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Seminar on Knowledge Graphs

NUMMER: 212113
KÜRZEL: SKNOWGR
MODULBEAUFTRAGTE:R: Prof. Dr. Maribel Acosta Deibe
DOZENT:IN:
FAKULTÄT: Fakultät für Informatik
SPRACHE: Englisch
SWS: 2 SWS
CREDITS: 3 CP
ANGEBOTEN IM: each winter semester

LINK ZUM VORLESUNGSVERZEICHNIS

Hier entlang.

VERANSTALTUNGSART

Mood­le

PRÜFUNGEN

FORM: Thesis and presentation
TERMIN: Siehe Prüfungsamt.

LERNFORM

se­mi­nar

LERNZIELE

The se­mi­nar in­clu­des four man­d­ato­ry ses­si­ons:

1. Kick-off ses­si­on (start of the se­mes­ter): Lec­tu­re on the fo­un­da­tio­nal tech­no­lo­gies of the se­mi­nar and pre­sen­ta­ti­on on the list of to­pics.
2. Preli­mi­na­ry pre­sen­ta­ti­on (start of the se­mes­ter): Se­mi­nar par­ti­ci­pants pre­sent in­iti­al ideas of the se­mi­nar the­sis.
3. In­ter­me­dia­te pre­sen­ta­ti­on (mid-se­mes­ter): Se­mi­nar par­ti­ci­pants re­port on the pro­gress of their the­ses.
4. Final pre­sen­ta­ti­on (end of the se­mes­ter): Se­mi­nar par­ti­ci­pants pre­sent their the­ses and final re­sults.

In ad­di­ti­on to the man­d­ato­ry ap­point­ments, se­mi­nar par­ti­ci­pants may sche­du­le in­di­vi­du­al mee­tings with the pro­fes­sor to di­s­cuss the pro­gress of the work (high­ly re­com­men­ded)

INHALT

Know­ledge Graphs (KG) allow for re­pre­sen­ting in­ter-con­nec­ted facts or state­ments an­no­ta­ted with se­man­ti­cs. In KGs, con­cepts and en­t­i­ties are ty­pi­cal­ly mo­de­led as nodes while their con­nec­tions are mo­de­led as di­rec­ted and la­be­led edges, crea­ting a graph.

In re­cent years, KGs have be­co­me core com­po­n­ents of mo­dern data eco­sys­tems. KGs, as buil­ding blocks of many Ar­ti­fi­ci­al In­tel­li­gence ap­proa­ches, allow for har­n­es­sing and un­co­ver­ing pat­terns from the data. Cur­rent­ly, KGs are used in the da­ta-dri­ven busi­ness pro­ces­ses of mul­ti­na­tio­nal com­pa­nies like Goog­le, Micro­soft, IBM, eBay, and Face­book. Fur­ther­mo­re, thousands of KGs are open­ly avail­able on the web fol­lowing the Lin­ked Data prin­ci­ples (https://lod-cloud.​net/​).

In this se­mi­nar, stu­dents will learn about sta­te-of-the-art KG tech­no­lo­gies and in­ves­ti­ga­te re­le­vant re­se­arch pro­blems in that field, in­clu­ding:

- Crea­ting KGs from (semi-)struc­tu­red on un­struc­tu­red sour­ces
- Re­pre­sen­ting facts in KGs: RDF, RDFS, OWL, Pro­per­ty Graphs
- Que­ry­ing KGs: SPAR­QL, Cy­pher­QL
- KG Qua­li­ty: me­trics and tasks to en­han­ce the qua­li­ty of KGs
- Vec­tor re­pre­sen­ta­ti­ons for KGs
- Pu­bli­ca­ti­on of KGs on the web

VORAUSSETZUNGEN CREDITS

passed seminar talk

EMPFOHLENE VORKENNTNISSE

Basic know­ledge about data­ba­ses or se­man­tic web is high­ly re­com­men­ded but not man­d­ato­ry.