Hey James, Have you ever seen any market ($$$$$) for this kind of work out there ?? I would think that the rule-based side of it could be very interesting.
Rich Halsey ----- Original Message ----- From: "James Owen" <[EMAIL PROTECTED]> To: <[EMAIL PROTECTED]> Sent: Thursday, February 05, 2004 1:24 PM Subject: RE: JESS: Re: Restricted Language Query/ Natural Language Parsing in Jess > Jason, Rich and Ernest: > > Actually, quite a bit of work has been done in this area. It followed > shortly after all of the speech-pattern-recognition stuff started. A > fellow named Sankar K. Pal started a program named "MyPal" wherein he > would be able to retrieve sense from nonsense typed in from the > keyboard. He gave a "presentation" way back in 1989 at UT Dallas in one > of the M.I.N.D. conferences co-hosted by UT Arlington. > > Dr. Daniel S. Levine and Dr. Alice O'Toole from UTA were the moderators. > They had top name guys from all over the world at the conference. [Gail > Carpenter and Steve Grossberg were the top two names there but the US > Naval Surface Warfare Depart was also well represented.] Dr. Levine is > now in the Department of Psychology at UTA because that was the only > department willing to fund his research. > > Anyway, Dr. Pal co-authored a book with Paul P. Wang. Amazon link is > > http://www.amazon.com/exec/obidos/ASIN/0849394678/inktomi-bkasin-20/ref% > 3Dnosim/102-1084313-6504134 > > I found another book at (of all places) WalMart.com on Pattern > Recognition software. > > http://www.walmart.com/catalog/product.gsp?product_id=1072257&sourceid=1 > 500000000000000040820 > > Some earlier works by Sankar are available from the Indian Statistical > Institute in Calcutta. > > http://www.wspc.com/books/compsci/4755.htm > > but, for some reason, this one is cheaper. Go figure... I guess that a > Microsoft like costs more to put up than a Unix link. :-) > > http://www.wspc.com/books/compsci/4755.html > > Finally, if you act now, you can get one for only $9.95 (or so) on EBay > > http://half.ebay.com/cat/buy/prod.cgi?cpid=805831&domain_id=1856&ad=5398 > 3 > > enjoy. > > SDG > jco > > James C. Owen > Knowledgebased Systems Corporation > Senior Consultant > > > -----Original Message----- > From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] > On Behalf Of Jason Morris > Sent: Thursday, February 05, 2004 10:44 AM > To: [EMAIL PROTECTED] > Subject: RE: JESS: Re: Restricted Language Query/ Natural Language > Parsing in Jess > > Hi Rich , > > Sort of. :-D > > If you look at the article in the link, you'll see how the researchers > approached the problem. Basically, I would like to start a Jess > application > (that follows the Tax Advisor pattern, but isn't a Tax Advisor!) by > allowing > the users to enter a free-text problem statement -- like when you tell > your > doctor "where it hurts". The doctor can then begin to make inferences > about > what type of problem you may have by parsing your input and > pattern-matching > it to syntactically similar, "pre-parsed phrases" that share the > distilled > semantics of the original input (if that makes sense), and then ask more > leading questions to heuristically home-in on the solution. > > As an example, in a typical BNF production, I might have a definition > > <problem_statement>::= <subject><verb><end-mark> so that a > <problems_statement> is composed of a the "non-terminals" > <subject><verb><end-mark> in that order. > > And I might have a vocabulary like > > <subject> -> I | You | We > <verb> -> ran | jumped | cried > <end-mark> -> . | ? | ! > > For all the possible combinations of these non-terminals and terminals > (all > productions), I'd have to construct a rule to deal with that production. > If > I understand the article right, what they did was to map the set of all > the > synonyms of each of the non-terminals to a "key", and after doing this > they > composed phrases of these keys to store the generic semantics of the > input, > thereby collapsing the number of patterns for which they need to store a > meaning. > > I just thought that it was a novel approach instead of parsing the > string by > brute force and trying to process the results with a gazillion rules. > > Hope that clarifies a bit. > > Regards, > > Jason Morris > ------- > Morris Technical Solutions > [EMAIL PROTECTED] > www.morristechnicalsolutions.com > fax/phone: 503.692.1088 > > -----Original Message----- > From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] > Behalf Of Rich Halsey > Sent: Thursday, February 05, 2004 4:06 AM > To: [EMAIL PROTECTED] > Subject: JESS: Re: Restricted Language Query/ Natural Language Parsing > in Jess > > > Hi Jason, > > In trying to reduce the description of your problem, I came up with the > following: > > Use a Natural Language front-end for the user to interact with a > rule-based > Tax Advisor where the rules derive a solution to a query based on data > derived from a free form input. > > Does this sound even close to what you want to do ?? > > Rich Halsey > > ----- Original Message ----- > From: "Jason Morris" <[EMAIL PROTECTED]> > To: "Jess-Users" <[EMAIL PROTECTED]> > Sent: Wednesday, February 04, 2004 7:07 PM > Subject: JESS: Restricted Language Query/ Natural Language Parsing in > Jess > > > > Hi All, > > > > Sorry for the long post, but this is an esoteric question... > > > > I am interested in adapting the Tax Form Advisor (using it almost like > a > OO > > design-pattern) by adding a component that can reason about > information > > drawn from natural-language input as well as using restricted answers > to > > hard-coded questions. To make the parsing problem more tractable, I > began > > thinking of different ways that I could derive meaning from various > input > > strings without coding a huge parsing engine from scratch or writing > > hundreds of extra rules. I read a lot of parsing theory and > experimented > > with various BNF syntaxes, but quickly ran into trouble as the > language > grew > > and the rules became more complex. Since my background is in > mechanical > > engineering, I tried to draw parallels with what I already know. > > > > In fluid mechanics, there is the theory of non-dimensional parameters > > whereby a complex functional equation in m variables and n dimensions > can > be > > reduced to (m-n) dimensionless parameters, which should be > theoretically > > easier to manipulate. I reasoned: why couldn't I attempt to do the > same > > thing with words -- in other words, treat the input string as function > of > > tokens having a certain "dimension" or membership in semantic subsets, > and > > then attempt to "normalize" the string to fit a stored semantic > pattern > that > > would have meaning to Jess. Theoretically, this would significantly > cut > > down the number of rules that I'd have to write to handle various > inputs, > > even ambiguous ones, while letting the user type away to describe the > > initial problem input. > > > > Alas, it seems that my idea was anticipated (see pg.2): > > http://www.amia.org/pubs/symposia/D005310.PDF > > > > However, does anyone have any good suggestions as to how to implement > this > > approach in Jess? > > > > Thanks! > > > > Jason Morris > > -------- > > Morris Technical Solutions > > [EMAIL PROTECTED] > > www.morristechnicalsolutions.com > > fax/phone: 503.692.1088 > > > > -------------------------------------------------------------------- > > To unsubscribe, send the words 'unsubscribe jess-users > [EMAIL PROTECTED]' > > in the BODY of a message to [EMAIL PROTECTED], NOT to the list > > (use your own address!) List problems? 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