can anyone tell me what commonalities and diffrences are between an ontology on the semantic web and a database on the syntactic web?
By going to answers.semanticweb.com you could likely get a thoughtful and descriptive comparison of the two. Since I'm short on time I'll just give you the resources where you can dig in further. See Wikipedia for Syntactic Web and for Semantic Web. See also:
Executive’s Quick Start Guide to Web 3.0 and the Semantic Web
Linked Data: The Story so Far
RDF Primer
RDFa Primer
Related
I am interested in statistical machine translation. Can anyone suggest where can I find more information about state-of-the-art implementations like Google Translate, Microsoft Translate?
I would like to know about the following stuff:
1) The size of training data for different languages.
2) The quality of the translations for different languages.
and any other interesting point about engine implementation.
If you want to have more details about the state of the art, you should have a look on this book: http://www.statmt.org/book/
It is probably a little outdated but it interesting.
The famous tool in MT is Moses: http://statmt.org/moses/
You'll find an overview of this tool, and you can try a tutorial if you're brave.
With these documentation you'll have a more detailed comprehension of the task.
Although i have a little bit of experience in developing dynamic websites using ASP technologies, but I am new to semantic web programming, and i intend to implement a website based on semantic web technology.I would like to develop a search engine, where a web user can query for keywords from the backend RDF triple store.I want to implement the website using Java and JSP.I have following questions:
I am currently studying Jena framework and SPARQL to start with,but
i am not sure what other technologies i need to study in order to
implement the website.
What is the difference between RDF and OWL, I have gone through a
lot of web resources but i am still confused.As per my understanding
RDF and OWL both define relationship between concepts but OWL is
more rich in terms of defining relations.
What is meant by different OWL Vocabularies like FOAF, SIOC etc.Why
do we need these vocabularies?
What exactly is the purpose of Virtuso Open Link
Software(http://ods.openlinksw.com/dataspace/dav/wiki/Main/VirtJenaProvider)
Any help would be highly appreciated.
Thanks!
I would definitely like to be kept up to date of your progress. I'm not experienced with java or jsp. I wonder if this could be done in php? I know that some work has been done in python on this kind of thing.
There are some extensions to drupal that work with these semantic web technologies and Semantic Media Wiki is good too.
Check out this and the related links at the bottom. The difference between microformats and vocabularies can be difficult to understand but I think there is a difference, say between a vocabulary like FOAF and a microformat like hCard, hCalendar or hResume. Oh, the link:
http://en.wikipedia.org/wiki/FOAF_(software)
Anyway these related terms are included.
Thanks,
Bruce
http://futurewavedesigns.com
Re: your first question - why do you want to use RDF to implement a keyword search? Keyword search isn't semantic, and there are many established frameworks and APIs for keyword search, such as Lucene.
Re: your second question, comparing RDF and OWL is comparing apples and oranges. RDF is basically for declaring data, but OWL is a layer on top of RDF that is for declaring ontologies (schemas). A more meaningful comparison would be between RDFS (RDF Schema) and OWL, which both address the ontology layer.
Example:
In RDF you might state that John Smith is a Person who hasAge "42" and is marriedTo Jill Smith.
In RDFS or OWL you would declare that Person is a class, hasAge is a property (with domain of Person and range of xsd:integer) and marriedTo is a property (with domain and range of Person).
In OWL you can also declare that marriedTo is a symmetric property (if A is marriedTo B, then B must be marriedTo A). RDF isn't this powerful, so you can't make this particular statement, so can't make inferences about symmetric properties etc.
I'm looking for code or a product or a service to do semantic analysis of text (sentences and or paragraphs) to categorize the text by general topic, e.g.
Finance
Entertainment
Technology
Business
Art
etc...
If you have a bunch of examples that have already been categorised, you can use these to train a classifier.
This is a very simple document classfication problem, and any suite of machine learning tools will have the algorithms and tutorials for this. For instance, check out weka: http://www.cs.waikato.ac.nz/ml/weka/
or rapidminer: http://rapid-i.com/content/blogcategory/38/69/
If your needs are limited, and you just want a simple API, you cannot go wrong with this Naive Bayes library: https://ci-bayes.dev.java.net/
Good luck!
If you want to evaluate a commercial service API, check out the VIKI engine APIs:
http://www.softwareevolution.it/en/products/viki-core-api.html
It is an easy to use Json service api with specific semantic features.
Would this be of any help to you?
http://en.wikipedia.org/wiki/Document_classification
It's not a finished product or service, neither code, but it describes the various algorithms that can be used for semantic analysis. Googling on a bit further, I believe that it's not really out of the laboratory yet. People are experimenting with KNN algorithms mostly, resulting in cool stuff, but not really what you need:
http://www.ebi.ac.uk/webservices/whatizit/info.jsf
But if there is some software that will do what you ask, it would be in this list:
http://www.kdnuggets.com/software/text.html
For example the LPU program, it seems to be able to learn if you feed it enough teaching documents.
http://www.cs.uic.edu/~liub/LPU/LPU-download.html
If you're into Python/interpreted languages, check out the excellent NLTK framework at nltk.org. It has an excellent how to page and a recently published O'Reilly book.
If you're into Java and/or require a more mature but harder to grasp framework, try GATE instead.
Core principles and tenets for designing a system. is this really web 3.0?
The core principles would include understanding of RDF, RDFS, OWL and
how arbitrary knowledge can be represented using these specs.
Understanding of what reasoners can do with semantic data is essential.
Then comes the idea of intelligent agents.
Then comes understanding of why this is all needed and why it was designed that way.
This would give you the clue about how promising (or not) is this technology.
For the software architect it would be good to know how OWL data can be efficiently stored(in RDBMS or in any other way for example).
As for myself I find this interesting but in reality it is yet very far from the
point where average users can benefit from it on the regular Web.
I am building an ontology-processing tool and need lots of examples of various owl ontologies, as people are building and using them in the real world. I'm not talking about foundational ontologies such as Cyc, I'm talking about smaller, domain-specific ones.
There's no definitive collection afaik, but these links all have useful collections of OWL and RDFS ontologies:
schemaweb.info
vocab.org
owlseek
linking open data constellation
RDF schema registry (rather old now)
In addition, there are some general-purpose RDF/RDFS/OWL search engines you may find helpful:
sindice
swoogle
Ian
My go-to site for this probably didn't exist at the time of the question. For latecomers like me:
Linked Open Vocabularies
I wish I'd found it much sooner!
It's well-groomed, maintained, has all the most-popular ontologies, and has a good search engine. However, it doesn't include some specialized collections, most notably, (most of?) the stuff in OBO Foundry.
Thanks! A couple more I found:
OntoSelect - browsable ontology repository
Protege Ontology Library
CO-ODE Ontologies
Within the life-science domain, the publically abvailable ontologies can be found listed on the OBO Foundry site. These ontologies can be queried via the ontology lookup service or the NCBO's Bioportal, which also contains additional resources.
One more concept search tool: falcons
There is also one good web engine for searching for ontologies. It is called Watson Semantic Web Search and you can try it here.