1,721,273 research outputs found
ptype: probabilistic type inference
Get PDFType inference refers to the task of inferring the data type of a given column of data. Current approaches often fail when data contains missing data and anomalies, which are found commonly in real-world data sets. In this paper, we propose ptype, a probabilistic robust type inference method that allows us to detect such entries, and infer data types. We further show that the proposed method outperforms existing methods
Probabilistic type inference for the construction of data dictionaries
Get PDFThe data understanding stage plays a central role in the entire process of data analytics,
as it allows the analyst to gain familiarity with the data, identify data quality issues,
and discover initial insights into the data before further analysis (Chapman et al., 2000).
These tasks become easier in the presence of well-documented background information such as a data dictionary, which is defined as “a centralized repository of information about data such as meaning, relationships to other data, origin, usage, and format”
(McDaniel, 1994). However, data dictionaries are often missing or incomplete.
In this thesis we focus on inference of data types (both syntactic and semantic),
and develop probabilistic approaches that enable the automatic construction of a data
dictionary for a given dataset. Unlike existing rule-based methods, our proposed methods allow us to express uncertainty in a principled way and can provide accurate type
predictions even for messy datasets with missing and anomalous values.
The thesis makes the following contributions: First, we present ptype - a probabilistic generative model that uses Probabilistic Finite-State Machines (PFSMs) to
represent data types. By detecting missing and anomalous data, ptype infers syntactic
data types accurately and improves over the performance of existing approaches for
type inference. Moreover, it offers the advantage of generating weighted predictions
when a column of messy data is consistent with more than one type assignment, in
contrast to more familiar finite-state machines (e.g., regular expressions).
Secondly, we propose ptype-cat which is an extension of ptype for a better detection of the categorical type. ptype treats non-Boolean categorical variables as either
integers or strings. By combining the output of ptype and additional features that
can indicate whether a column represents a categorical variable or not, ptype-cat can
correctly detect the general categorical type (including non-Boolean variables). In
addition, we adapt ptype to the task of identifying the values associated with the corresponding categorical variable.
Finally, we present ptype-semantics to demonstrate how ptype can be enriched
by semantic information. In this regard, we focus on dimension and unit inference,
which are respectively the task of identifying the dimension of a data column and the
task of identifying the units of its entries. Syntactic type inference methods including
ptype do not address these tasks. However, ptype-semantic can extract extra semantic
information (such as dimension and unit) about data columns and treat them as either
floats or integers rather than strings
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
Having a look inside-out: impact of self-evaluation processes on quality assurance in higher education - the case of Unibe University
No full textThis study sets to investigate the use of self-evaluation mechanisms and processes as a device for improving quality in higher education. The study presents a single, longitudinal case study of a private university in the Dominican Republic and provides an account of how two self-evaluation processes helped in shaping a culture of self-reflection, quality awareness and actually improved some aspects of institutional performance. Most existing studies self-evaluations to date are grounded in the context of developed nations. This study therefore, aims to contribute to the existing literature on self-evaluation in higher education by exploring the experience of a private university in a developing nation.The findings show that the self-evaluation processes acted as triggers of positive change and improved the quality of a number of institutional functions as well as helped develop an evaluation culture in the university. The study recommends a model for Self-evaluation Quality Culture as well as a framework for successful self-evaluation as a trigger of positive change
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