Statistical vs "semantic web" approaches to making sense of the Net
There was an interesting conjunction of articles on the ACM "technews" page [http://www.acm.org/technews/current/homepage.html] -- one on "AI" approaches to spam filtering http://www.nwfusion.com/news/tech/2003/0414techupdate.html and the other on the Semantic Web http://www.computerworld.com/news/2003/story/0,11280,80479,00.html. What struck me is that the "AI" approach (I'll guess it makes heavy use of pattern matching and statistical techniques such as Bayesian inference) is working with raw text that the authors are deliberately trying to obfuscate the meaning of to get past "keyword" spam filters, and the Semantic Web approach seems to require explicit, honest markup. Given the "metacrap" argument about semantic metadata (http://www.well.com/~doctorow/metacrap.htm) I suspect that in general the only way we're going to see a "Semantic Web" is for statistical/pattern matching software to create the semantic markup and metadata. That is, if such tools can make useful inferences today about spam that pretends to be something else, they should be very useful in making inferences tomorrow about text written by people who try to say what they mean. This raises a question, for me anyway: If it will take a "better Google than Google" (or perhaps an "Autonomy meets RDF") that uses Baysian or similar statistical techniques to create the markup that the Semantic Web will exploit, what's the point of the semantic markup? Why won't people just use the "intelligent" software directly? Wearing my "XML database guy" hat, I hope that the answer is that it will be much more efficient and programmer-friendly to query databases generated by the 'bots containing markup and metadata to find the information one needs. But I must admit that 5-6 years ago I thought the world would need standardized, widely deployed XML markup before we could get the quality of searches that Google allows today using only raw HTML and PageRank heuristic algorithm. So, anyone care to pick holes in my assumptions, or reasoning? If one does accept the hypothesis that it will take smart software to produce the markup that the Semantic Web will exploit, what *is* the case for believing that it will be ontology-based logical inference engines rather than statistically-based heuristic search engines that people will be using in 5-10 years? Or is this a false dichotomy? Or is the "metacrap" argument wrong, and people really can be persuaded to create honest, accurate, self- aware, etc. metadata and semantic markup? [please note that my employer, and many colleagues at W3C, may have a very different take on this and please don't blame anyone but me for this blather!] --
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