The following are some Semantic Marketing Resources that may help people learn more about the Semantic Web.
Enables searchers to search for sites that use the Data Set Schema.
Google Dataset Search: Building a search engine for datasets in an open Web ecosystem (pdf)
by Natasha Noy, Matthew Burgess, Dan Brickley
Information about building Google’s Dataset Search along with lessons learned while doing so.
Entity Oriented Search
by Krisztian Balrog
An Open Access (free) book, about State of the Art Entity Search. It’s very detailed and a good starting point to learn more about the role of entities in Today’s Search Engines.
The Semantic Web
by Tim Berners-Lee, James Hendler, and Ora Lassila
An effort to help computers better understand content and data on the Web, and enable it to be shared widely and quickly. This is one of the first and one of the most well-known papers about the Semantic Web, as the inventor behind the Web reimagined it, so that the web could be treated as a large and very rich database.
by R. Guha (IBM Research), Rob McCool (Knowledge Systems Lab), and Eric Miller (W3C/MIT)
A look at some of the early challenges on the Semantic Web, differing from crawling the Web of pages, to collect information from the Web of Data. This includes a look at Documents vs Real World Objects, Human vs Machine Readable Information, and the Relation between the HTML & Semantic Web.
A description of an Ontology being used by Google that extracts attributes from a query stream, and then “uses the best extractions to seed attribute extraction from text.” This approach crowdsources information about what people want to learn to help build knowledge that people need and want to see.
As their subtitle says, “…or how to link data and schemas across the web.”
Interesting discussions and papers about question-answering on the Web.
A free HTML version of a book about the Web of data, and how that data might be linked together in a number of different places, and how that can help someone whom may want or need that data.
Wikidata: A Free Collaborative Knowledge Base –
BY Denny Vrandeci Ë‡ C. and Marcus Krotzsch
A little about the history and Purpose behind Wikidata.
The Structured Search Engine
By Andrew Hogue
The Search Engineer who led the Annotation framework team at Google, responsible for the Browseable Fact Repository (A precursor to the Knowledge Graph) and who led the acquisition of Meta Web and Freebase at Google.
SemTag and Seeker: Bootstrapping the Semantic Web via Automated Semantic Annotation
by: Stephen Dill, Nadav Eiron, David Gibson, Daniel Gruhl, R. Guha, Anant Jhingran, Tapas Kanungo, Sridhar Rajagopalan, Andrew Tomkins, John A. Tomlin, and Jason Y. Zien
An IBM Research project that when published in 2003 was the largest scale semantic tagging effort at the time.
Microsoft Concept Graph for Short Text Understanding
Based upon a Microsoft Research project named Probase, which was a very large concept graph, which was reclaimed and returned to.
Bing Entity Search API
This may or may not be related to the Microsoft Concept Graph, but may include local entities that have been registered with Bing Places for Business.
Google Knowledge Graph API Search Explored
Enter a query term to see if Google believes it is an entity, or if Google associates multiple entities with that query term. The higher the “result score” for a particular entity, the more confidence Google will have in associating a particular term with a specific entity.
Google’s Experimental Table Search
Developed during Google’s Webtables Project to learn more about Semantics while looking at tables of Data on the Web.
WebTables: Exploring the Power of Tables on the Web – Google set out to learn about Semantics found on the Web from labels and associated text related to data in tables on webpages. The Webtables Project is worth learning about and reading about in more depth, and there have been some follow-up papers that tell us more about the project.
Ten Years of WebTables
by Michael Cafarella, Alon Halevy, Hongrae Lee, Jayant Madhavan, Cong Yu, Daisy Zhe Wang and Eugene Wu
The WebTables project started in 2008, and this is a 10 year review of the project, attempting to see what lessons were learned from it, and what it might lead to.
Recovering Semantics of Tables on the Web – One of the followups to the orginal Webtables Project.
Applying WebTables in Practice – This paper tells us about some of the lessons learned by people at Google during the Webtables project, and is a good followup to previous papers about that project.
Knowledge Base Completion via Search-Based Question Answering – a 2014 Google blog post which tells us about efforts to update Google’s knowledge graph. It is an interesting evolution of the knowledge graph into a more Web scalable approach.
Introduction to Structured Data | Google Developers – Where Google introduces us to the use of Structured Data on the pages of our sites. This is where Google tells us that the form of Structured data that they recommend in JSON-LD. This is recommended reading.
Schema.org – A helpful effort from Google, Microsoft, Yahoo, and later Yandex about the use of structured data on the pages of our sites, including examples, and more about Schema, including information about the extension of Schema, and a blog about Schema which tells us about updates to it. Since this is an area of SEO that may be updated, it is worth keeping an eye upon it.
Updated April 24, 2019