Results by title

3 books match the query 'Data mining'

cover of Blow Up the Humanities

Blow Up the Humanities

Toby Miller

Temple University Press, 2012

A short, sharp, and provocative book, Blow Up the Humanities has esteemed scholar Toby Miller declaring that there are two humanities in the United States. One is the venerable, powerful humanities of private universities; the other is the humanities of state schools, which focus mainly on job prospects. There is a class division between the two—both in terms of faculty research and student background—and it must end.

Miller critically lays waste to the system. He examines scholarly publishing as well as media and cultural studies to show how to restructure the humanities by studying popular cultural phenomena, like video games. Miller ultimately insists that these two humanities must merge in order to survive and succeed in producing an aware and concerned citizenry.

[more]
cover of Data: Now Bigger and Better!

Data

Now Bigger and Better!

Edited by Tom Boellstorff and Bill Maurer

Prickly Paradigm Press, 2015

Data is too big to be left to the data analysts. Data: Now Bigger and Better! brings together researchers whose work is deeply informed by the conceptual frameworks of anthropology—frameworks that are comparative as well as field-based. From kinship to gifts, everything old becomes rich with new insight when the anthropological archive washes over “big data.” Bringing together anthropology’s classic debates and contemporary interventions, the book counters the future-oriented speculation so characteristic of discussions regarding big data. Drawing on the long-standing experience in industry contexts, the contributors also provide analytical provocations that can help reframe some of the most important shifts in technology and society in the first half of the twenty-first century.
[more]
cover of Knowledge Discovery and Data Mining

Knowledge Discovery and Data Mining

M.A. Bramer

The Institution of Engineering and Technology, 1999

Modern computing systems of all kinds accumulate various data at an almost unimaginable rate. Alongside the advances in technology that make such storage possible has grown a realisation that buried within this mass of data there may exist some knowledge of considerable value. This could be information critical for a company's business success or something leading to a scientific or medical discovery or breakthrough. Most data is simply stored and never examined, but machine-learning technology has the potential to extract knowledge of value (i.e. data mining).
[more]