Teadmiste otsing, formaliseerimine ja hoidmine

Allikas: Lambda
Redaktsioon seisuga 1. veebruar 2014, kell 22:35 kasutajalt Tammet (arutelu | kaastöö)
Mine navigeerimisribale Mine otsikasti
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

Web mining by Nell:


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

Various 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

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 the 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:

  • wiki. Understand the core usage scenario and be able to create a small example.

Bitmap indexes:

  • wiki. For exam: understand the core usage scenario of bitmap indexes.

Multi-field and geoindexes, Fulltext and term indexes

A few words about both multi-field indexes and geoindexes.

Fancier term indexes

  • Path indexes
  • On from here.

Nosql indexes

  • Document bases
  • Graph bases