Venkataraman et al., 2019 - Google Patents
Towards identifying impacted users in cellular servicesVenkataraman et al., 2019
View PDF- Document ID
- 48102795265949480
- Author
- Venkataraman S
- Wang J
- Publication year
- Publication venue
- Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
External Links
Snippet
An essential step in the customer care routine of cellular service carriers is determining whether an individual user is impacted by on-going service issues. This is traditionally done by monitoring the network and the services. However, user feedback data, generated when …
- 230000001413 cellular 0 title abstract description 8
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
-
- 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
- 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
- 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
- G06Q10/10—Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
-
- 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
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
-
- 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
- G06N7/00—Computer systems based on specific mathematical models
- G06N7/005—Probabilistic networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN109615116B (en) | A kind of telecommunication fraud incident detection method and detection system | |
Harms et al. | Discovering sequential association rules with constraints and time lags in multiple sequences | |
CN112306982B (en) | Abnormal user detection method and device, computing equipment and storage medium | |
Carton et al. | Extractive adversarial networks: High-recall explanations for identifying personal attacks in social media posts | |
CN117708746B (en) | Risk prediction method based on multi-mode data fusion | |
CN105659263A (en) | Sequence identification | |
CN113095080B (en) | Theme-based semantic recognition method and device, electronic equipment and storage medium | |
US11574250B2 (en) | Classification of erroneous cell data | |
Hewawasam et al. | Rule mining and classification in a situation assessment application: A belief-theoretic approach for handling data imperfections | |
US10635521B2 (en) | Conversational problem determination based on bipartite graph | |
Zhang et al. | An influence-based approach for root cause alarm discovery in telecom networks | |
CN109446327B (en) | A method and system for diagnosing mobile communication customer complaints | |
CN116739408A (en) | Power grid dispatching safety monitoring method and system based on data tag and electronic equipment | |
Dommati et al. | Bug Classification: Feature Extraction and Comparison of Event Model using Na\" ive Bayes Approach | |
Venkataraman et al. | Towards identifying impacted users in cellular services | |
Tao et al. | Biglog: Unsupervised large-scale pre-training for a unified log representation | |
CN110502432B (en) | Intelligent test method, device, equipment and readable storage medium | |
Jan et al. | A statistical machine learning approach for ticket mining in IT service delivery | |
Mittal et al. | A COMPARATIVE STUDY OF ASSOCIATION RULE MINING TECHNIQUES AND PREDICTIVE MINING APPROACHES FOR ASSOCIATION CLASSIFICATION. | |
Eken et al. | Predicting defects with latent and semantic features from commit logs in an industrial setting | |
Subramanian et al. | A cognitive assistant for risk identification and modeling | |
Zhang et al. | A crowd-AI dynamic neural network hyperparameter optimization approach for image-driven social sensing applications | |
Ma et al. | iLoc: a framework for incremental location-state acquisition and prediction based on mobile sensors | |
Venkataraman et al. | Assessing the impact of network events with user feedback | |
Deb et al. | Discovering latent semantic structure in human mobility traces |