- From: Paola Di Maio <paola.dimaio@gmail.com>
- Date: Wed, 8 Aug 2018 13:21:57 +0100
- To: public-aikr@w3.org
- Message-ID: <CAMXe=Sqc938hsEuzCoiLf-RnOPBh5NFmiiR55Y3bmkkzR+GFJg@mail.gmail.com>
of interest? ---------- Forwarded message ---------- From: Martynas Jusevičius <martynas@atomgraph.com> Date: Sat, Aug 4, 2018 at 3:06 PM Subject: Re: Semantic web vs big data / ML To: Phillip Rhodes <motley.crue.fan@gmail.com> Cc: Michael F Uschold <uschold@gmail.com>, John Leonard < john.leonard@incisivemedia.com>, "semantic-web@w3.org" <semantic-web@w3.org> This might be of interest to you: https://developer.amazon.com/blogs/alexa/post/29f92b4d- 1369-4d22-8494-7c4cc57650a3/amazon-scientists-to-present- more-sophisticated-semantic-representation-language-for-alexa Alexa Meaning Representation Language is using RDF ontologies. That is mentioned in the PDF article - link in the bottom of the post. On Sat, 4 Aug 2018 at 02.19, Phillip Rhodes <motley.crue.fan@gmail.com> wrote: > There is, indeed, an entire field - and body of research - on > "ontology learning". See, for ref: > > https://en.wikipedia.org/wiki/Ontology_learning > > https://pdfs.semanticscholar.org/8198/9605fba59a415a28603ce709566cc6 > ebc45c.pdf > > https://arxiv.org/pdf/1311.1764.pdf > > etc... > > > Phil > > This message optimized for indexing by NSA PRISM > > > On Fri, Aug 3, 2018 at 6:57 PM, Michael F Uschold <uschold@gmail.com> > wrote: > > This is a very good question. I agree with other responses that ML and > the > > Semantic Web technologies are not in competition, they do very different > > things. The question is whether and how they can work together in > concert. > > ML is used in a lot of NLP which is, in turn, used to extract triples > from > > text. The state of the art here is improving all the time, but it is > still > > not that great. A common approach is for a NLP engine to take as input > both > > an ontology and a text document and to extract triples using the classes > and > > properties in the ontology. This works best if the ontology has a lot of > > text descriptions of the classes and properties. I'm not sure how much > these > > triple-extractors make use of the ontology axioms, probably they use the > > class hierarchy, and property domains and ranges. > > > > Another interesting possibility, which I have not seen much written is > using > > ontology vocabulary to express the features that are learned. I'm not > an > > ML person, but in ML they talk about models, which to some extent > describe > > the kinds of things in the subject area and their attributes/features. > > Probably someone has looked into this. > > > > Probably the most common use of ML is to put things into pre-determined > > categories. But its just statistics. There is no human-grokkable way to > > explain why something goes into one category vs. another. It would be > nice > > if there was a way to do that, in terms of an ontology classes and > > properties. Don't know if that is being done. > > > > Another possible link up is where ML is used to do automatic creation of > > categories. Humans can look at the categories and give them meaningful > > names, but to the computer they are just the result of statistics, they > have > > no meaning. It could be that meaning of these categories could be > inferred > > and matched against an ontology. General topics would probably start with > > the DBpedia ontology. > > > > Way back in 2005 there was a Dagstuhl workshop on ML and the Semantic > Web; > > but there is not a lot of documentation on that event. > > > > Michael > > > > > > > > > > > > > > On Fri, Aug 3, 2018 at 4:30 AM, John Leonard > > <john.leonard@incisivemedia.com> wrote: > >> > >> Can someone please fill me in on the latest state of play between the > >> symantec web and using machine learning techniques with massive > unstructured > >> datasets to derive probablistic links between data items. Are the two > >> techniques in competition? Are they compatible? Or is it more a case of > >> horses for courses? I refer to this 2009 paper > >> https://static.googleusercontent.com/media/ > research.google.com/en//pubs/archive/35179.pdf > >> The Unreasonable Effectiveness of Data by Norvig et al. > >> Thanks for any pointers > >> > >> > > > > > > > > -- > > > > Michael Uschold > > Senior Ontology Consultant, Semantic Arts > > http://www.semanticarts.com > > LinkedIn: www.linkedin.com/in/michaeluschold > > Skype, Twitter: UscholdM > > > > > > > >
Received on Wednesday, 8 August 2018 12:22:22 UTC