Teadmiste otsing, formaliseerimine ja hoidmine: erinevus redaktsioonide vahel

Allikas: Lambda
Mine navigeerimisribale Mine otsikasti
273. rida: 273. rida:
* [http://attempto.ifi.unizh.ch/site/pubs/papers/phd_kaljurand.pdf Attempto restricted english]
* [http://attempto.ifi.unizh.ch/site/pubs/papers/phd_kaljurand.pdf Attempto restricted english]


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== 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_draft.ppt|logic and databases intro draft]] -->
* [[Media:Kr_plain_data_db_logic.ppt | relation of plain data in databases to logic & representing complex structures in databases ]]
<!-- * [[Media:Kr_prop_val_pairs.ppt|property/value pairs]] -->
* [[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]
-->


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Redaktsioon: 13. mai 2013, kell 17:36

teadmised
teadmised

Code: ITV0060
Link: http://www.lambda.ee/index.php/Teadmiste_otsing,_formaliseerimine_ja_hoidmine or http://www.lambda.ee/index/itv0060
Lecturer: Tanel Tammet
Contact: tanel.tammet@ttu.ee, 6203457, TTÜ AK223
Archives of previous years: 2012, 2011, 2010, 2009, 2008, 2007, 2006, [http:/cs.ttu.ee/kursused/wav4130/ older].

Muutused loengukohas

Loengud toimuvad nüüd ja edaspidi uues IT majas Akadeemia 15, 4 korrus arvutiteaduse seminariruumis 411.

Time, place, result

Semester: spring
Grading: exam
Points: 3.5

Lectures: every Monday 16:00-17.30, room IT-140.
Practical work: Thursdays on odd weeks 16:00-17:30 room IT-213D, IT-213H.
Practical work will give 40% and exam 60% of points underlying the final grade.


Practical work

There are three labs. All labs have to be presented to the prof and all students present at labwork.

First lab 2013

The main goal is to select a domain and a task for the second lab. What to search, from where, etc. You should experiment with scraping, search and apis to find out what you can really get, in practice. The ideas, experiments and the final plan should be presented. Might be useful to have a look at:


Deadline: 21. February.

Second lab 2013

The main goal is to develop an app which scrapes/searches potentially uncertain data from the web and creates a representation of that data in a machine-processable form (json, csv, xml etc). You can scrape html pages, google, bing, wolfram alpha results and/or use any apis like twitter, google places, google plus etc. It is best to have a combination of these.

Deadline: end of March.

Third lab 2013

The main goal of the third lab is to develop a ruleset for generating new interesting facts from the data obtained from the second lab. The ruleset has to be encoded in a format suitable for some first-order based logical prover and then used with the prover to actually derive new facts.

Deadline: end of the spring semester.

ITV006 third lab 2013


Lectures

Declarative and procedural representations

Lecture materials:

Databases: meaning and representation of facts

Lecture materials:


NoSQL databases

  • Nosql links and notes (here for exam: understand the basic categories of Nosql bases: what is the main point

and differences between the categories. Not necessary to know the details of different bases).

HTML annotations. RDFa, reading and using RDF data from web pages. Starting RDFs

Lecture materials:

Understand main parts:

RDFs continued. Starting OWL

Understand RDFS:

(for exam: you should understand the core principles of rdfs)

Understand basics of owl:

(for exam: you should understand the core principles of owl, not the details below here)

Owl background: description logics

Start looking at interesting ontologies:

  • SUMO (not necessary for exam)



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

For exam: you should be able to encode a small blocks world planning example and solve it. The details below "see also" are not necessary, but the last example is useful.

Lecture material:

See also:


Logic for uncertain knowledge

Indexes

Traditional database indexes incl B+ tree:

Bitmap indexes:

Hash indexes:

Fulltext indexes:


Data extraction

Not necessary for the exam.

Web mining by Nell:


Restricted english jms

Not necessary for the exam.


Various rule/logic languages

Not necessary for the exam.

Lecture material:

Several languages:

  • RDFS
  • OWL
  • KIF
  • CL
  • ontologies
  • wordnet
  • cyc
  • restricted english systems

See also: