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 Ontologies


Sites Relevant to Ontologies and Knowledge Sharing

AITopics Original Links

This ontology is available under the terms of the GNU General Public License. It consists of 21,521 concepts and 37,162 assertions and is part of the ThoughtTreasure artificial intelligence program/tool set, which contains much else besides the ontology.


Artbotics Bringing Art and Robotics Together

AITopics Original Links

An Artbotics with Lego Mindstorms EV3 workshop is being held for educators at UC Irvine in California on Saturday, December 5, 2015. For more information, look here: http://artbotics-uci.eventbrite.com Two Artbotics workshops using the newly developed Arduino curriculum will be held as part of the Middlesex Community College Summer Bridge 2015 program on August 4 and 18, 2015.


The Weeknd's Sex Life Takes The Spotlight Amid Selena Gomez's Dating Rumors; 'Starboy' Singer Reveals Nontraditional Relationship Views

International Business Times

Selena Gomez and rumored boyfriend The Weeknd were certified newsmakers this week. But what's more interesting about this developing story was the latest report highlighting the sex life and nontraditional views on love and marriage of Gomez's new lover. In a recent interview with GQ magazine, the publication that labeled The Weeknd as the "king of sex pop," the 26-year-old "Starboy" singer candidly spoke about his own views on love and marriage. The Grammy Award-winning musician said his popularity does not affect his ego and his dating game, saying most girls want to get involve with him because of his talents instead of appearance. "The reason why they want to [have sex] with me is because of what I do [in the studio]," The Weeknd said in an interview for GQ's February 2017 issue, Us Weekly quoted.


Probabilistic Description Logics for Subjective Uncertainty

Journal of Artificial Intelligence Research

We propose a family of probabilistic description logics (DLs) that are derived in a principled way from Halpern's probabilistic first-order logic. The resulting probabilistic DLs have a two-dimensional semantics similar to temporal DLs and are well-suited for representing subjective probabilities. We carry out a detailed study of reasoning in the new family of logics, concentrating on probabilistic extensions of the DLs ALC and EL, and showing that the complexity ranges from PTime via ExpTime and 2ExpTime to undecidable.


Combining Existential Rules and Transitivity: Next Steps

arXiv.org Artificial Intelligence

We consider existential rules (aka Datalog+) as a formalism for specifying ontologies. In recent years, many classes of existential rules have been exhibited for which conjunctive query (CQ) entailment is decidable. However, most of these classes cannot express transitivity of binary relations, a frequently used modelling construct. In this paper, we address the issue of whether transitivity can be safely combined with decidable classes of existential rules. First, we prove that transitivity is incompatible with one of the simplest decidable classes, namely aGRD (acyclic graph of rule dependencies), which clarifies the landscape of `finite expansion sets' of rules. Second, we show that transitivity can be safely added to linear rules (a subclass of guarded rules, which generalizes the description logic DL-Lite-R) in the case of atomic CQs, and also for general CQs if we place a minor syntactic restriction on the rule set. This is shown by means of a novel query rewriting algorithm that is specially tailored to handle transitivity rules. Third, for the identified decidable cases, we pinpoint the combined and data complexities of query entailment.


The Art of Modeling Names

@machinelearnbot

As you may have noticed, the discussion here talks about names because they usually hide a lot of unstated assumptions, but the reality is this is as relevant to most data structures that you have within enterprise level ontologies. The bigger take-away here is to understand that we're moving into a world where data conversions and data integration dominate, and the kind of thinking that wants to just add a couple of fields to an object to represent a name or other singleton entries (addresses, contact information, emails, companies, stores, the list is pretty much endless) is likely to get you into trouble, especially when data worlds collide. In my next article in this series (check back here for the new link) I'll look at the temporal aspect of change, as well as exploring controlled vocabularies and how they fit into contemporary data modeling.


About: Is Your CEO Blogging?

#artificialintelligence

This page provides a structured representation (serialized as HTML RDFa) of the description of the entity denoted ("referred to") by the hyperlink that anchors the About: Entity Label text at the top. The data is presented here in the form of a collection of Entity- Attribute- Value (EAV) or Subject- Predicate- Object (SPO) relations. In conformance with core Web Architecture, the same description data may also be retrieved in a variety of other negotiable serialization formats, which currently include CSV, HTML Microdata, (X)HTML RDFa, N-Triples, Turtle, N3, RDF/JSON, JSON-LD, RDF/XML, Atom, and CXML. Why is this page important? This page and its neighbors provide 5-Star Linked Data URIs (Web Super Keys) for HTTP-accessible data.


Cognonto Takes On Knowledge-Based Artificial Intelligence - DATAVERSITY

#artificialintelligence

That's the direction taken by startup Cognonto, co-founded by Michael Bergman, a man whose history in the AI, Machine Learning, Semantic technologies, Internet search and data arenas goes back a long way. That includes his additional duties as CEO of Structured Dynamics, birthplace of UMBEL (Upper-level Mapping and Binding Exchange Layer), a knowledge graph and vocabulary for interoperating Web-accessible information, which had its latest update in May. As far as the new Cognonto venture, whose initial fruits are the Cognonto Platform and KBpedia knowledge structure, Bergman says it's been in gestation for about eight years. "The'aha' moment came when we realized how many of the large-scale QA systems were basing their knowledge structure around Wikipedia," Bergman says. "We realized this was a huge storehouse of very useful information, but one that everyone reinvented every time they brought in their own system," from Siri to Viv to IBM Watson and the Google Knowledge Graph.


Cognonto Takes On Knowledge-Based Artificial Intelligence - DATAVERSITY

#artificialintelligence

That's the direction taken by startup Cognonto, co-founded by Michael Bergman, a man whose history in the AI, Machine Learning, Semantic technologies, Internet search and data arenas goes back a long way. That includes his additional duties as CEO of Structured Dynamics, birthplace of UMBEL (Upper-level Mapping and Binding Exchange Layer), a knowledge graph and vocabulary for interoperating Web-accessible information, which had its latest update in May. As far as the new Cognonto venture, whose initial fruits are the Cognonto Platform and KBpedia knowledge structure, Bergman says it's been in gestation for about eight years. "The'aha' moment came when we realized how many of the large-scale QA systems were basing their knowledge structure around Wikipedia," Bergman says. "We realized this was a huge storehouse of very useful information, but one that everyone reinvented every time they brought in their own system," from Siri to Viv to IBM Watson and the Google Knowledge Graph.


Lexical Similarity of Information Type Hypernyms, Meronyms and Synonyms in Privacy Policies

AAAI Conferences

Privacy policies are used to communicate company data practices to consumers and must be accurate and comprehensive. Each policy author is free to use their own nomenclature when describing data practices, which leads to different ways in which similar information types are described across policies. A formal ontology can help policy authors, users and regulators consistently check how data practice descriptions relate to other interpretations of information types. In this paper, we describe an empirical method for manually constructing an information type ontology from privacy policies. The method consists of seven heuristics that explain how to infer hypernym, meronym and synonym relationships from information type phrases, which we discovered using grounded analysis of five privacy policies. The method was evaluated on 50 mobile privacy policies which produced an ontology consisting of 355 unique information type names. Based on the manual results, we describe an automated technique consisting of 14 reusable semantic rules to extract hypernymy, meronymy, and synonymy relations from information type phrases. The technique was evaluated on the manually constructed ontology to yield .95 precision and .51 recall.