II-SDV 2015, 20 - 21 April, in Nice

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Dr. Haxel Consult

Internet

Text and Data Mining at CCC
Solving the Content Retrieval and Licensing Conundrums for TDM
Dr. Haralambos Marmanis
CTO & VP, Engineering
Copyright Clearance Center

Making Copyright Work – CCC and RightsDirect
Rightsholders Content Users
600+ million rights
from:
• Publishers
• Authors
• Creators
• 35,000 companies
• Employees
worldwide
• Users in 180
countries
• Licensing
Solutions
• Rights
Management
• Content Delivery
• Copyright
Education
4/22/2015

What Is Text and Data Mining?
• Automate the extraction of “Entities” from Text
• Find Relationships and Patterns
• Produce hypotheses of interest
• Drive decision making
4/22/20155

Applications
• Biomarker discovery
• Drug repurposing
• Drug safety
• Competitive intelligence
• Sentiment analysis
• …….
4/22/20156

The General Problem & Our Solution
Through An Example
4/22/20157

“Drug Discovery” Process
• Goal: Develop new treatments for diseases
through hypothesis formation.
• Methodology:
– Keyword/Database Searching
– Review Literature
– Find relationships
– Develop hypothesis
– Test
– Product development
Etc.
4/22/20158

General Overview of the Process
1. Identify a set of resources that are relevant to a
particular research objective
2. Analyze and extract information specific to the
research objective
3. Develop and explore the various relations between
extracted objects of interest
4/22/20159

Data Processing Workflow:
Information Retrieval and Knowledge Discovery
4/22/201510 *http://www.jisc.ac.uk/reports/value-and-benefits-of-text-mining
Software Platforms for TDM
Information
Retrieval
Knowledge
Discovery

Problem: Too Much Research
• 53M Records in Scopus
• 800,000 Journal Articles published per year
4/22/201511

More Problems…
• Many sources of content
• Many formats
• Difficult to obtain full-text in XML
• Difficult to integrate content into TDM software.
• Hard to negotiate and manage licenses and feeds from
all publishers.
4/22/201512

The DirectPath Solution
• Speed up time to obtain properly licensed content for
text mining
• Discover and download full-text in XML, not just
abstracts
• Main corpus includes Subscribed and Not-Subscribed
content
• Normalize XML format across many publishers
• Provide a Web UI and RESTful API services
4/22/201513

4/22/201514
2. Researchers create
content sets by using
search or other
discovery criteria
XML
Article
corpus
TDM Software
3. Researchers slice and
dice results and identify
an appropriate corpus for
their project
4. XML corpus
can be
imported into
various TDM
tools
1. Publishers
provide
content
and rights
<XML>
<XML>
<XML>
Publishers Researchers

RESTful Services Based on Open Standards
4/22/201522

Unique Features
• Custom analysis/indexing for each Project
– Custom stop-word lists; synonyms/dictionaries
– Custom analyzers
– The finest granularity at the analysis and indexing level
• Build by design with multilingual support in mind
– Based on Lucene
• Search beyond TFIDF (e.g. document ranking by citation)
• Retrieval beyond Search (e.g. nearest neighbors)
• Cost and Quality Optimization (roadmap/patent pending)
• Integration with text mining tools like Linguamatics I2E
4/22/201524

TDM Product Roadmap
• Augment and Enrich the Inventory
• Workflow Integrations with 3rd Party Support
• Expand and enhance Metadata Normalization
• Introduce Content Metrics for Retrieval
• Cost Optimization
• Information Content Optimization
4/22/201525

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AI-SDV 2022: New Insights from Trademarks with Natural Language Processing Al...

Dr. Haxel Consult

In our customer projects involving automated document processing, we often encounter document types providing crucial data in the form of tables. While established text analytics algorithms are usually optimized to operate on running text, they tend to produce rather poor results on tables as they do not capture the non-sequential relations inside them (e.g. interpret the content of a table cell relative to its column title, interpret line breaks inside a cell differently from line breaks between cells or rows). While there are elaborate information extraction products in the market for a few highly specific types of tabular documents, there is no general approach out there. The main cause for this is the fact that table structures can be encoded by a heterogenous range of layout means (e.g. column boundaries can be signaled by lines vs. aligned text vs. white space). In this talk, we will illustrate several solutions that we have developed for a range of challenges occurring in this context, both for scanned and digitally generated documents.

AI-SDV 2022: Extracting information from tables in documents Holger Keibel (K...

