Tammet: /* */

2013-01-28T16:36:56Z

Tammet: Uus lehekülg: '

teadmised Code: ITV0060
Link: http://www.lambda.ee/index.php/Teadmiste_otsing,_formaliseerimine_j...'
2013-01-28T16:36:46Z

Uus lehekülg: '<table> <tr> <td> left|teadmised </td> <td> Code: ITV0060 Link: http://www.lambda.ee/index.php/Teadmiste_otsing,_formaliseerimine_j...'

Uus lehekülg
<table>
<tr>
<td>
[[Pilt:Mephistophiles small.gif| left|teadmised]]
</td>
<td>
Code: ITV0060 
Link: http://www.lambda.ee/index.php/Teadmiste_otsing,_formaliseerimine_ja_hoidmine or http://www.lambda.ee/index/itv0060 
Lecturer: Kalle Tomingas, Tanel Tammet 
Contact: kalle.tomingas@gmail.com, 50 40 568 
tammet@staff.ttu.ee, 6203457, TTÜ AK223 
Archives of previous years: [[itv0060 2011 arhiiv|2011]], [[itv0060 20010 arhiiv|2010]], [[itv0060 2009 arhiiv|2009]], [[itv0060 2008 arhiiv|2008]], [[itv0060 2007 arhiiv|2007]], [[itv0060 2006 arhiiv|2006]], [http:/cs.ttu.ee/kursused/wav4130/ older].
</td>
</tr>
</table>

== ==

== Järeleksam 2012 sügis ==

* Järeleksam: 29. august (kolmapäev) kell 9.00-12.00, IT majas ruumis IT-140.

== Exam and results ==

Two times available (choose one):

* 1. June (Friday) at 9.00-12.00, room II-102
* 8. June (Friday) at 9.00-12.00, room II-102

Tulemused 2012 eksamisession:

JT 3
TT 3
RT 5
MS 5
KI 4
RKA 4
RK 5
JK 2
AS 4
NV 5
MM 5

== Time, place, result ==

Semester: spring 
Grading: exam 
Points: 3.5 

Lectures: every Monday 17.45-19.15, room IT-137a 
Practical work: Mondays on odd weeks 19.15-20.00, room IT-137a: 6 feb, 20 feb, 5 mar, 19 mar, 2 apr, 16 apr, 30 apr, 14 may, 21 may.

Practical work will give 40% and exam 60% of points underlying the final grade.

== Practical work ==

There are two labs on the same theme and an optional third lab.

=== First lab ===

The main goal of the first lab is to web-scrape data from the public sources using search engines and simple text analysis/statistics.

Details in [[Teadmised first lab 2012|Teadmised first lab 2012]]. The lab should be completed by March, later presentation will cut the points to half.

=== Second lab ===

The main goal of the second lab is to augment data obtained from the first lab by writing and using probabilistic rules with a rule engine.

Details about second lab will be available on beginning of April. Previous year lab can be seen here: [[Teadmised second lab 2012]]. You may also have a look at the 2011 version of the lab [[Teadmised second lab 2011]].

=== Optional third lab ===

The optional third lab can be done in parallel with the second. It will be a relatively complex lab: successful passing will give additional 20 points, thus the weight of the exam is diminished from 60% to 40% of the overall score.

What to do: use Attempto to create a system such that you can write rules and/or facts and/or queries for the second lab in restricted english. These restricted english sentences have to be automatically converted to the form usable by Otter. It is a good idea to avoid probabilities in these rules, since it would be very hard to encode probabilities using attempto.

See: http://attempto.ifi.uzh.ch/site/ , http://attempto.ifi.uzh.ch/ape/

== Materials to study for the exam ==

Eksamiküsimused:

Väikesed ülesanded: data ja reeglite
esitamine ja kasutamine

Andmebaas nö tüüpilise relatsioonilise
mudelina, key-value ja rdf kujul. Nende esituste
omavahelise teisendamise oskus.

Ülesanne blocks worldist: esita mingi
olukord, mingi reegel ja näita rakendamise
tulemust. Hea oleks aru saada erinevatest
võimalustest

RDF, RDFS ja OWL põhiasjad: väike
ülesanne. Süntaksid ja eridetailid
ei ole olulised.

RDF ja RDFS esitada loogikas
faktide ja reeglitena.

Arusaamine RDFa põhiasjadest, oskus
teha näidet. ??? Kallelt küsida.

Arusaam et mis on mittemonotoonne
loogika ja mis ei ole, mis oleks
viisid esitada vasturääkivaid
teadmisi. Võib olla väike ülesanne
mingite asjade esitamise kohta: näide
ja selgitus. Default loogika ülesanne a la linnud
ja Quaker diamond: panna kirja reeglid
ja viia läbi järeldused ja vbl selgitada
lisaks. Seos CWA, Prolog ja default loogika
vahel võib samuti küsimuse alla tulla.

Arusaam fuzzy ja probabilistic logic erinevustest
ja võimalikest rakenduskohtadest.

Indeksid: arusaam baasindekseerimis-ideedest
ja B+ treest. Ntx ehitada B+ mingi
väikese datahulga jaoks.

