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Erhan Giral

from Danville, CA
Age ~43
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Also known as:
Erhan Girall, Giral Erhan
Related to:
Erhan Girall
Connected to:
Ruben Giral, 46Anthony Giraldez, 32Pedro P Giraldez, 70Raquel M Giraldez, 66Robert Giraldez, 50Andrew W Giraldi, 43Anthony M Giraldi, 68Jeffery Giraldi, 45Robert T Giraldi, 38Adiela Giraldo, 60

Erhan Giral Phones & Addresses

  • Danville, CA
  • 15288 Fruitvale Ave, Saratoga, CA 95070
  • Daly City, CA
  • Lafayette, CA
  • 285 Lee St, Oakland, CA 94610 (510) 444-4558
  • Berkeley, CA

Publications

Us Patents

Visualization Of Jvm And Cross-Jvm Call Stacks

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US Patent:
20120260236, Oct 11, 2012
Filed:
Apr 8, 2011
Appl. No.:
13/082741
Inventors:
Indranil Basak - West Linn OR, US
Erhan Giral - Lafayette CA, US
Assignee:
COMPUTER ASSOCIATES THINK, INC. - Islandia NY
International Classification:
G06F 9/44
US Classification:
717132
Abstract:
A method for diagnosing problems in a computer system by visualizing flows through applications and other subsystems in a directed graph on a user interface. The user interface represents multiple instances of each application or other subsystem by a respective node, and edges indicate which nodes depend on one another. Aggregate metrics which are based on the multiple instances, and associated alerts, can be provided for the nodes and edges. An aging process can indicate which nodes have not been recently invoked. The user interface can also indicate which nodes and edges are associated with a given business transaction. In a summary view, a node hides the identity of invoked components such as servlets of the application, while in a detailed view these details are provided.

Probabilistic Root Cause Analysis

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US Patent:
20230095270, Mar 30, 2023
Filed:
Mar 31, 2022
Appl. No.:
17/657628
Inventors:
- Houston TX, US
Erhan Giral - Danville CA, US
International Classification:
G06F 11/07
G06N 5/02
G06F 16/901
Abstract:
Described systems and techniques determine causal associations between events that occur within an information technology landscape. Individual situations that are likely to represent active occurrences requiring a response may be identified as causal event clusters, without requiring manual tuning to determine cluster boundaries. Consequently, it is possible to identify root causes, analyze effects, predict future events, and prevent undesired outcomes, even in complicated, dispersed, interconnected systems.

Recommendations For Remedial Actions

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US Patent:
20230096290, Mar 30, 2023
Filed:
Mar 31, 2022
Appl. No.:
17/657626
Inventors:
- Houston TX, US
Erhan Giral - Danville CA, US
International Classification:
G06F 11/07
Abstract:
Described systems and techniques determine causal associations between events that occur within an information technology landscape. Individual situations that are likely to represent active occurrences requiring a response may be identified as causal event clusters, without requiring manual tuning to determine cluster boundaries. Consequently, it is possible to identify root causes, analyze effects, predict future events, and prevent undesired outcomes, even in complicated, dispersed, interconnected systems.

Directed Incremental Clustering Of Causally Related Events

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US Patent:
20230098896, Mar 30, 2023
Filed:
Mar 31, 2022
Appl. No.:
17/657623
Inventors:
- Houston TX, US
Erhan Giral - Danville CA, US
International Classification:
H04L 41/0631
H04L 41/069
H04L 41/12
Abstract:
Described systems and techniques determine causal associations between events that occur within an information technology landscape. Individual situations that are likely to represent active occurrences requiring a response may be identified as causal event clusters, without requiring manual tuning to determine cluster boundaries. Consequently, it is possible to identify root causes, analyze effects, predict future events, and prevent undesired outcomes, even in complicated, dispersed, interconnected systems.

Directed Incremental Clustering Of Causally Related Events Using Multi-Layered Small World Networks

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US Patent:
20230102002, Mar 30, 2023
Filed:
Mar 31, 2022
Appl. No.:
17/657622
Inventors:
- Houston TX, US
Erhan Giral - Danville CA, US
International Classification:
H04L 41/0631
G06N 3/08
H04L 41/14
Abstract:
Described systems and techniques determine causal associations between events that occur within an information technology landscape. Individual situations that are likely to represent active occurrences requiring a response may be identified as causal event clusters, without requiring manual tuning to determine cluster boundaries. Consequently, it is possible to identify root causes, analyze effects, predict future events, and prevent undesired outcomes, even in complicated, dispersed, interconnected systems.

Ccontinuous Knowledge Graph Generation Using Causal Event Graph Feedback

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US Patent:
20230102786, Mar 30, 2023
Filed:
Sep 23, 2022
Appl. No.:
17/934992
Inventors:
- Houston TX, US
Erhan Giral - Danville CA, US
International Classification:
G06N 5/02
G06N 3/08
Abstract:
Described systems and techniques determine causal associations between events that occur within an information technology landscape. Individual situations that are likely to represent active occurrences requiring a response may be identified as causal event clusters, without requiring manual tuning to determine cluster boundaries. Consequently, it is possible to identify root causes, analyze effects, predict future events, continuously generate a knowledge graph, and prevent undesired outcomes, even in complicated, dispersed, interconnected systems.

Efficient Mining Of Web-Page Related Messages

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US Patent:
20200110841, Apr 9, 2020
Filed:
Oct 9, 2018
Appl. No.:
16/155268
Inventors:
- New York NY, US
Erhan Giral - Saratoga CA, US
International Classification:
G06F 17/30
G06F 17/27
G06K 9/62
G06F 17/18
Abstract:
To extract meaningful information that aids in analysis of a web application or web site based on page summarizations without impractical resource demand, statistical modeling is employed to approximately identify pages across web application transactions and predict meaningful content or items of information within the pages. Statistics are collected on a sample of traffic for a web application. The collected statistics are on tokens generated from messages that correspond to web pages. Statistics are collected by message, by transaction, and across the sampling of messages. Descriptive tokens that meaningfully describe a web page and attribute-value pair tokens are scored. Those of the tokens that satisfy selection criteria are selected as a basis for generating extraction rules. Subsequently, the extraction rules are applied to message payloads to efficiently extract descriptive “tags” and attribute-value pairs.

Multivariate Path-Based Anomaly Prediction

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US Patent:
20190294524, Sep 26, 2019
Filed:
Mar 29, 2018
Appl. No.:
15/939893
Inventors:
- New York NY, US
Erhan Giral - Saratoga CA, US
David Sanchez Charles - Barcelona, ES
Victor Muntés-Mulero - Sant Feliu de Llobregat, ES
International Classification:
G06F 11/36
G06F 11/34
G06F 11/30
Abstract:
A multivariate path-based anomaly detection and prediction service (“anomaly detector”) can generate a prediction event for consumption by the APM manager that indicates a likelihood of an anomaly occurring based on path analysis of multivariate values after topology-based feature selection. To predict that a set of metrics will travel to a cluster that represents anomalous application behavior, the anomaly detector analyzes a set of multivariate date slices that are not within a cluster to determine whether dimensionally reduced representations of the set of multivariate data slices fit a path as described by a function.
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Erhan Giral from Danville, CA, age ~43 Get Report