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
The use of MMR, diversity-based reranking for reordering documents and producing summaries
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
An Algorithm that Learns What‘s in a Name
Machine Learning - Special issue on natural language learning
First story detection in TDT is hard
Proceedings of the ninth international conference on Information and knowledge management
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
Topic-conditioned novelty detection
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
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
Retrieval and novelty detection at the sentence level
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
A System for new event detection
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Syntactic features in question answering
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Evaluating question-answering techniques in Chinese
HLT '01 Proceedings of the first international conference on Human language technology research
First story detection using a composite document representation
HLT '01 Proceedings of the first international conference on Human language technology research
Novelty detection based on sentence level patterns
Proceedings of the 14th ACM international conference on Information and knowledge management
Minimal document set retrieval
Proceedings of the 14th ACM international conference on Information and knowledge management
An information-pattern-based approach to novelty detection
Information Processing and Management: an International Journal
Discovering unexpected documents in corpora
Knowledge-Based Systems
Finding support sentences for entities
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Efficient set-correlation operator inside databases
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
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
Ranking related news predictions
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Arabic news: topic and novelty detection
Proceedings of the 3rd International Conference on Information and Communication Systems
Comparative document summarization via discriminative sentence selection
ACM Transactions on Knowledge Discovery from Data (TKDD)
Comparative Document Summarization via Discriminative Sentence Selection
ACM Transactions on Knowledge Discovery from Data (TKDD)
Sequential Summarization: A Full View of Twitter Trending Topics
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
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The detection of new information in a document stream is an important component of many potential applications. In this work, a new novelty detection approach based on the identification of sentence level information patterns is proposed. First, the information-pattern concept for novelty detection is presented with the emphasis on new information patterns for general topics (queries) that cannot be simply turned into specific questions whose answers are specific named entities (NEs). Then we elaborate a thorough analysis of sentence level information patterns on data from the TREC novelty tracks, including sentence lengths, named entities, sentence level opinion patterns. This analysis provides guidelines in applying those patterns in novelty detection particularly for the general topics. Finally, a unified pattern-based approach is presented to novelty detection for both general and specific topics. The new method for dealing with general topics will be the focus. Experimental results show that the proposed approach significantly improves the performance of novelty detection for general topics as well as the overall performance for all topics from the 2002-2004 TREC novelty tracks.