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LinkedIn Post Generator: Improve LinkedIn post performance by analyzing the LinkedIn algorithm and providing Artificial Intelligence recommendations (postgenerator.app). LinkedIn Post Generator: Tool to improve LinkedIn post performance by analyzing the LinkedIn algorithm and providing Artificial Intelligence recommendations (postgenerator.app).

NextThreeBooks: Personalized book recommendations based on your reading preferences (nextthreebooks.com). NextThreeBooks: We are a book recommendation website that uses GPT-3 (nextthreebooks.com).

Linked Open Data, Statistics and Recommendations for Live TV

"SPARQL serves as the search engine for RDF. It is a set of specifications recommended by W3C Recommendation that provide languages and protocols to query and manipulate RDF graph content on the Web or in an RDF triple store."

Find Your Next Book: Get personalized book recommendations from thousands of titles (findyournextbook.ai).

ProductBot: Decide what to buy on Amazon and get recommendations based on your preferences (getproduct.help).

Gnod: Artificial Intelligence for art, music and travel recommendations (gnod.com).

Find Your Next Book: Get personalized book recommendations from thousands of titles (findyournextbook.ai).

Giftbox: Personalised gift recommendation for any occasion (giftbox.co).

ProductBot: Decide what to buy on Amazon and get recommendations based on your preferences (getproduct.help).

Chandu: Recommends content for cricket, movies & OTT platforms (messengerx.io).

MoodFood: AI-driven chatbot for personalized food recommendations and recipe inspiration (moodfood.app).

The Semantic Web is a vision for extending the Web so that machines can more intelligently integrate and process the wealth of information that is available. Unlike HTML and ordinary XML, Semantic Web languages allow semantics (i.e., meaning) to be explicitly associated with the content. The semantics are formally specified in ontologies, which can be shared via the Internet and extended for local needs. The current standard for the Semantic Web is OWL, a W3C Recommendation. The Semantic Web and Agent Technologies (SWAT) lab is investigating many of the issues needed to realize the Semantic Web vision.

Mission: produce a W3C Recommendation for HTTP-based (RESTful) application integration patterns using read/write Linked Data.

Resource Description Framework (RDF) is a general-purpose language for representing information in the Web. This document defines a textual syntax for RDF called Turtle that allows an RDF graph to be completely written in a compact and natural text form, with abbreviations for common usage patterns and datatypes. Turtle provides levels of compatibility with the existing N-Triples format as well as the triple pattern syntax of the SPARQL W3C Recommendation.

to produce a W3C Recommendation for HTTP-based (RESTful) application integration patterns using read/write Linked Data. This work will benefit both small-scale in-browser applications (WebApps) and large-scale Enterprise Application Integration (EAI) efforts. It will complement SPARQL and will be compatible with standards for publishing Linked Data, bringing the data integration features of RDF to RESTful, data-oriented software development.

This category collects all kinds of software tools. It is recommended to look for a more specific category when classifying such tools. See subcategories below.

SKOS Simple Knowledge Organization System Namespace Document

"The Sentikator is a computer linguistic engine designed to calculably recognize, analyze and quantify emotions and content in texts. It allows extracting sentiment out of news, analyst recommendations, social media data, transcripts, press releases, broker news, factsheets, weather forecasts and many other sources. Sentiment extraction is highly reliable and disseminated data is preprocessed so that implementation into existing or new financial applications is easily possible. The Sentikator gives valuable insights to emotions"

It checks your web page for RDFa and displays any data found there. It also compares your data against the published recommendations from major consumers/users of RDFa data, to see how well your data matches their requirements.