platforms with RAM3S
No full textNowadays, Big Data platforms allow the analysis of massive data streams in an efficient way. However, the services they provide are often too raw, thus the implementation of advanced real-world applications requires a non-negligible effort for interfacing with such services. This also complicates the task of choosing which one of the many available alternatives is the most appropriate for the application at hand. In this paper, we present a comparative study of the three major open-source Big Data platforms for stream processing, as performed by using our novel RAM 3 S framework. Although the results we present are specific for our use case (recognition of suspect people from massive video streams), the generality of the RAM 3 S framework allows both considering such results as valid for similar applications and implementing different use cases on top of Big Data platforms with very limited effort
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
From RAM3S to SPAF: Towards a Stream Processing Abstracting Framework
Full text linkWe describe the evolution of RAM3S, a software infrastructure for the integration of Big Data stream processing platforms, to SPAF, an abstraction framework able to provide programmers with a simple but powerful API to ease the development of stream processing applications. By using SPAF, the programmer can easily implement real-time complex analyses of massive streams on top of a distributed computing infrastructure, able to manage the volume and velocity of (multimedia) Big Data streams
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
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
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