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Data Exploration Using Example-Based Methods (Paperback)
Loot Price: R1,443
Discovery Miles 14 430
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Data Exploration Using Example-Based Methods (Paperback)
Series: Synthesis Lectures on Data Management
Expected to ship within 10 - 15 working days
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Data usually comes in a plethora of formats and dimensions,
rendering the exploration and information extraction processes
challenging. Thus, being able to perform exploratory analyses in
the data with the intent of having an immediate glimpse on some of
the data properties is becoming crucial. Exploratory analyses
should be simple enough to avoid complicate declarative languages
(such as SQL) and mechanisms, and at the same time retain the
flexibility and expressiveness of such languages. Recently, we have
witnessed a rediscovery of the so-called example-based methods, in
which the user, or the analyst, circumvents query languages by
using examples as input. An example is a representative of the
intended results, or in other words, an item from the result set.
Example-based methods exploit inherent characteristics of the data
to infer the results that the user has in mind, but may not able to
(easily) express. They can be useful in cases where a user is
looking for information in an unfamiliar dataset, when the task is
particularly challenging like finding duplicate items, or simply
when they are exploring the data. In this book, we present an
excursus over the main methods for exploratory analysis, with a
particular focus on example-based methods. We show how that
different data types require different techniques, and present
algorithms that are specifically designed for relational, textual,
and graph data. The book presents also the challenges and the new
frontiers of machine learning in online settings which recently
attracted the attention of the database community. The lecture
concludes with a vision for further research and applications in
this area.
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