1,721,149 research outputs found
Type Inference for Queries on Semistructured Data (Extended Abstract)
No full textTova Milo Tel Aviv University [email protected] Dan Suciu AT&T Labs [email protected] 1 Introduction Semistructured data allows data to be given without a schema. Objects may have arbitrary combinations of attributes, different objects may have the same attribute with different types, collections may be heterogeneous, etc. The schematic information is embedded in the data, i.e. objects have the names of their attributes stored with the object. The model has proven successful in a number of applications like data integration [PGMW95], querying biological data [BDHS96], querying the WWW [MMM96], managing Web sites [FFK + 98], or as a general-purpose management system [QRS + 95]. In all these applications however, data often has some regularity and ignoring the available (possibly partial) schema results in several drawbacks, like efficiency penalties in querying and storing the data, or the loss of semantics for the user, making it hard to formulate queries. Researchers ha..
Schema-Based Data Translation (Extended Abstract)
No full textTova Milo Tel Aviv University [email protected] Sagit Zohar Tel Aviv University [email protected] 1 Introduction Data integration and translation is a problem facing many organizations that wish to utilize Web data. A broad spectrum of data is available on the Web in distinct heterogeneous sources, stored under different formats: a specific database vendor format, SGML or Latex (documents), DX formats (scientific data), Step (CAD/CAM data), etc. Their integration is a very active field of research and development, (see for instance, for a very small sample, [16, 10, 14, 13, 26, 22, 15, 4, 3]). A key observation is that, often, the application programs used by organizations can only handle data of a specific format. (e.g. Web browsers, like Netscape, expect files in HTML format, and relational databases expect relations) . To enable a specific tool to manipulate data coming from various sources (e.g. use, in a relational system, data stored on the Web in HTML format), a transla..
The Smart Crowd - Learning from the Ones Who Know (Invited Talk)
No full textOne of the foremost challenges for information technology over the last few years has been to explore, understand, and extract useful information from large amounts of data. Some particular tasks such as annotating data or matching entities have been outsourced to human workers for many years. But the last few years have seen the rise of a new research field called crowdsourcing that aims at delegating a wide range of tasks to human workers, building formal frameworks, and improving the efficiency of these processes.
In order to provide sound scientific foundations for crowdsourcing and support the development of efficient crowd sourcing processes, adequate formal models and algorithms must be defined. In particular, the models must formalize unique characteristics of crowd-based settings, such as the knowledge of the crowd and crowd-provided data; the interaction with crowd members; the inherent inaccuracies and disagreements in crowd answers; and evaluation metrics that capture the cost and effort of the crowd.
Clearly, what may be achieved with the help of the crowd depends heavily on the properties and knowledge of the given crowd. In this talk we will focus on knowledgeable crowds. We will examine the use of such crowds, and in particular domain experts, for assisting solving data management problems. Specifically we will consider three dimensions of the problem: (1) How domain experts can help in improving the data itself, e.g. by gathering missing data and improving the quality of existing data, (2) How they can assist in gathering meta-data that facilitate improved data processing, and (3) How can we find and identify the most relevant crowd for a given data management task
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
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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