Improving text categorization methods for event tracking
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Temporal summaries of new topics
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Learning Approaches for Detecting and Tracking News Events
IEEE Intelligent Systems
Beyond independent relevance: methods and evaluation metrics for subtopic retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Fast discovery of connection subgraphs
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Event threading within news topics
Proceedings of the thirteenth ACM international conference on Information and knowledge management
NewsInEssence: summarizing online news topics
Communications of the ACM - The digital society
A Recursive Greedy Algorithm for Walks in Directed Graphs
FOCS '05 Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science
Cost-effective outbreak detection in networks
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning from labeled features using generalized expectation criteria
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Turning down the noise in the blogosphere
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Connecting the dots between news articles
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
The web of topics: discovering the topology of topic evolution in a corpus
Proceedings of the 20th international conference on World wide web
Unified analysis of streaming news
Proceedings of the 20th international conference on World wide web
Evolutionary timeline summarization: a balanced optimization framework via iterative substitution
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Discovering diverse and salient threads in document collections
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
TUT: a statistical model for detecting trends, topics and user interests in social media
Proceedings of the 21st ACM international conference on Information and knowledge management
Towards topics-based, semantics-assisted news search
Proceedings of the 3rd International Conference on Web Intelligence, Mining and Semantics
Information cartography: creating zoomable, large-scale maps of information
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Structured summarization for news events
Proceedings of the 22nd international conference on World Wide Web companion
NIFTY: a system for large scale information flow tracking and clustering
Proceedings of the 22nd international conference on World Wide Web
Penguins in sweaters, or serendipitous entity search on user-generated content
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
ESTHETE: a news browsing system to visualize the context and evolution of news stories
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Socially motivated multimedia topic timeline summarization
Proceedings of the 2nd international workshop on Socially-aware multimedia
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When information is abundant, it becomes increasingly difficult to fit nuggets of knowledge into a single coherent picture. Complex stories spaghetti into branches, side stories, and intertwining narratives. In order to explore these stories, one needs a map to navigate unfamiliar territory. We propose a methodology for creating structured summaries of information, which we call metro maps. Our proposed algorithm generates a concise structured set of documents maximizing coverage of salient pieces of information. Most importantly, metro maps explicitly show the relations among retrieved pieces in a way that captures story development. We first formalize characteristics of good maps and formulate their construction as an optimization problem. Then we provide efficient methods with theoretical guarantees for generating maps. Finally, we integrate user interaction into our framework, allowing users to alter the maps to better reflect their interests. Pilot user studies with a real-world dataset demonstrate that the method is able to produce maps which help users acquire knowledge efficiently.