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
Novelty and redundancy detection in adaptive filtering
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Learning Approaches for Detecting and Tracking News Events
IEEE Intelligent Systems
Topic-conditioned novelty detection
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
A System for new event detection
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Bursty and Hierarchical Structure in Streams
Data Mining and Knowledge Discovery
Simple Semantics in Topic Detection and Tracking
Information Retrieval
Identifying similarities, periodicities and bursts for online search queries
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Using temporal profiles of queries for precision prediction
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Query based event extraction along a timeline
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Parameter free bursty events detection in text streams
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
A web-based kernel function for measuring the similarity of short text snippets
Proceedings of the 15th international conference on World Wide Web
Time-dependent semantic similarity measure of queries using historical click-through data
Proceedings of the 15th international conference on World Wide Web
Event detection from evolution of click-through data
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Continuous keyword search on multiple text streams
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Novelty detection: the TREC experience
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Resource-adaptive real-time new event detection
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Analyzing feature trajectories for event detection
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
New event detection based on indexing-tree and named entity
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Time-dependent event hierarchy construction
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Searching blogs and news: a study on popular queries
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
Predicting the future impact of news events
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
Identify the User's Information Need Using the Current Search Context
International Journal of Enterprise Information Systems
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In this paper, we aim at detecting events of common user interests from huge volume of user-generated content. The degree of interest from common users in an event is evidenced by a significant surge of event-related queries issued to search for documents (e.g., news articles, blog posts) relevant to the event. Taking the stream of queries from users and the stream of documents as input, our proposed framework seamlessly integrates the two streams into a single stream of query profiles. A query profile is a set of documents matching a query at a given time. With the single stream of query profiles, the well-studied techniques in event detection (e.g., incremental clustering) could be easily applied. In our experiments using real data collected from Blog and News search engines respectively, the proposed technique achieved very high event detection accuracy.