PAT-tree-based keyword extraction for Chinese information retrieval
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
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
KEA: practical automatic keyphrase extraction
Proceedings of the fourth ACM conference on Digital libraries
Automatic generation of overview timelines
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Combining semantic and syntactic document classifiers to improve first story detection
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Chinese keyword extraction based on max-duplicated strings of the documents
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Learning Algorithms for Keyphrase Extraction
Information Retrieval
A System for new event detection
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion 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
Integrating word relationships into language models
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
Keyphrase Extraction Using Semantic Networks Structure Analysis
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Using query contexts in information retrieval
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
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
Automatic online news issue construction in web environment
Proceedings of the 17th international conference on World Wide Web
Using Burstiness to Improve Clustering of Topics in News Streams
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Automatic online news topic ranking using media focus and user attention based on aging theory
Proceedings of the 17th ACM conference on Information and knowledge management
Context-dependent term relations for information retrieval
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Domain-specific keyphrase extraction
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Automatic keyphrase extraction from chinese news documents
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
Automatic keyphrase extraction from scientific articles
Language Resources and Evaluation
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News Topics are related to a set of keywords or keyphrases. Topic keyphrases briefly describe the key content of topics and help users decide whether to do further reading about them. Moreover, keyphrases of a news topic can be considered as a cluster of related terms, which provides term relationship information that can be integrated into information retrieval models. In this paper, an automatic online news topic keyphrase extraction system is proposed. News stories are organized into topics. Keyword candidates are firstly extracted from single news stories and filtered with topic information. Then a phrase identification process combines keywords into phrases using position information. Finally, the phrases are ranked and top ones are selected as topic keyphrases. Experiments performed on practical Web datasets show that the proposed system works effectively, with a performance of precision=70.61% and recall=67.94%.