Amant et al., 1994 - Google Patents
Toward the Integration of Exploration and Modeling in a Planning Framework.Amant et al., 1994
View PDF- Document ID
- 10727891518866356784
- Author
- Amant R
- Cohen P
- Publication year
- Publication venue
- KDD Workshop
External Links
Snippet
Statistical operations are often facilitated by other operations. We can facilitate modeling operations by testing their input for irregularities and removing problems wherever possible. A planning representation is well-suited to this task. We describe the representation used in …
- 238000000034 method 0 abstract description 23
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
- G06F17/30386—Retrieval requests
- G06F17/30424—Query processing
- G06F17/30477—Query execution
- G06F17/30507—Applying rules; deductive queries
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30705—Clustering or classification
- G06F17/3071—Clustering or classification including class or cluster creation or modification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/02—Knowledge representation
- G06N5/022—Knowledge engineering, knowledge acquisition
- G06N5/025—Extracting rules from data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
- G06K9/6279—Classification techniques relating to the number of classes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
- Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10S707/00—Data processing: database and file management or data structures
- Y10S707/99931—Database or file accessing
- Y10S707/99933—Query processing, i.e. searching
- Y10S707/99936—Pattern matching access
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA 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
- G06Q10/00—Administration; Management
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
- Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10S707/00—Data processing: database and file management or data structures
- Y10S707/99941—Database schema or data structure
- Y10S707/99942—Manipulating data structure, e.g. compression, compaction, compilation
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US5317741A (en) | Computer method for identifying a misclassified software object in a cluster of internally similar software objects | |
US7426497B2 (en) | Method and apparatus for analysis and decomposition of classifier data anomalies | |
US5440742A (en) | Two-neighborhood method for computing similarity between two groups of objects | |
Shokripour et al. | Why so complicated? simple term filtering and weighting for location-based bug report assignment recommendation | |
Peukert et al. | A self-configuring schema matching system | |
EP3674918B1 (en) | Column lineage and metadata propagation | |
US20040225631A1 (en) | System and method for identifying a workload type for a given workload of database requests | |
Rheinländer et al. | SOFA: An extensible logical optimizer for UDF-heavy data flows | |
US5485621A (en) | Interactive method of using a group similarity measure for providing a decision on which groups to combine | |
Redyuk et al. | Automating Data Quality Validation for Dynamic Data Ingestion. | |
Tu et al. | FRUGAL: Unlocking semi-supervised learning for software analytics | |
US11113266B2 (en) | Detecting inconsistencies in semantics of business vocabulary and business rules (SBVR) using many-sorted logic | |
Jonsson et al. | Automatic localization of bugs to faulty components in large scale software systems using bayesian classification | |
US5428788A (en) | Feature ratio method for computing software similarity | |
US5438676A (en) | Method for adapting a similarity function for identifying misclassified software objects | |
Sharma et al. | Indexer++ workload-aware online index tuning with transformers and reinforcement learning | |
Girard et al. | A comparison of abstract data types and objects recovery techniques | |
Amant et al. | Toward the Integration of Exploration and Modeling in a Planning Framework. | |
CN117827882B (en) | Deep learning-based financial database SQL quality scoring method, system, equipment and storable medium | |
CN117687824A (en) | Satellite fault diagnosis system based on quality problem knowledge graph | |
Samer et al. | Towards issue recommendation for open source communities | |
Tatale et al. | A Survey on Test Case Generation using UML Diagrams and Feasibility Study to Generate Combinatorial Logic Oriented Test Cases. | |
Memon et al. | A regression analysis based model for defect learning and prediction in software development | |
Alhumam | Explainable Software Fault Localization Model: From Blackbox to Whitebox. | |
Iria et al. | An incremental tri-partite approach to ontology learning |