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
Clustering user queries of a search engine
Proceedings of the 10th international conference on World Wide Web
Retrieving and organizing web pages by “information unit”
Proceedings of the 10th international conference on World Wide Web
Probabilistic query expansion using query logs
Proceedings of the 11th international conference on World Wide Web
Topic Extraction from News Archive Using TF*PDF Algorithm
WISE '02 Proceedings of the 3rd International Conference on Web Information Systems Engineering
Bursty and hierarchical structure in streams
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Topic-conditioned novelty detection
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Web unit mining: finding and classifying subgraphs of web pages
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Identifying similarities, periodicities and bursts for online search queries
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Text classification and named entities for new event detection
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Hourly analysis of a very large topically categorized web query log
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
A probabilistic model for retrospective news event detection
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Web-page summarization using clickthrough data
Proceedings of the 28th 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
Data association for topic intensity tracking
ICML '06 Proceedings of the 23rd international conference on Machine learning
Event detection from evolution of click-through data
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Using names and topics for new event detection
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Analyzing feature trajectories for event detection
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Random walks on the click graph
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Extracting semantic relations from query logs
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Exact indexing of dynamic time warping
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Top-Down Parameter-Free Clustering of High-Dimensional Categorical Data
IEEE Transactions on Knowledge and Data Engineering
Using the wisdom of the crowds for keyword generation
Proceedings of the 17th international conference on World Wide Web
DECK: Detecting Events from Web Click-Through Data
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Mining rich session context to improve web search
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Named entity mining from click-through data using weakly supervised latent dirichlet allocation
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
The automatic creation of literature abstracts
IBM Journal of Research and Development
Detecting hot events from web search logs
WAIM'10 Proceedings of the 11th international conference on Web-age information management
Event-Driven document selection for terrorism information extraction
ISI'05 Proceedings of the 2005 IEEE international conference on Intelligence and Security Informatics
Hi-index | 0.00 |
Recent years have witnessed increased efforts on detecting topics and events from Web search logs, since this kind of data not only capture web content but also reflect the users’ activities. However, the majority of existing work is focused on exploiting clustering techniques for topic and event detection. Due to the huge size and the evolving nature of Web data, existing clustering approaches are limited to meet the real-time demand. To that end, in this article, we propose a method called LETD to detect evolving topics in a timely manner. Also, we design the techniques to extract events from topics and to infer the evolving relationship among the events. For topic detection, we first provide a measurement to select the important URLs, which are most likely to describe a real-life topic. Then, starting from these selected URLs, we exploit the local expansion method to find other topic-related URLs. Moreover, in the LETD framework, we design algorithms based on Random Walk and Markov Random Fields (MRF), respectively. Because the LETD method exploits a divide-and-conquer strategy to process the data, it is more efficient than existing methods based on clustering techniques. To better illustrate the LETD framework, we develop a demo system StoryTeller which can discover hot topics and events, infer the evolving relationships among events, and visualize information in a storytelling way. This demo system can provide a global view of the topic development and help users target the interesting events more conveniently. Finally, experimental results on real-world Microsoft click-through data have shown that StoryTeller can find real-life hot topics and meaningful evolving relationships among events, and has also demonstrated the efficiency and effectiveness of the LETD method.