[go: up one dir, main page]

Kolchinsky et al., 2019 - Google Patents

Real-time multi-pattern detection over event streams

Kolchinsky et al., 2019

View PDF
Document ID
7056401670846197417
Author
Kolchinsky I
Schuster A
Publication year
Publication venue
Proceedings of the 2019 International Conference on Management of Data

External Links

Snippet

Rapid advances in data-driven applications over recent years have intensified the need for efficient mechanisms capable of monitoring and detecting arbitrarily complex patterns in massive data streams. This task is usually performed by complex event processing (CEP) …
Continue reading at dl.acm.org (PDF) (other versions)

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
    • G06F17/30442—Query optimisation
    • G06F17/30448—Query rewriting and transformation
    • G06F17/30451—Query rewriting and transformation of sub-queries or views
    • 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
    • G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30386—Retrieval requests
    • G06F17/30424—Query processing
    • G06F17/30533—Other types of 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
    • G06F17/30943—Information retrieval; Database structures therefor; File system structures therefor details of database functions independent of the retrieved data type
    • G06F17/30946—Information retrieval; Database structures therefor; File system structures therefor details of database functions independent of the retrieved data type indexing structures
    • G06F17/30958—Graphs; Linked lists
    • 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
    • G06F17/30312—Storage and indexing structures; Management thereof
    • G06F17/30321—Indexing structures
    • 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
    • G06F17/30587—Details of specialised database models
    • 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
    • G06F17/30861—Retrieval from the Internet, e.g. browsers
    • 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
    • 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
    • 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
    • Y10S707/99931—Database or file accessing
    • Y10S707/99933—Query processing, i.e. searching

Similar Documents

Publication Publication Date Title
Kolchinsky et al. Real-time multi-pattern detection over event streams
Qian et al. Active learning for large-scale entity resolution
Fumarola et al. CloFAST: closed sequential pattern mining using sparse and vertical id-lists
Sethi et al. HFIM: a Spark-based hybrid frequent itemset mining algorithm for big data processing
US20180329958A1 (en) Performance and usability enhancements for continuous subgraph matching queries on graph-structured data
Kolchinsky et al. Join query optimization techniques for complex event processing applications
Qin et al. Towards bridging theory and practice: hop-constrained st simple path enumeration
Dalvi et al. Optimal hashing schemes for entity matching
Peng et al. Hop-constrained st Simple Path Enumeration: Towards Bridging Theory and Practice.
Kolchinsky et al. Efficient adaptive detection of complex event patterns
US8150790B2 (en) Lightweight physical design alerter
Verma et al. Dams: Dynamic association for view materialization based on rule mining scheme
Wang et al. Efficient computation of g-skyline groups
Han et al. Efficiently mining frequent itemsets on massive data
US11875199B2 (en) Real-time multi-pattern detection over event streams
Han et al. An efficient algorithm for mining closed high utility itemsets over data streams with one dataset scan
Makanju et al. Deep parallelization of parallel FP-growth using parent-child MapReduce
Wu et al. Efficient algorithms for deriving complete frequent itemsets from frequent closed itemsets
Aluç et al. chameleon-db: a workload-aware robust RDF data management system
Thakkar et al. Smm: A data stream management system for knowledge discovery
Wu et al. Novel structures for counting frequent items in time decayed streams
Gottlob et al. The hypertrac project: Recent progress and future research directions on hypergraph decompositions
Djenouri et al. Diversification heuristics in bees swarm optimization for association rules mining
Bhattarai et al. Mnemonic: A parallel subgraph matching system for streaming graphs
Saranya et al. Certain strategic study on machine learning-based graph anomaly detection