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Investigative Data Mining: Mathematical Models for Analyzing, Visualizing and Destabilizing Terrorist Networks

von Nasrullah Memon

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Statistik und Sichtungsnachweis dieser Seite findet sich am Artikelende
[1.] Nm/Fragment 206 01 - Diskussion
Zuletzt bearbeitet: 2012-08-03 22:01:29 Sotho Tal Ker
Fragment, Gesichtet, Nm, SMWFragment, Schutzlevel sysop, Verschleierung, Zhao et al 2006

Typus
Verschleierung
Bearbeiter
Graf Isolan
Gesichtet
Yes.png
Untersuchte Arbeit:
Seite: 206, Zeilen: 1-21
Quelle: Zhao et al 2006
Seite(n): 2, Zeilen: left column 43-49, right column 1, 13-30
• Terrorist organizations such as Al Qaeda

• Terrorists such as Osama Bin Ladin, Ramzi Yousef, etc.

• Terrorist facilities such as Darunta Training Camp, Khalden Training Camp, etc.

• Terrorist events/attacks such as 9/11, WTC terrorist attack 2003, etc.

The dataset also contains various types of relations connecting instances of different entity types. Here is a partial list of the various relation types:

• memberOf: instances of terrorist can be affiliated with various instances of terrorist organization.

• facilityOwner: instances of terrorist facility are usually run by instances of terrorist organizations.

• facilityMember: instances of terrorist are linked to various instances of terrorist facilities if the terrorist instance attended/spent some time at the facility.

• claimResponsibility: instances of terrorist organization are linked to the instances of terror attacks they claim responsibility for.

• participatedIn: instances of terrorist that may have participated in instances of terror attacks.

Terrorist organizations such as Hamas, Hizballah, Liberation Tigers of Tamil Eelam (LTTE), etc.

Terrorists such as Osama bin Ladin, Ramzi Yousef, etc.

Terrorist facilities such as Darunta Training Camp, Khalden Training Camp, etc.

Terrorist events/attacks such as African embassy bombings of 1998, Madrid Bombings of 2004, etc.

[...]

The dataset also contains various types of relations connecting instances of different entity types. Here is a partial list of the various relation types:

memberOf: instances of terrorist can be affiliated with various instances of terrorist organization.

facilityOwner: instances of terrorist facility are usually run by instances of terrorist organizations.

facilityMember: instances of terrorist are linked to various instances of terrorist facilities if the terrorist instance attended/spent some time at the facility.

claimResponsibility: instances of terrorist organization are linked to the instances of terror attacks they claim responsibility for.

participate: instances of terrorist may participate in instances of terror attacks.

Anmerkungen

continues the verbatim take-over of the description of another research group's counter-terrorism knowledge base;

Mark also the transcription "Bin Ladin" which corresponds to the one given in the source, but which is used nowhere else in Nm's thesis (Usually Nm writes "Bin Laden").

Sichter
(Graf Isolan), fiesh

[2.] Nm/Fragment 206 26 - Diskussion
Zuletzt bearbeitet: 2012-05-22 20:01:31 Hindemith
Fragment, Gesichtet, Jensen et al 2003, KomplettPlagiat, Nm, SMWFragment, Schutzlevel sysop

Typus
KomplettPlagiat
Bearbeiter
Graf Isolan
Gesichtet
Yes.png
Untersuchte Arbeit:
Seite: 206, Zeilen: 26-28
Quelle: Jensen et al 2003
Seite(n): 381, Zeilen: left column 6-12
The analysis of relational data is a rapidly growing area within the larger research community interested in machine learning, knowledge discovery, and data mining. Several workshops [(Dzeroski, S., De Raedt, L., and Wrobel, S. 2002; Getoor, L., and Jensen, D. 2000; Jensen, D. and Goldberg, H. 1998) have focused on this particular topic, and another DARPA research program — Evidence Extraction and Link Discovery (EELD) —focuses on extracting, representing, reasoning with, and learning from relational data.] Analysis of relational data is a rapidly growing area within the larger research community interested in machine learning, knowledge discovery, and data mining. Several recent workshops [EN 3, EN 6, EN 8] have focused on this precise topic, and another DARPA research program — Evidence Extraction and Link Discovery (EELD) —focuses on extracting, representing, reasoning with, and learning from relational data. [FN 5]

---

[EN 3] Dzeroski, S., De Raedt, L., and Wrobel, S. (Eds). Papers of the Workshop on Multi-Relational Data Mining. The Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM Press, 2002.

[EN 6] Getoor, L., and Jensen, D. (Eds). Learning Statistical Models from Relational Data: Papers from the AAAI 2000 Workshop, AAAI Press, Menlo Park CA, 2000.

[EN 8] Jensen, D. and Goldberg, H. Artificial Intelligence and Link Analysis: Papers from the 1998 AAAI Fall Symposium., AAAI Press, Menlo Park CA, 1998.

Anmerkungen

Verbatim with the references as in the source, which is not referenced, although it represents another workshop of those described.

Sichter
(Graf Isolan), Hindemith


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