=== Declarative and procedural representations ===

Lecture material:
* [[Media:Kr intro.ppt | Intro lecture: declarative and procedural representations]]

=== Databases: meaning and representation of facts ===

* [[Media:Kr_plain_data_db_logic.ppt | relation of plain data in databases to logic & representing complex structures in databases ]]
* [[Media:Kr_rdf_schemalessdb_3.pdf|key/value pairs and rdf, compared to the relational model]]

=== Rules in logic: apps in planning, robotics, ... ===

Lecture material:
* [[Media:Kr_rules1.pdf|Rules and logic: refresher]] and as [[Media:Kr_rules1.ppt|ppt]]

See also:

* [[Media:Geoffreasoningnotes.pdf|Geoff reasoning course notes: just for background, no questions in exam]]
* [http://www.ee.pdx.edu/~mperkows/May4/005.Ch11-planning.ppt planning and blocks world]
* [[blocks world axiom/query examples from lecture]]

=== RDF, RDFS, OWL and conversion to 1st order logic ===

Lecture material:
* [[Media:Kr_rdfs.pdf|RDFS: rdf schema]] and as [[Media:Kr_rdfs.ppt|ppt]]

Understand RDF and RDFS:

* [http://en.wikipedia.org/wiki/Resource_Description_Framework RDF wikipedia]
* [http://www.w3.org/TR/rdf-primer/ w3c RDF primer]

Understand basics of owl:

* [http://en.wikipedia.org/wiki/Web_Ontology_Language OWL wikipedia]
* [http://www.w3.org/TR/owl-guide/ w3c OWL guide]

=== RDFa, reading and using RDF data from web pages ===

Understand main parts:

* [http://en.wikipedia.org/wiki/RDFa wiki intro]
* [[Media:portaalidekoosvoime.ppt]] or as pdf [[Media:portaalidekoosvoime.pdf]]
* [http://www.w3.org/2006/07/SWD/RDFa/primer/ w3c rdfa primer]

=== RDF relation to logic ===

Notes from lecture:
* [[Notes about RDF and OWL: logical meaning]]

Understand a bit of:
* [http://www.w3.org/TR/2003/NOTE-lbase-20031010/ Hayes & Guha Lbase]

=== Semantics of ordinary relational base ===

* [http://cs.ttu.ee/kursused/wav4130/rdftutapp.pdf rdf tutorial addendum for logic and dbases]

=== First order logic in query engines and planning ===

* [[Media:Geoffreasoningnotes.pdf|Geoff reasoning course notes: just for background, no questions in exam]]
* [http://www.ee.pdx.edu/~mperkows/May4/005.Ch11-planning.ppt planning and blocks world]
* [[blocks world axiom/query examples from lecture]]

=== Data extraction ===

Web mining by Nell:
* [http://rtw.ml.cmu.edu/rtw/ Nell]

=== Restricted english jms ===

* [http://attempto.ifi.unizh.ch/site/pubs/papers/phd_kaljurand.pdf Attempto restricted english]

=== Uncertain knowledge logic ===

* [http://plato.stanford.edu/entries/logic-nonmonotonic/ nonmonotonic logic]
* [http://en.wikipedia.org/wiki/Default_logic default logic]
* [http://sc.snu.ac.kr/courses/2008/spring/pg/krr/Lectures/Lecture11/Lec11.ppt Reasoning with Conflicting Knowledge]

=== Indexes ===

Traditional database indexes incl B+ tree:
* [http://www.lambda.ee/index.php/Pilt:IndexNotes04.ppt G. Molina lecture 4]

Bitmap indexes:
* [http://en.wikipedia.org/wiki/Bitmap_index wiki]

Hash indexes:
* [http://en.wikipedia.org/wiki/Hash_table wiki]

Fulltext indexes:
* [http://www.lambda.ee/index.php/Pilt:Fulltext_indexes.ppt good intro and overview]

Term indexes:
Understand basics of discrimination tree trie-type term indexes and path indexes from
* [http://www.lambda.ee/index.php/Pilt:Mccuneindexing.pdf mccune paper]

== Course structure ==

We start with representing and converting facts, continue to rules, first monotonic, then probabilistic and nonmonotonic, then look into search and indexing of complex information, and finally, some learning.

=== Intro and paradigms of knowledge representation ===

Lecture materials:
* [[Media:Kr intro.ppt | Intro lecture: declarative and procedural representations]]
* [http://dl.dropbox.com/u/11794296/roboswarm_saso_2.pdf roboswarm example of combining dec and proc]

For KR, declarative and procedural rep see:
* [http://en.wikipedia.org/wiki/Knowledge_representation Short wiki overview of knowledge representation]
* [http://groups.csail.mit.edu/medg/ftp/psz/k-rep.html Long and philosophical MIT overview of knowledge representation]
* [http://www.cse.buffalo.edu/~rapaport/676/F01/proc.decl.html Pointers to classical papers]
* [http://www.cogarch.org/index.php/Main_Page A Survey of Cognitive and Agent Architectures]
* [ftp://reports.stanford.edu/pub/cstr/reports/cs/tr/76/581/CS-TR-76-581.pdf Classical KRL paper from 1977: Bobrow & Winograd]
Web mining by Nell:
* [http://rtw.ml.cmu.edu/rtw/ Nell]
* [http://www.cs.cmu.edu/~rcwang/ Richard Wang]
* [http://www.boowa.com/ boowa extractor]

