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Janos Haits

Google Knowledge Graph Search Engine (no API skills required) - 0 views

carlhendy.com/knowledge-graph-search

knowledge graph search search engine skills api engine google service tools semantic web3.0 Semantic Web reference searchengine semanticweb web

shared by Janos Haits on 17 Jul 21 - No Cached
  • Janos Haits on 17 Jul 21
     
    "Introduction to the Knowledge Graph API The Google Knowledge Graph API reveals entity information related to a keyword, that Google knows about. This information can be very useful for SEO - discovering related topics and what Google believes is relevant. It can also help when trying to claim/win a Knowledge Graph box on search results. The API requires a high level of technical understanding, so this tool creates a simple public interface, with the ability to export data into spreadsheets."
Janos Haits

Freebase API - Google Developers - 0 views

developers.google.com/freebase

freebase api developers web 3.0 web3.0 semantic web evolution semantic web semanticweb Google service tools web2.0 search

shared by Janos Haits on 13 Mar 13 - No Cached
  • Janos Haits on 13 Mar 13
     
    Build intelligent apps with Freebase data Explore a free, open knowledge graph of 36 million people, places, and things.
Seçkin Anıl Ünlü

Semantic Web Patterns: A Guide to Semantic Technologies - ReadWriteWeb - 0 views

www.readwriteweb.com/...semantic_web_patterns.php

semantic web semantic web web3.0 readwriteweb

shared by Seçkin Anıl Ünlü on 02 Nov 08 - Cached
  • To some, the Semantic Web is the web of data, where information is represented in RDF and OWL. Some people replace RDF with Microformats. Others think that the Semantic Web is about web services, while for many it is about artificial intelligence - computer programs solving complex optimization problems that are out of our reach. And business people always redefine the problem in terms of end user value, saying that whatever it is, it needs to have simple and tangible applications for consumers and enterprises.
  • The bottom-up approach is focused on annotating information in pages, using RDF, so that it is machine readable. The top-down approach is focused on leveraging information in existing web pages, as-is, to derive meaning automatically.
  • Another recent win for the bottom-up approach was the announcement of the Semantify web service from Dapper
  • ...17 more annotations...
  • Similarly, top-down semantic tools are focused on dealing with imperfections in existing information.
  • Within the bottom-up approach to annotation of data, there are several choices for annotation. They are not equally powerful, and in fact each approach is a tradeoff between simplicity and completeness. The most comprehensive approach is RDF - a powerful, graph-based language for declaring things, and attributes and relationships between things.
  • the major benefit of RDF is interoperability and standardization, particularly for enterprises
  • Microformats offer a simpler approach by adding semantics to existing HTML documents using specific CSS styles.
  • The more annotations there are in web pages, the more standards are implemented, and the more discoverable and powerful the information becomes.
  • People simply do not care that a product is built on the Semantic Web, all they are looking for is utility and usefulness.
  • RDF solves a problem of data interoperability and standards.
  • Behind Calais is a powerful natural language processing technology developed by Clear Forest (now owned by Reuters), which relies on algorithms and databases to extract entities out of text. According to Reuters, Calais is extensible, and it is just a matter of time before new entities will be added.
  • Another example is the SemanticHacker API from TextWise, which is offering a one million dollar prize for the best commercial semantic web application developed on top of it.
  • Another semantic API is offered by Dapper - a web service which facilitates the extraction of structure from unstructured HTML pages.
  • The premise that semantical understanding of pages leads to vastly better search has yet to be validated. The two main contenders, Hakia and PowerSet, have made some progress, but not enough. The problem is that Google's algorithm, which is based on statistical analysis, deals just fine with semantic entities like people, cities, and companies.
  • Likely, understanding semantics is helpful but not sufficient to build a better search engine. A combination of semantics, innovative presentation, and memory of who the user is, will be necessary to power the next generation search experience.
  • Contextual navigation does not just improve search, but rather shortcuts it.
  • The common theme among these tools is the recognition of information and the creation of specific micro contexts for the users to interact with that information.
  • Semantic databases are another breed of semantic applications focused on annotating web information to be more structured.
  • Another big player in the semantic databases space is a company called Metaweb, which created Freebase. In its present form, Freebase is just a fancier and more structured version of Wikipedia - with RDF inside and less information in total.
  • With any new technology it is important to define and classify things. The Semantic Web is offering an exciting promise: improved information discoverability, automation of complex searches, and innovative web browsing.
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