An analysis into using unstructured non-expert text in the illicit drug domain

Brian Carter; Markus Hofmann

doi:10.1109/IAdCC.2014.6779401

An analysis into using unstructured non-expert text in the illicit drug domain

Brian Carter
, Markus Hofmann

Research output: Contribution to conference › Paper › peer-review

Abstract

The Pillreports.com database was mined in order to determine if the free-text fields in the database could be of use in differentiating regular pills from those that have been adulterated, i.e. contains ingredients not comparable to MDMA.

Original language	English
Pages	651-657
Number of pages	7
DOIs	https://doi.org/10.1109/IAdCC.2014.6779401
Publication status	Published - 2014
Event	2014 4th IEEE International Advance Computing Conference, IACC 2014 - Gurgaon, India Duration: 21 Feb 2014 → 22 Feb 2014

Conference

Conference	2014 4th IEEE International Advance Computing Conference, IACC 2014
Country/Territory	India
City	Gurgaon
Period	21/02/14 → 22/02/14

Keywords

classification
Text analysis
web content mining

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10.1109/IAdCC.2014.6779401

Cite this

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abstract = "The Pillreports.com database was mined in order to determine if the free-text fields in the database could be of use in differentiating regular pills from those that have been adulterated, i.e. contains ingredients not comparable to MDMA.",

keywords = "classification, Text analysis, web content mining",

author = "Brian Carter and Markus Hofmann",

year = "2014",

doi = "10.1109/IAdCC.2014.6779401",

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AU - Hofmann, Markus

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KW - classification

KW - Text analysis

KW - web content mining

UR - https://www.scopus.com/pages/publications/84899119636

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DO - 10.1109/IAdCC.2014.6779401

M3 - Paper

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T2 - 2014 4th IEEE International Advance Computing Conference, IACC 2014

Y2 - 21 February 2014 through 22 February 2014

ER -

An analysis into using unstructured non-expert text in the illicit drug domain

Abstract

Conference

Keywords

Access to Document

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Cite this