=== Databases: meaning and representation of facts ===

Lecture material:


* [[Media:Kr_plain_data_db_logic.ppt | relation of plain data in databases to logic & representing complex structures in databases ]]

* [[Media:Kr_rdf_schemalessdb_3.pdf|key/value pairs and rdf, compared to the relational model]]

See also about databases and logic:

* [http://www.cs.rice.edu/~tlogic/Database/all-lectures.pdf Logic and Database Queries (readable)]
* [http://magenta.ruc.dk/dat_en/research/reports/127.pdf logic in databases workshop (complex stuff)]

See also about RDF and related:

* [http://cs.ttu.ee/kursused/wav4130/rdftutapp.pdf rdf tutorial addendum for logic and dbases]
* [http://en.wikipedia.org/wiki/Resource_Description_Framework RDF wikipedia]
* [http://www.w3.org/TR/rdf-primer/ w3c RDF primer]
* [http://en.wikipedia.org/wiki/RDFa wiki intro]
* [[Media:portaalidekoosvoime.ppt]] or as pdf [[Media:portaalidekoosvoime.pdf]]
* [http://www.w3.org/2006/07/SWD/RDFa/primer/ w3c rdfa primer]
* [http://tripletalk.wordpress.com/2011/01/25/rdfa-deployment-across-the-web/ rdfa and microformats deployment now]
* [http://www.microformats.org microformats: a similar technology]
* [http://www.w3.org/TR/2003/NOTE-lbase-20031010/ Hayes & Guha Lbase]

=== Rules in logic: apps in planning, robotics, ... ===

Lecture material:
* [[Media:Kr_rules1.pdf|Rules and logic: refresher]] and as [[Media:Kr_rules1.ppt|ppt]]

Topics:

* propositional, first order, higher order
* semantics/models
* proofs and deriving new information
* automated reasoning

See also:

* [[Media:Geoffreasoningnotes.pdf|Geoff reasoning course notes: just for background, no questions in exam]]
* [http://www.ee.pdx.edu/~mperkows/May4/005.Ch11-planning.ppt planning and blocks world]
* [[blocks world axiom/query examples from lecture]]

=== Various rule/logic languages ===

Lecture material:
* [[Media:Kr_rdfs.pdf|RDFS: rdf schema]] and as [[Media:Kr_rdfs.ppt|ppt]]
* [[Notes about RDF and OWL: logical meaning]]

Several languages:
* RDFS
* OWL
* KIF
* CL
* ontologies
* wordnet
* cyc
* restricted english systems

See also:
* [http://en.wikipedia.org/wiki/Resource_Description_Framework RDF wikipedia]
* [http://www.w3.org/TR/rdf-primer/ w3c RDF primer]
* [http://en.wikipedia.org/wiki/Web_Ontology_Language OWL wikipedia]
* [http://www.w3.org/TR/owl-guide/ w3c OWL guide]
* [http://cl.tamu.edu/ CL main page],
* [http://attempto.ifi.unizh.ch/site/pubs/papers/phd_kaljurand.pdf Attempto restricted english]

=== Scraping semistructured data ===

* Example for background: http://www.sightsmap.com/

=== Time, context, metainformation ===

=== Probabilistic and nonmonotonic reasoning ===

See also:
* [http://plato.stanford.edu/entries/logic-nonmonotonic/ nonmonotonic logic]
* [http://en.wikipedia.org/wiki/Default_logic default logic]

=== Personalized search and recommendations ===

=== Fast search of facts and rules using indexing ===

* [http://www.lambda.ee/index.php/Pilt:IndexNotes04.ppt G. Molina lecture 4]
* [http://www.lambda.ee/index.php/Pilt:IndexNotes05.ppt G. Molina lecture 5]
* [http://www.lambda.ee/index.php/Pilt:Fulltext_indexes.ppt good intro and overview]
* [http://www.lambda.ee/index.php/Pilt:Mccuneindexing.pdf mccune paper about term indexes]

=== Learning ===

See also:

* [http://www.cs.toronto.edu/~hinton/csc2515/notes/lec1.ppt intro]
* [http://gamma.cs.unc.edu/rob-course/public_html/LEC/MachineLearningMethods.ppt robots/cars]
* [http://www.cs.toronto.edu/~hinton/csc2515/notes/lec4.ppt backpropagation]
* [http://www.cs.toronto.edu/~hinton/csc2515/lectures.html good set of lecture materials]
* [http://www.cs.cmu.edu/~tom/mlbook-chapter-slides.html another good full set of lecture materials]
** sh [http://www.cs.cmu.edu/afs/cs.cmu.edu/project/theo-20/www/mlbook/ch4.pdf neural netw chapter]





[[Category:Kursus]]

Itv0060 2012 arhiiv - Redigeerimiste ajalugu

Tammet: /* */