Details of the second lab: rule system - Redigeerimiste ajalugu

Tammet: /* What will you have to do */

2010-03-23T01:30:15Z

What will you have to do

←Vanem redaktsioon		Redaktsioon: 23. märts 2010, kell 03:30
10. rida:		10. rida:
	* Find rdfa pages with touristically interesting objects: it should contain some relevant info about these objects.		* Find rdfa pages with touristically interesting objects: it should contain some relevant info about these objects.
	** The recommended site is http://dbpedia.org/snorql/		** The recommended site is http://dbpedia.org/snorql/
	** Try query		** Try query (use Results: XML selection from the box below the query window!)
	SELECT ?x WHERE {		SELECT ?x WHERE {
	?x dbpedia-owl:location <http://dbpedia.org/resource/Berlin>.		?x dbpedia-owl:location <http://dbpedia.org/resource/Berlin>.
16. rida:		16. rida:

	** Try similar queries for other cities (London etc)		** Try similar queries for other cities (London etc)
	** Try a more limited query		** Try a more limited query (use Results: XML selection from the box below the query window!)
	SELECT ?x ?p ?v WHERE {		SELECT ?x ?p ?v WHERE {
	?x dbpedia-owl:location <http://dbpedia.org/resource/Berlin>.		?x dbpedia-owl:location <http://dbpedia.org/resource/Berlin>.
23. rida:		23. rida:
	ORDER BY ?x		ORDER BY ?x

	** Your program will have to read all the links in the result listing, scanning the corresponding pages for rdfa (example: http://dbpedia.org/~~snorql/?describe=http%3A//dbpedia.org/resource~~/Palace_of_the_Republic)		** Your program will have to read all the links in the result listing, scanning the corresponding pages for rdfa (example: http://dbpedia.org/page/Palace_of_the_Republic )
	** Your program should be able to work with several cities		** Your program should be able to work with several cities
	* Look at these rdfa pages and invent/create sensible small rule files in the Otter syntax for deriving tourist interest data from physically present rdfa data.		* Look at these rdfa pages and invent/create sensible small rule files in the Otter syntax for deriving tourist interest data from physically present rdfa data.

Tammet: /* What will you have to do */

2010-03-23T01:27:16Z

What will you have to do

←Vanem redaktsioon		Redaktsioon: 23. märts 2010, kell 03:27
14. rida:		14. rida:
	?x dbpedia-owl:location <http://dbpedia.org/resource/Berlin>.		?x dbpedia-owl:location <http://dbpedia.org/resource/Berlin>.
	}		}

	** Try similar queries for other cities (London etc)		** Try similar queries for other cities (London etc)
	** Try a more limited query		** Try a more limited query
21. rida:		22. rida:
	}		}
	ORDER BY ?x		ORDER BY ?x

	** Your program will have to read all the links in the result listing, scanning the corresponding pages for rdfa (example: http://dbpedia.org/snorql/?describe=http%3A//dbpedia.org/resource/Palace_of_the_Republic)		** Your program will have to read all the links in the result listing, scanning the corresponding pages for rdfa (example: http://dbpedia.org/snorql/?describe=http%3A//dbpedia.org/resource/Palace_of_the_Republic)
	** Your program should be able to work with several cities		** Your program should be able to work with several cities

Tammet: /* What will you have to do */

2010-03-23T01:27:01Z

What will you have to do

←Vanem redaktsioon		Redaktsioon: 23. märts 2010, kell 03:27
8. rida:		8. rida:
	Concretely, you will have:		Concretely, you will have:

	* Find rdfa pages with touristically interesting objects: it should contain some relevant info about these objects. ** The recommended site is http://dbpedia.org/snorql/		* Find rdfa pages with touristically interesting objects: it should contain some relevant info about these objects.
			** The recommended site is http://dbpedia.org/snorql/
	** Try query		** Try query
	SELECT ?x WHERE {		SELECT ?x WHERE {

Tammet: /* What will you have to do */

2010-03-23T01:26:37Z

What will you have to do

@@ 8. rida: / 8. rida: @@
 Concretely, you will have:
-* Find rdfa pages with touristically interesting objects: it should contain some relevant info about these objects
+* Find rdfa pages with touristically interesting objects: it should contain some relevant info about these objects. ** The recommended site is http://dbpedia.org/snorql/
 * Look at these rdfa pages and invent/create sensible small rule files in the Otter syntax for deriving tourist interest data from physically present rdfa data.
 * Add example data about interests of a concrete tourist to the file.