Dr. Haxel Consult

Most scientific journals request, that the complete set of research data is published simultaneously with the peer-reviewed paper. The publication of the research data usually is carried out as so-called "Supplementary Material", attached to the original paper, or on a "Research Data Repository". Both forms have in common, that the data is published usually unstructured and not in an uniform machine processable format. This makes its further use in electronic tools for AI or data mining unnecessarily difficult or even impossible. A concept is presented, in which the data is digitally recorded, following the principle of FAIR data, as part of the publication process. This digital capture makes the data available to the scientific community for easy use in data mining and AI tools. The data in the repository contains links to the publication to document its origin. The concept is applicable for preprints, peer-review papers, diploma and doctoral theses and is particularly suitable for open access publications. Moreover, the presentation highlights correspondent activities, which were released in scientific publications recently.

AI-SDV 2022: Scientific publishing in the age of data mining and artificial i...

Dr. Haxel Consult

AI-SDV 2022: AI developments and usability Linus Wretblad (IPscreener / Uppdr...

Dr. Haxel Consult

How do you find video when you only have sparse data? While you can wander the stacks (if you can still find open stacks) for inspiration, video either physical or digital, is difficult to discover. Wandering the virtual stacks is, well, virtually impossible. Discovery platforms on the whole have not replicated the inspirational experience of wandering the stacks. More companies are using archivable video for internal communication of the various research projects, product developments, test results, and more that are being considered, in progress, or completed. Showing how an experiment was conducted can convey considerably more information that is very difficult to communicate via text. How do you find a company video that might be helpful for your project? A case study is presented of the problems and the solutions that were implemented by a large, multinational chemical company. A suite of content discovery technologies was used including a video to text to tagging system connected to their documents database and automatically indexed using several chemical as well as conceptual systems (rule-based, NLP, inference engine). To build the system and support the manuscript and video submission there is a metadata extraction program which pulls and inserts the metadata into the submission forms so the author can move quickly through that process.

AI-SDV 2022: Where’s the one about…? Looney Tunes® Revisited Jay Ven Eman (CE...

Dr. Haxel Consult

Copyright Clearance Center A pioneer in voluntary collective licensing, CCC (Copyright Clearance Center) helps organizations integrate, access, and share information through licensing, content, software, and professional services. With expertise in copyright and information management, CCC and its subsidiary RightsDirect collaborate with stakeholders to design and deliver innovative information solutions that power decision-making by helping people integrate and navigate data sources and content assets. CCC recently acquired the assets and technology of Deep SEARCH 9 (DS9), a knowledge management platform that leverages machine learning to help customers perform semantic search, tag content, and discover new insights.

AI-SDV 2022: Copyright Clearance Center

Dr. Haxel Consult

Lighthouse IP is the world’s leading provider of intellectual property content. The core business of Lighthouse IP is sourcing and creating content from the world’s most challenging authorities. Specialized in IP data, Lighthouse IP provides over 160 countries coverage for patents, over 200 authorities for trademarks and over 90 authorities for designs. Lighthouse IP data is available via several partners. The company is headquartered in Schiphol-Rijk in the Netherlands and has offices in the United States, China, Thailand, Vietnam, Egypt, Indonesia and Belarus. Globally a team of 150 experts works on the creation of this unique data collection.

AI-SDV 2022: Lighthouse IP

Dr. Haxel Consult

CENTREDOC was created in 1964 as the technical information center of the swiss watchmaking industry. Building on a strong team of engineers, CENTREDOC now offers a complete range of services and solutions for the monitoring of strategic, technological and competitive information. CENTREDOC is also a leader in the research of patent, technical and business intelligence, and offers consulting expertise in the implementation of monitoring solutions.

AI-SDV 2022: New Product Introductions: CENTREDOC

Dr. Haxel Consult

AI-SDV 2022: Possibilities and limitations of AI-boosted multi-categorization...

Dr. Haxel Consult

What if there was a platform where literature, conference abstracts, patents, clinical trials, news, grants and other sources were fully integrated? What if the data would be harmonized, enriched with standardized concepts and ready for analysis? After building our patent analytics platform we didn’t stop dreaming and built our big data analytics platform by semantically integrating text-rich, scientific sources. In my presentation I will talk about what we built and why we built it. And, of course, I will also address the challenges and hurdles along the way. Was it worth it and what comes next? Let’s talk about it!

AI-SDV 2022: Big data analytics platform at Bayer – Turning bits into insight...

Dr. Haxel Consult

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