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1. WO2016156115 - ANOMALY DETECTION BY MULTI-LEVEL TOLERANCE RELATIONS

Publication Number WO/2016/156115
Publication Date 06.10.2016
International Application No. PCT/EP2016/056284
International Filing Date 22.03.2016
IPC
G06Q 10/06 2012.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
10Administration; Management
06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
G06Q 30/02 2012.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
30Commerce, e.g. shopping or e-commerce
02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
G06F 17/30 2006.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
FELECTRIC DIGITAL DATA PROCESSING
17Digital computing or data processing equipment or methods, specially adapted for specific functions
30Information retrieval; Database structures therefor
G06F 11/30 2006.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
FELECTRIC DIGITAL DATA PROCESSING
11Error detection; Error correction; Monitoring
30Monitoring
CPC
G06F 11/3072
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
FELECTRIC DIGITAL DATA PROCESSING
11Error detection; Error correction; Monitoring
30Monitoring
3065Monitoring arrangements determined by the means or processing involved in reporting the monitored data
3072where the reporting involves data filtering, e.g. pattern matching, time or event triggered, adaptive or policy-based reporting
G06F 16/22
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
FELECTRIC DIGITAL DATA PROCESSING
16Information retrieval; Database structures therefor; File system structures therefor
20of structured data, e.g. relational data
22Indexing; Data structures therefor; Storage structures
G06F 16/24578
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
FELECTRIC DIGITAL DATA PROCESSING
16Information retrieval; Database structures therefor; File system structures therefor
20of structured data, e.g. relational data
24Querying
245Query processing
2457with adaptation to user needs
24578using ranking
G06F 16/2468
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
FELECTRIC DIGITAL DATA PROCESSING
16Information retrieval; Database structures therefor; File system structures therefor
20of structured data, e.g. relational data
24Querying
245Query processing
2458Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
2468Fuzzy queries
G06N 20/00
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
20Machine learning
G06Q 10/06
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
10Administration; Management
06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
Applicants
  • BRITISH TELECOMMUNICATIONS PUBLIC LIMITED COMPANY [GB]/[GB]
Inventors
  • AZVINE, Behnam
  • MARTIN, Trevor
Agents
  • ROBERTS, Scott
Priority Data
15161343.727.03.2015EP
Publication Language English (en)
Filing Language English (EN)
Designated States
Title
(EN) ANOMALY DETECTION BY MULTI-LEVEL TOLERANCE RELATIONS
(FR) DÉTECTION D'ANOMALIE PAR RELATIONS DE TOLÉRANCE MULTINIVEAUX
Abstract
(EN) A method for partitioning a plurality of entities each associated with a plurality of ordered sequences of events received by a computer system, the method comprising: defining a minimal directed acyclic graph data structure representing the sequences of events to define a plurality of categories of behaviour of the entities; defining a threshold degree of similarity as an xmu number, the xmu number having cardinality that is able to vary across a normalised range; defining a relation for each entity including a degree of association of the entity with each of the categories; defining a cluster of entities as a set of entities comprising a first entity; and comparing a relation for the first entity with a relation for a second entity to define a xmu Jaccard similarity coefficient for the first and second entities; responsive to the coefficient meeting the threshold degree of similarity, adding the second entity to the cluster.
(FR) L'invention concerne un procédé de partitionnement d'une pluralité d'entités, chacune associée à une pluralité de séquences ordonnées d'événements reçues par un système informatique, le procédé comprenant les étapes suivantes : définition d'une structure de données graphique acyclique dirigée minimale représentant les séquences d'événements afin de définir une pluralité de catégories de comportement des entités; définition d'un degré de seuil de similarité en tant que nombre xmu, le nombre xmu ayant une cardinalité qui est capable de varier sur une plage normalisée; définition d'une relation pour chaque entité comprenant un degré d'association de l'entité avec chacune des catégories; définition d'une grappe d'entités sous la forme d'un ensemble d'entités comprenant une première entité; et comparaison d'une relation pour la première entité avec une relation pour une deuxième entité afin de définir un coefficient de similarité de Jaccard xmu pour les première et deuxième entités; en réponse au fait que le coefficient satisfait au degré de seuil de similarité, ajout de la deuxième entité à la grappe.
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