Life science companies increasingly rely on text mining to gain important insights from vast amounts of published information. But researchers struggle to get access to full-text articles for text mining. When they do get the full text they must contend with multiple formats and inconsistent license terms – all of which inhibit text mining efforts. In this presentation, we will describe the value in mining full-text scientific literature and outline the issues researchers face in accessing and licensing this content for commercial purposes. We will provide a walkthrough of Copyright Clearance Center’s (CCC) RightFind™ XML for Mining solution and contrast this with other approaches to solving these time-consuming content and licensing challenges. CCC is the parent organization of RightsDirect.

1. Improving Text Mining Results with
Access to Full-Text Scientific Articles
Mike Iarrobino
Product Manager, CCC

2. Introduction
Mike Iarrobino
Product Manager
RightFind™ XML for Mining
Copyright Clearance Center

3. Making Copyright Work – CCC and RightsDirect
Rightsholders Content Users
• Licensing Solutions
• Rights Management
• Content Delivery
• Copyright Education
950+ million rights from:
• Publishers
• Authors
• Agents
• Creators
• 35,000 companies
• Workers worldwide
• 1,200 colleges
and universities
• Publishers and
Authors

4. CCC and Text Mining
Rightsholders Content Users
Servicing many text
mining license and
content requests
Managing text
mining feeds
Negotiating text
mining rights with
multiple publishers

5. “Text mining” is the process of
deriving high-quality information
from text materials using software.

6. Text Mining
Non-Patent
Literature
• Mining limited to abstracts
• High cost to obtain
formatted full-text
content and permission
from multiple publishers
• Multiple formats
• Researchers can’t mine
content to which they
are not subscribed

7. What is the Benefit of Full Text?
Volume Timeliness Quality
Catherine Blake. “Beyond genes, proteins, and abstracts:
Identifying scientific claims from full-text biomedical
articles.” Journal of Biomedical Informatics Volume 43,
Issue 2, April 2010, Pages 173–189
Elsevier (2015) Harnessing the Power of Content -
Extracting value from scientific literature: the power of
mining full-text articles for pathway analysis. Available at
www.elsevier.com/__data/assets/pdf_file/0016/83005/R
_D-Solutions_Harnessing-Power-of-Content_DIGITAL.pdf
Elsevier (2015) Harnessing the Power of Content -
Extracting value from scientific literature: the power of
mining full-text articles for pathway analysis. Available at
www.elsevier.com/__data/assets/pdf_file/0016/83005/R
_D-Solutions_Harnessing-Power-of-Content_DIGITAL.pdf
Enrique Bernal-Delgado and Elliot S
Fisher. “Abstracts in high profile journals
often fail to report harm.” BMC Medical
Research Methodology (2008); 8:14

8. Volume and Recall
December 20158
(Abstract: "tau hyperphosphorylation" AND
Abstract: kinase OR (GSK3β OR (CDK5 OR (MAPK1 OR
(MARK1 OR (MARK2 OR (MARK3 OR MARK4))))))) AND
(Abstract: alzheimer OR alzheimer's)
content:"tau hyperphosphorylation kinase"~25 OR
"tau hyperphosphorylation GSK3β "~25 OR "tau
hyperphosphorylation CDK5"~25 OR "tau
hyperphosphorylation MAPK1"~25 OR "tau
hyperphosphorylation MARK1"~25 OR "tau
hyperphosphorylation MARK2"~25 OR "tau
hyperphosphorylation MARK3"~25 OR "tau
hyperphosphorylation MARK4"~25

9. Volume and Recall - Results
December 20159
0
100
200
300
400
500
600
700
800
BTK Tau
hyperphosphorylation
NumberArticles
Abstract
Full text

10. Text Mining Today – Example Workflow
December 201510
Search
Get
permission
Download
PDFs
Convert
PDFs
Import into
text mining
software
Search
Get
permission
Download
PDFs
Convert
PDFs
Import into
text mining
software
• Perform search• Obtain permission from
publishers to mine full
text for commercial use
• Requires automated tool or
custom software to download
in bulk
• Requires text mining permission
from multiple publishers
• Requires content storage and
feed management
• PDF is converted to a “blob of text”
• No tags
• Loss of metadata
• Low fidelity of content
• References induce noise
• Requires structuring text into XML
• Article text does not
have “fields”
• Combining content
from multiple sources
takes time to normalize
the metadata
Search
Get
permission
Download
PDFs
Convert
PDFs
Import into
text mining
software
TEXT MINING TOOLS
Run
queries
View
results
MANUAL WORKTypically takes
4-8 weeks

11. CCC’s RightFind™ XML for Mining Service
Build a corpus of full-text articles in XML format for mining
Text Mining SoftwareCCC’s Text Mining Service

12. XML for Mining
• Rapid inventory growth
• MEDLINE abstract corpus
• Purchase not subscribed articles
with cost optimization process
• MeSH article tagging and flat
synonym list

13. Market Observations and Future Vision
ACCESS
AUTOMATION

14. Thank you!
Mike Iarrobino
Product Manager, CCC
+1.978.646.2633
miarrobino@copyright.com