Teadmiste otsing, formaliseerimine ja hoidmine: erinevus redaktsioonide vahel

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lab. The ruleset has to be encoded in a format suitable for some first-order based logical prover and then used
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.
with the prover to actually derive new facts.
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Redaktsioon: 1. veebruar 2014, kell 22:41

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: 2013, 2012, 2011, 2010, 2009, 2008, 2007, 2006, [http:/cs.ttu.ee/kursused/wav4130/ older].


Time, place, result

Semester: spring
Grading: exam

Lectures: every Wedesday 16:00-17.30, room ICT-A2
Practical work: Fridays on odd weeks (7. Feb, 21 Feb, ...) 12:00-13:30 room ICT-403
Practical work will give 40% and exam 60% of points underlying the final grade.

Focus

The main focus of the course is on KR (knowledge representation): how to represent nontrivial information in programs and databases, how to build and use indexes for efficient search through large sets of knowledge.

The course contains three blocks built on each other:

  • Declarative and procedural representations, relational and nosql databases, core logic, html annotations.


Practical work

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

First lab 2014

Second lab 2014

Third lab 2014

Lecture block 1: declarative/procedural, KR in programming languages, databases, core logic, web annotations

Declarative and procedural representations. Notes on relational databases.

Lecture materials:

Databases: SQL and NoSQL: meaning and representation of facts

Lecture materials:

HTML annotations. Microformats, microdata, RDFa, Starting RDFs

Lecture materials:

Understand main parts:

Data extraction

  • Overview
  • Some details about Nell as a nice example.

Lecture block 2: various languages: rule/logic languages, restricted English

Important rule/logic languages

Not necessary for the exam.

Several languages:

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

See also:

RDFs and OWL

Understand RDFS:

Lecture material:

Understand basics of owl:

Owl background: description logics

Start looking at interesting ontologies:

Restricted english

Attempto details not necessary for the exam.

Lecture block 3: time and uncertain knowledge

Rules in planning and robotics

Lecture material:

See also:

Logic for uncertain knowledge

For the exam: you should be able to create and solve small examples with default logic.

Fuzzy and probabilistic logic

For the exam: understand the differences between fuzzy and probabilistic logic and be able to present small examples.

Logic of belief and knowledge

For exam: understand referential transparency and core ideas about encoding belief and knowledge. Modal logic not necessary for the exam.

Lecture block 4: indexes and search

Indexes: intro and mainstream

Traditional database indexes incl B+ tree:

Hash indexes:

Bitmap indexes:

For exam: understand the core usage scenarios and be able to create small examples.

Multi-field and geoindexes, fulltext and term indexes

Fancier term indexes

  • Path indexes
  • On from here.

Nosql indexes

  • Document bases
  • Graph bases
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