Tammet – 22. märts 2010, kell 15:57

2010-03-22T15:57:19Z

←Vanem redaktsioon		Redaktsioon: 22. märts 2010, kell 17:57
8. rida:		8. rida:
	Concretely, you will have:		Concretely, you will have:

	* Look at ~~your~~ rdfa pages and invent/create sensible small rule files in the Otter syntax for deriving ~~new~~ data from physically present rdfa data.		* Find rdfa pages with touristically interesting objects: it should contain some relevant info about these objects
	** It may happen that the rdfa pages from the first lab do not contain really suitable/interesting data ~~for this. In that case, create new pages.~~		* Look at these rdfa pages and invent/create sensible small rule files in the Otter syntax for deriving tourist interest data from physically present rdfa data.
	** The rdfa pages should indicate (by having a ~~corresponding link in~~ the ~~rdfa data) which rule set should be used. You should have at least two different rdfa pages and two different rulesets, one for each page.~~		* Add example data about interests of a concrete tourist to the file.
	** The rule file ~~should be such that no contradiction arises and the set of derived facts is still maintainable (not millions of new facts)~~.		* Write a program which takes your first lab output, you rule/data file and builds a new Otter syntax file containing both rules and the data obtained from the rdfa page.
	* Write a program which takes your first lab output, ~~finds an indicated~~ rule file and builds a new Otter syntax file containing both rules and the data obtained from the rdfa page.
	* Then let the same program call Otter with the newly built file and send the result to a result file.		* Then let the same program call Otter with the newly built file and send the result to a result file.
	* Write a program which takes the output file, parses out the derived facts ~~(fact has just one atom~~ and ~~no variables) and adds~~ these to ~~the original~~ rdfa~~-parsed dataset~~.		* Write a program which takes the output file, parses out the derived facts saying interest and stores these to either csv or rdfa format file.
	* Finally print out the ~~extended dataset: the original facts and newly derived facts from this dataset.~~		* Finally print out the file.
	* Create an addition to the program which answers the posed query: true/false or finds a concrete necessary value (or values). Use otter atom like person(X) or forall person(X) or similar (choose a suitable one yourself) as a query input.

	You may write just one program for all these tasks or several different. In the latter case you will also have to write a "master" program (as a shell script or bat file, for example) calling these subprograms.		You may write just one program for all these tasks or several different. In the latter case you will also have to write a "master" program (as a shell script or bat file, for example) calling these subprograms.

	The final resulting program should take a page url or file name as a single input and produce a list of ~~all found and~~ derived facts as output.		The final resulting program should take a page url or a file name as a single input and produce a list of relevant derived facts as output.

	== Example data/rule set ==		== Example data/rule set ==

Tammet – 22. märts 2010, kell 15:49

2010-03-22T15:49:04Z

←Vanem redaktsioon		Redaktsioon: 22. märts 2010, kell 17:49
21. rida:		21. rida:

	The final resulting program should take a page url or file name as a single input and produce a list of all found and derived facts as output.		The final resulting program should take a page url or file name as a single input and produce a list of all found and derived facts as output.

			== Example data/rule set ==

			This data/rule set is just a basic example: you should extend it significantly and make it correspond/match real tourism object data.

			<pre>
			set(hyper_res).
			%set(binary_res).
			set(factor).
			set(print_kept).
			%set(prolog_style_variables).

			formula_list(sos).

			% --- city facts ----

			fact(rdf_type,tallinn_Bogapott,tourism_cafe,100).
			fact(rdf_type,tallinn_vonkrahl,tourism_pub,100).

			fact(tourism_pop,tallinn_Bogapott,50,100).
			fact(tourism_pop,tallinn_vonkrahl,90,100).

			fact(rdf_type,tallinn_oleviste,tourism_church,100).
			fact(rdf_type,tallinn_vabaduserist,tourism_memorial,100).

			fact(rdf_type,tallinn_xcafe,tourism_cafe,70).

			% ---- city rules ----

			all X all U
			(fact(rdf_type,X,tourism_cafe,U) &
			$GT($DIV($PROD(U,60),100),50)
			->
			fact(rdf_type,X,tourism_drinkinghole,
			$DIV($PROD(U,60),100))).

			all X all U
			(fact(rdf_type,X,tourism_pub,U)
			->
			fact(rdf_type,X,tourism_drinkinghole,U)).

			all X all U
			(fact(rdf_type,X,tourism_church,U)
			->
			fact(rdf_type,X,tourism_architecture,U)).

			all X all U
			(fact(rdf_type,X,tourism_memorial,U) &
			$GT($DIV($PROD(U,80),100),50)
			->
			fact(rdf_type,X,tourism_architecture,
			$DIV($PROD(U,80),100))).

			% ---- interest application rules ------

			% with popularity info

			all P all X all Y all U all V all W all M
			(fact(interest,P,Y,U) &
			fact(rdf_type,X,Y,V) &
			fact(tourism_pop,X,W,M)
			->
			fact(interest,P,X, $DIV($PROD(W,$DIV($PROD(U,V),100)),100)) ).

			% without popularity info

			all P all X all Y all U all V all W all M
			(fact(interest,P,Y,U) &
			fact(rdf_type,X,Y,V)
			->
			fact(interest,P,X, $DIV($PROD(90,$DIV($PROD(U,V),100)),100)) ).


			% ----------- person description ------

			fact(interest,p1,tourism_architecture,80).
			fact(interest,p1,tourism_drinkinghole,60).

			% --- want to get something like this ---

			%** KEPT (pick-wt=5): 20 [hyper,13,15,18,demod] fact(interest,p1,tallinn_Bogapott,32).
			%** KEPT (pick-wt=5): 21 [hyper,13,15,16,demod] fact(interest,p1,tallinn_vonkrahl,54).
			%** KEPT (pick-wt=5): 22 [hyper,13,14,19,demod] fact(interest,p1,tallinn_vabaduserist,57).
			%** KEPT (pick-wt=5): 23 [hyper,13,14,17,demod] fact(interest,p1,tallinn_oleviste,72).


			end_of_list.
			</pre>


	== Suggestions and links ==		== Suggestions and links ==

Tammet – 22. märts 2010, kell 15:38

2010-03-22T15:38:35Z

←Vanem redaktsioon		Redaktsioon: 22. märts 2010, kell 17:38
1. rida:		1. rida:
	Main goal of the lab: ~~extending the dataset obtained~~ from rdfa ~~by automatically derived context-based information~~.		Main goal of the lab: write a ruleset for tourism objects and use Otter or Prover9 to derive a list of recommended tourism objects: each object has
			an associated interest number. The tourism object information should be read from rdfa.

	The lab will build upon your first rdfa lab.		The lab will build upon your first rdfa lab.

Tammet: /* What will you have to do */

2009-03-27T11:13:42Z

What will you have to do

←Vanem redaktsioon		Redaktsioon: 27. märts 2009, kell 13:13
15. rida:		15. rida:
	* Write a program which takes the output file, parses out the derived facts (fact has just one atom and no variables) and adds these to the original rdfa-parsed dataset.		* Write a program which takes the output file, parses out the derived facts (fact has just one atom and no variables) and adds these to the original rdfa-parsed dataset.
	* Finally print out the extended dataset: the original facts and newly derived facts from this dataset.		* Finally print out the extended dataset: the original facts and newly derived facts from this dataset.
	* Create ~~and~~ addition to the program which answers the posed query: true/false or finds a concrete necessary value (or values). Use otter atom like person(X) or forall person(X) or similar (choose a suitable one yourself) as a query input.		* Create an addition to the program which answers the posed query: true/false or finds a concrete necessary value (or values). Use otter atom like person(X) or forall person(X) or similar (choose a suitable one yourself) as a query input.

	You may write just one program for all these tasks or several different. In the latter case you will also have to write a "master" program (as a shell script or bat file, for example) calling these subprograms.		You may write just one program for all these tasks or several different. In the latter case you will also have to write a "master" program (as a shell script or bat file, for example) calling these subprograms.

Tammet: /* What will you have to do */

2009-03-27T11:13:35Z

What will you have to do

←Vanem redaktsioon		Redaktsioon: 27. märts 2009, kell 13:13
15. rida:		15. rida:
	* Write a program which takes the output file, parses out the derived facts (fact has just one atom and no variables) and adds these to the original rdfa-parsed dataset.		* Write a program which takes the output file, parses out the derived facts (fact has just one atom and no variables) and adds these to the original rdfa-parsed dataset.
	* Finally print out the extended dataset: the original facts and newly derived facts from this dataset.		* Finally print out the extended dataset: the original facts and newly derived facts from this dataset.
			* Create and addition to the program which answers the posed query: true/false or finds a concrete necessary value (or values). Use otter atom like person(X) or forall person(X) or similar (choose a suitable one yourself) as a query input.

	You may write just one program for all these tasks or several different. In the latter case you will also have to write a "master" program (as a shell script or bat file, for example) calling these subprograms.		You may write just one program for all these tasks or several different. In the latter case you will also have to write a "master" program (as a shell script or bat file, for example) calling these subprograms.

Tammet: /* Suggestions and links */

2009-03-20T08:20:37Z

Suggestions and links

@@ 28. rida: / 28. rida: @@
 As said, probably the simplest way to create the required system is to write several small programs/scripts for subtasks and then write a master shell script or bat file calling all these programs one by one and using their output files as input to following programs.
-How to get the derived facts from the Otter output file? Just look for rows with a string indicating that this is a derived fact (for example, rows with *KEPT*) and cut out the relevant part. Pure string manipulation, in other words.
+How to get the derived facts from the Otter output file? Just look for rows with a string indicating that this is a derived fact (for example, rows with *KEPT*) and cut out the relevant part. Pure string manipulation, in other words. Concrete suggestions for plan9:
 Otter prover: