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The basic information is pretty well summarized here http://www.rdfabout.com/ http://www.rdfabout.com/ Automatically mapping disparate data sets is a pretty har
by keefe 17y ago
The basic information is pretty well summarized here http://www.rdfabout.com/ http://www.rdfabout.com/ Automatically mapping disparate data sets is a pretty hard problem that does not tend to automate well. My current company produces tools for this and you can download a beta here http://www.topquadrant.com/products/TB_Composer.html http://www.topquadrant.com/products/TB_Composer.html The basic technique is to import your datasets (XML files or RDB or whatever) into RDF, then define a master data model in RDF and define a set of sparql construct rules (or SPIN rules, spin is one of TQ's proprietary languages) which says what I see data with structure X in data source A construct structure Y in data source A using the fields of X. The chief scientist at TQ has written a book on how to effectively do modeling with RDF : http://workingontologist.org/ http://workingontologist.org/ There are a number of other books and tools, you can checkout the semantic technologies conference for exhibitors for a full list.
- messel 17y agoThanks I'll check it out. I've been using a simple approach of allowing folks like Zemanta to extract meta tags from content (natural language text), weighting them by confidence levels or reuse and then finding similar combinations/weights. Link by content.
- keefe 17y agoI'm not sure exactly what you mean, are you talking about entity extraction with confidence levels ala Calais? That used to be clearforest before Reuters bought them. I think entity extraction in general is so closely related to natural language quantification that it is one of those generally tough problems. In general, I feel work in this area suffers scalability issues and highly optimized point solutions will do better for a while yet. I guess we'll have to see how Bing ne Powerset does in mainstreaming this whole thing or if it'll be just a bunch of hype like twine.
- messel 17y agoYup, Calais & Zemanta have similar APIs. Input text and get back tags.
- andraz 17y agoIt's much more than tags - in-text exact entities, deep categorization, related news, etc :) The exact disambiguation of mentioned concepts and entities is what is exciting and underused by web developers right now. Andraz Tori, CTO at Zemanta
- messel 17y agoHow best do you think this can be leveraged by folks that are interested in associating commonality within text (clustering by topic)?
- keefe 17y agoI think sense disambiguation is certainly one of the most interesting applications of semantic technologies. Here at TQ, the focus tends to be on the exploitation of referential semantics and structured data to establish master data models, merge data models and provide a platform for model driven application development and analytics. However, the focus here tends to be more towards corporate IT than mainstream web dev.
- andraz 17y agoIf you need any more help from us (Zemanta), let us know! we know a lot about these problems & solutions, so send us an email at info@zemanta.com Andraz Tori, CTO at Zemanta
- messel 17y agoThanks Andraz, appreciate your presence here and continued support of your business.