Topic-conditioned novelty detection
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Simple Semantics in Topic Detection and Tracking
Information Retrieval
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
Query based event extraction along a timeline
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Event threading within news topics
Proceedings of the thirteenth ACM international conference on Information and knowledge management
A probabilistic model for retrospective news event detection
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
An Adaptation of the Vector-Space Model for Ontology-Based Information Retrieval
IEEE Transactions on Knowledge and Data Engineering
Proximity-based document representation for named entity retrieval
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Measuring Semantic Similarity between Named Entities by Searching the Web Directory
WI '07 Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence
Storyline-based summarization for news topic retrospection
Decision Support Systems
Exploring Combinations of Ontological Features and Keywords for Text Retrieval
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Bilingual news clustering using named entities and fuzzy similarity
TSD'07 Proceedings of the 10th international conference on Text, speech and dialogue
Connecting the dots between news articles
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
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
LRD: latent relation discovery for vector space expansion and information retrieval
WAIM '06 Proceedings of the 7th international conference on Advances in Web-Age Information Management
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Large amounts of information about news events are published on the Internet every day in online newspapers. While search engines like Google help retrieve information using keywords, the large volumes of unstructured search results returned by search engines make it hard to track the evolution of an event. A story chain is composed of a set of news articles that coherently connect together to help answer the question of how event A is related to event B. Previous algorithms for finding story chains do not utilize the fact that news events are composed of "Who", "What", "Where" and "When". In this paper, we extract structured information from unstructured news articles so that every news article is represented as a multi-dimensional event profile. News article relevance is computed base on the event profile. An improved story chain algorithm is further proposed based on the new relevance measure. Experimental results show that the proposed article representation can help to find relevant news articles and our proposed algorithm can generate better story chains.