WO2006037747A3 - Method for structuring a data stock that is stored on at least one storage medium - Google Patents

Method for structuring a data stock that is stored on at least one storage medium Download PDF

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Publication number
WO2006037747A3
WO2006037747A3 PCT/EP2005/054891 EP2005054891W WO2006037747A3 WO 2006037747 A3 WO2006037747 A3 WO 2006037747A3 EP 2005054891 W EP2005054891 W EP 2005054891W WO 2006037747 A3 WO2006037747 A3 WO 2006037747A3
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WO
WIPO (PCT)
Prior art keywords
parametric
data
structuring
stored
data records
Prior art date
Application number
PCT/EP2005/054891
Other languages
German (de)
French (fr)
Other versions
WO2006037747A2 (en
Inventor
Volker Tresp
Kai Yu
Shipeng Yu
Original Assignee
Siemens Ag
Volker Tresp
Kai Yu
Shipeng Yu
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Siemens Ag, Volker Tresp, Kai Yu, Shipeng Yu filed Critical Siemens Ag
Publication of WO2006037747A2 publication Critical patent/WO2006037747A2/en
Publication of WO2006037747A3 publication Critical patent/WO2006037747A3/en

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/23—Clustering techniques
    • G06F18/232—Non-hierarchical techniques
    • G06F18/2321—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Mathematical Optimization (AREA)
  • Mathematical Physics (AREA)
  • Pure & Applied Mathematics (AREA)
  • Computational Mathematics (AREA)
  • Mathematical Analysis (AREA)
  • Probability & Statistics with Applications (AREA)
  • General Engineering & Computer Science (AREA)
  • Evolutionary Biology (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Software Systems (AREA)
  • Operations Research (AREA)
  • Databases & Information Systems (AREA)
  • Algebra (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Evolutionary Computation (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Complex Calculations (AREA)

Abstract

The invention relates to a non-parametric Bayes method for analysing data records, in which elements occur with a specific frequency. The installed model retains the size of earlier extensions, in which latent factors of each data record (e.g. themes of documents) were investigated, whilst at the same time permitting the investigation of the cluster structures of data records, which reflect the statistical dependency of the latent factors. Compared to parametric Bayes modelling, the non-parametric model that is induced by a Dirichlet process (DP) is sufficiently flexible to reveal the data structure. Instead of having to use the Markov chain Monte Carlo (MCMC), which is slow with our specifications, the inventive method introduces an efficient variational inference, which is based on a finite, highly-dimensioned approximation of (DP).
PCT/EP2005/054891 2004-10-04 2005-09-28 Method for structuring a data stock that is stored on at least one storage medium WO2006037747A2 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102004048272.1 2004-10-04
DE102004048272 2004-10-04

Publications (2)

Publication Number Publication Date
WO2006037747A2 WO2006037747A2 (en) 2006-04-13
WO2006037747A3 true WO2006037747A3 (en) 2007-05-31

Family

ID=35985416

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/EP2005/054891 WO2006037747A2 (en) 2004-10-04 2005-09-28 Method for structuring a data stock that is stored on at least one storage medium

Country Status (1)

Country Link
WO (1) WO2006037747A2 (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105426647B (en) * 2016-01-18 2018-08-07 中国人民解放军国防科学技术大学 Cold stand-by systems reliablity estimation method based on the fusion of reliability prior information

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
BLEI D M ET AL: "Hierarchical topic models and the nested Chinese restaurant process", ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS (NIPS) 16 (THRUN S ET AL EDITORS), 2004, Cambridge, MA, MIT Press, XP002427365, Retrieved from the Internet <URL:http://www.cs.princeton.edu/~blei/papers/BleiGriffithsJordanTenenbaum2003.pdf> [retrieved on 20070329] *
BLEI D M ET AL: "Latent Dirichlet Allocation", JOURNAL OF MACHINE LEARNING RESEARCH, vol. 3, January 2003 (2003-01-01), pages 993 - 1022, XP002427366, Retrieved from the Internet <URL:http://portal.acm.org/citation.cfm?id=944937&dl=GUIDE,> [retrieved on 20070329] *
BLEI D M ET AL: "Variational methods for the Dirichlet process", 21ST INTERNATIONAL CONFERENCE ON MACHINE LEARNING (ICML 2004), 4-8 JULY 2004, BANFF, CANADA, 4 July 2004 (2004-07-04), XP002427364, Retrieved from the Internet <URL:http://portal.acm.org/citation.cfm?id=1015330.1015439> [retrieved on 20070329] *
YU K ET AL: "Dirichlet enhanced latent semantic analysis", 10TH INTERNATIONAL WORKSHOP ON ARTIFICIAL INTELLIGENCE AND STATISTICS (AISTATS-05), 6-8 JANUARY 2005, BARBADOS, 6 January 2005 (2005-01-06), XP002427363, Retrieved from the Internet <URL:http://www.dbs.informatik.uni-muenchen.de/~yu_k/aistat2005l.pdf> [retrieved on 20070329] *

Also Published As

Publication number Publication date
WO2006037747A2 (en) 2006-04-13

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