Mining Massive Data Sets for Security : Advances in Data Mining, Search, Social Networks and Text Mining, and Their Applications to Security
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| Title: | Mining Massive Data Sets for Security : Advances in Data Mining, Search, Social Networks and Text Mining, and Their Applications to Security |
|---|---|
| Description: | The real power for security applications will come from the synergy of academic and commercial research focusing on the specific issue of security. Special constraints apply to this domain, which are not always taken into consideration by academic research, but are critical for successful security applications: large volumes: techniques must be able to handle huge amounts of data and perform ‘on-line'computation; scalability: algorithms must have processing times that scale well with ever growing volumes; automation: the analysis process must be automated so that information extraction can ‘run on its own'; ease of use: everyday citizens should be able to extract and assess the necessary information; and robustness: systems must be able to cope with data of poor quality (missing or erroneous data). The NATO Advanced Study Institute (ASI) on Mining Massive Data Sets for Security, held in Italy, September 2007, brought together around ninety participants to discuss these issues. This publication includes the most important contributions, but can of course not entirely reflect the lively interactions which allowed the participants to exchange their views and share their experience. The bridge between academic methods and industrial constraints is systematically discussed throughout. This volume will thus serve as a reference book for anyone interested in understanding the techniques for handling very large data sets and how to apply them in conjunction for solving security issues. |
| Authors: | Françoise Fogelman-Soulié, Jakub Piskorski, Ralf Steinberger |
| Resource Type: | eBook. |
| Subjects: | Terrorism--Prevention--Congresses, Computer algorithms--Congresses, Data mining--Congresses, Terrorism--Risk assessment--Congresses |
| Categories: | COMPUTERS / Business & Productivity Software / Databases, COMPUTERS / Data Science / Data Analytics, COMPUTERS / Security / General |
| Database: | eBook Collection (EBSCOhost) |
| FullText | Links: – Type: ebook-pdf Text: Availability: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Mining Massive Data Sets for Security : Advances in Data Mining, Search, Social Networks and Text Mining, and Their Applications to Security – Name: Abstract Label: Description Group: Ab Data: The real power for security applications will come from the synergy of academic and commercial research focusing on the specific issue of security. Special constraints apply to this domain, which are not always taken into consideration by academic research, but are critical for successful security applications: large volumes: techniques must be able to handle huge amounts of data and perform ‘on-line'computation; scalability: algorithms must have processing times that scale well with ever growing volumes; automation: the analysis process must be automated so that information extraction can ‘run on its own'; ease of use: everyday citizens should be able to extract and assess the necessary information; and robustness: systems must be able to cope with data of poor quality (missing or erroneous data). The NATO Advanced Study Institute (ASI) on Mining Massive Data Sets for Security, held in Italy, September 2007, brought together around ninety participants to discuss these issues. This publication includes the most important contributions, but can of course not entirely reflect the lively interactions which allowed the participants to exchange their views and share their experience. The bridge between academic methods and industrial constraints is systematically discussed throughout. This volume will thus serve as a reference book for anyone interested in understanding the techniques for handling very large data sets and how to apply them in conjunction for solving security issues. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Françoise+Fogelman-Soulié%22">Françoise Fogelman-Soulié</searchLink><br /><searchLink fieldCode="AR" term="%22Jakub+Piskorski%22">Jakub Piskorski</searchLink><br /><searchLink fieldCode="AR" term="%22Ralf+Steinberger%22">Ralf Steinberger</searchLink> – Name: TypePub Label: Resource Type Group: TypPub Data: eBook. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Terrorism--Prevention--Congresses%22">Terrorism--Prevention--Congresses</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+algorithms--Congresses%22">Computer algorithms--Congresses</searchLink><br /><searchLink fieldCode="DE" term="%22Data+mining--Congresses%22">Data mining--Congresses</searchLink><br /><searchLink fieldCode="DE" term="%22Terrorism--Risk+assessment--Congresses%22">Terrorism--Risk assessment--Congresses</searchLink> – Name: SubjectBISAC Label: Categories Group: Su Data: <searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Business+%26+Productivity+Software+%2F+Databases%22">COMPUTERS / Business & Productivity Software / Databases</searchLink><br /><searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Data+Science+%2F+Data+Analytics%22">COMPUTERS / Data Science / Data Analytics</searchLink><br /><searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Security+%2F+General%22">COMPUTERS / Security / General</searchLink> |
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| RecordInfo | BibRecord: BibEntity: Classifications: – Code: 006.3 Scheme: ddc Type: prePub Languages: – Code: eng Text: English Subjects: – SubjectFull: Terrorism--Prevention--Congresses Type: general – SubjectFull: Computer algorithms--Congresses Type: general – SubjectFull: Data mining--Congresses Type: general – SubjectFull: Terrorism--Risk assessment--Congresses Type: general Titles: – TitleFull: Mining Massive Data Sets for Security : Advances in Data Mining, Search, Social Networks and Text Mining, and Their Applications to Security Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Françoise Fogelman-Soulié – PersonEntity: Name: NameFull: Jakub Piskorski – PersonEntity: Name: NameFull: Ralf Steinberger – PersonEntity: Name: NameFull: Françoise Fogelman-Soulié – PersonEntity: Name: NameFull: Jakub Piskorski – PersonEntity: Name: NameFull: Ralf Steinberger IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2008 – D: 04 M: 02 Type: profile Y: 2014 Identifiers: – Type: isbn-print Value: 9781586038984 – Type: isbn-electronic Value: 9781441605399 – Type: isbn-electronic Value: 9781607503620 Numbering: – Type: volume Value: 00019 Titles: – TitleFull: Mining Massive Data Sets for Security : Advances in Data Mining, Search, Social Networks and Text Mining, and Their Applications to Security Type: main |
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