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Taking semantic search to full text [Webinar]
Logo - CCC

When engaging in semantic search, many researchers opt for the use of article abstracts over full-text articles as they are easily accessible via biomedical databases like MEDLINE and are in XML, a format easily read by computers. While article abstracts yield some information, there are limitations to what can be discovered through that process.

During this webinar hear from Lee Harland, SciBite’s CSO and Founder and Mike Iarrobino, CCC’s Product Manager as they look at the content challenges facing R&D teams in the life sciences, the benefits of semantic enrichment of full text content, and how the integrated CCC and SciBite solution can help improve the results of semantic enrichment initiatives, reduce cost and simplify copyright compliance.

Enterprise search partners

We partner with leading enterprise search platforms to enhance real-time big data analytics for pharma and biotech companies. Semantic search capabilities improve the accuracy of search results allowing companies to make data-informed decisions. Find out more about how SciBite’s solutions can help unlock the potential of the R&D data in your business.

Enterprise search partners

Sam Shelton
Director of Alliances, SciBite

Sam leads partnerships and alliances at SciBite, working collaboratively with existing partners and developing new partnerships aligned to SciBite’s strategic goals. He has a strong technical background in the life sciences, with a PhD in Protein Biochemistry from the University of Nottingham and post-doctoral training in bioinformatics within the department of Neurosurgery at the University of California San Francisco.

Prior to Joining SciBite he held technical sales and commercial roles at Carl Zeiss and most recently led business development at Repositive, building relationships with contract research organisations, biotech’s and pharma companies, facilitating data exchange and search across multiomic datasets. He has a good grasp of the challenges of dealing with unstructured scientific data, and collaboratively developing practical solutions to overcome these.

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