Posts Tagged ‘Semantic web’
“The semantic web is another way to “represent web content in a form more easily machine-processable and to use intelligent techniques to take advantage of these representations. (…)
In other words, the semantic web is where machines can automatically process the meaning of content along with the ability to make meaningful connections and links among information. It is not about machines being able to understand but being able to process information effectively. (…)
Fong, Candice. Connecting the dots: a semantic web primer. FUMSI, Online, the 3rd of October 2011.
FUMSI has released in July a folio dedicated to the semantic web.
It is a collection of 4 articles, directed by Martin Belam.
The first part is composed with an “historical” article that Silver Oliver wrote in 2008 and where he predicted, for instance, the move from the pull to the push search paradigm, associated with “context-aware” applications. Let’s have a look to our current search environment in databases to see how various facets, semantic refine features, context-based apps, etc. have invaded the search interfaces and to understand how accurate were his predictions in 2008.
The rest of the folio introduces different technologies and standards that will change the Web in next months:
- HTML5, the markup language
- The Linked data “philosophy”
- Microformats to improve your publishing
SciVerse, the latest release of Elsevier which is now used by 15 millions of users worlwide, has released a new application de dedicated to improve the search experience.
HealthMash, by Weblib, utilizes proprietary natural language processing and semantic technology tools and resources in order to find highly relevant, reliable and recent health information from the most trusted sources and facilitate focused user exploration and discovery.
- vertical semantic search (Trusted Health Information, MeSH)
- federated search (Health News, Videos, etc.),
- semantic synthesis with mouse-over contexts for exploration and discovery (Related Concepts, Health Concerns, Tests and Treatments),
- and TABLE OF CONTENTS and TOPIC CLUSTERS for drill down in search results and dynamic query modification.
By explicitly identifying facets of particular interest to users: disorders, signs/symptoms, tests and diagnosis, treatments/procedures, drugs and their side effects, interactions/contraindications, and alternative medicine approaches; the user is presented with the most recent, reliable and comprehensive information on their query/topic.
Find meaningful results in context, not just long lists of documents
Quertle is a free search engine for the biomedical literature, providing linguistic approaches to get much more relevant results, returning documents where the author has stated a relationship between the search terms, not just simply throwing back long lists of documents where the terms have been found scattered throughout.
Currently it provides access to all of PubMed, open access full-text articles from PubMed Central and BioMed Central, FierceMarkets news articles, whitepapers, Toxline, and the NIH RePorter database, and is adding more databases all the time.
Because we find and report to the user the specific facts of interest from those articles (nicely highlighted in context), the searcher has a much better idea of whether the article contains information not in the abstract that is worth buying from the publisher.
Why Quertle is different:
30 seconds to understand what is semantic search in science:
According these chines study, Web 3.0 could help in drug discovering.
Basicaly, the semantic web vision is to create a web of data by
interlinking, mapping and combining disparate data sources based on machine-understandable ontologies.
This data sharing especially could enable scientific networks and efficient retrievable systems.
The semantic web, developed on the web technology, provides a common, open framework capable of harmonizing diversified resources to enable networked and collaborative drug discovery.
Authors surveyed the state of art of utilizing web ontologies and other
semantic web technologies to interlink both data and people to support
integrated drug discovery across domains and multiple disciplines.
Particularly, the survey covers three major application categories including:
- semantic integration and open data linking;
- semantic web service and scientific collaboration and
- semantic data mining and integrative network analysis
Chen, H.a , Xie, G.b. The use of web ontology languages and other semantic web tools in drug discovery. Expert Opinion on Drug Discovery. Volume 5, Issue 5, May 2010, Pages 413-423