Computer systems that learn: classification and prediction methods from statistics, neural nets, machine learning, and expert systems
Rule induction with CN2: some recent improvements
EWSL-91 Proceedings of the European working session on learning on Machine learning
Classifying news stories using memory based reasoning
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
C4.5: programs for machine learning
C4.5: programs for machine learning
Automated learning of decision rules for text categorization
ACM Transactions on Information Systems (TOIS)
An example-based mapping method for text categorization and retrieval
ACM Transactions on Information Systems (TOIS)
Information extraction as a basis for high-precision text classification
ACM Transactions on Information Systems (TOIS)
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Some advances in transformation-based part of speech tagging
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
A comparison of classifiers and document representations for the routing problem
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Cluster-based text categorization: a comparison of category search strategies
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Translating collocations for bilingual lexicons: a statistical approach
Computational Linguistics
Combining classifiers in text categorization
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Context-sensitive learning methods for text categorization
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Feature selection, perceptron learning, and a usability case study for text categorization
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Ontology-based extraction and structuring of information from data-rich unstructured documents
Proceedings of the seventh international conference on Information and knowledge management
Inductive learning algorithms and representations for text categorization
Proceedings of the seventh international conference on Information and knowledge management
Environmental scanning and information systems in relation to success in introducing new products
Information and Management
A study of retrospective and on-line event detection
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
On-line new event detection and tracking
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Using a generalized instance set for automatic text categorization
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Distributional clustering of words for text classification
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Information management for the intelligent organization (2nd ed.): the art of scanning the environment
Context-sensitive learning methods for text categorization
ACM Transactions on Information Systems (TOIS)
Learning Information Extraction Rules for Semi-Structured and Free Text
Machine Learning - Special issue on natural language learning
A re-examination of text categorization methods
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Learning Approaches for Detecting and Tracking News Events
IEEE Intelligent Systems
Maximizing Text-Mining Performance
IEEE Intelligent Systems
Machine Learning
Machine Learning
A simple rule-based part of speech tagger
ANLC '92 Proceedings of the third conference on Applied natural language processing
Scanning world wide web documents with the vector space model
Decision Support Systems
Identifying and characterizing public science-related fears from RSS feeds: Research Articles
Journal of the American Society for Information Science and Technology
Mining the change of event trends for decision support in environmental scanning
Expert Systems with Applications: An International Journal
Preserving User Preferences in Automated Document-Category Management: An Evolution-Based Approach
Journal of Management Information Systems
Discovering event episodes from news corpora: a temporal-based approach
Proceedings of the 11th International Conference on Electronic Commerce
Automatic online news monitoring and classification for syndromic surveillance
Decision Support Systems
Detecting News Event from a Citizen Journalism Website Using Tags
AMT '09 Proceedings of the 5th International Conference on Active Media Technology
Making words work: Using financial text as a predictor of financial events
Decision Support Systems
Social tags as news event detectors
Journal of Information Science
Cross-lingual text categorization: Conquering language boundaries in globalized environments
Information Processing and Management: an International Journal
Event-Driven document selection for terrorism information extraction
ISI'05 Proceedings of the 2005 IEEE international conference on Intelligence and Security Informatics
Exploiting poly-lingual documents for improving text categorization effectiveness
Decision Support Systems
More applicable environmental scanning systems leveraging "modern" information systems
Information Systems and e-Business Management
Hi-index | 0.00 |
Environmental scanning, the acquisition and use of the information about events, trends, and relationships in an organization's external environment, permits an organization to adapt to its environment and to develop effective responses to secure or improve the organization's position in the future, Event detection technique that identifies the onset of new events from streams of news stories would facilitate the process of organization's environmental scanning. However, traditional event detection techniques generally adopted the feature co-occurrence approach that identifies whether a news story contains an unseen event by comparing the similarity of features between the new story and past news stories. Such feature-based event detection techniques greatly suffer from the word mismatch and inconsistent orientation problems and do not directly support event categorization and news stories filtering. In this study, we developed an information extraction-based event detection (NEED) technique that combines information extraction and text categorization techniques to address the problems inherent to traditional feature-based event detection techniques. Using a traditional feature-based event detection technique (i.e., INCR) as benchmarks, the empirical evaluation results showed that the proposed NEED technique improved the effectiveness of event detection measured by the tradeoff between miss and false alarm rates.