Topic tracking with time granularity reasoning

ACM Transactions on Asian Language Information Processing

Volumn 5, Issue 4, 2006, Pages 388-412

  Li, Baoli ^a,b   Li, Wenjie ^a   Lu, Qin ^a  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^b Georgia Institute of Technology   (United States)

Author keywords

Event tracking; Time granularity; Time reasoning; Topic detection and tracking; Topic tracking

Indexed keywords

EVENT TRACKING; TIME GRANULARITY; TIME REASONING; TOPIC DETECTION AND TRACKING (TDT);

ALGORITHMS; FEATURE EXTRACTION; INFORMATION SYSTEMS; INFORMATION USE; LOGIC PROGRAMMING;

INFORMATION RETRIEVAL;

EID: 34147203258     PISSN: 15300226     EISSN: 15583430     Source Type: Journal    
DOI: 10.1145/1236181.1236186     Document Type: Article

References (30)

1. ALLAN, J., CARBONELL, J., DODDINGTON, G., YAMRON, J., AND YANG, Y. 1998a. Topic detection and tracking pilot study: Final report. In Proceedings of the DARPA Broadcast News Transcription and Understanding Workshop.
2. ALLAN, J., PAPKA, R., AND LAVRENKO, V. 1998b. Online new event detection and tracking. In Proceedings of the 21st ACM SIGIR International Conference on Research and Development in Information Retrieval (SIGIR'98). 37-45.
3. ALLAN, J., JIN, H., RAJMAN, M., WAYNE, C., GILDEA, D., LAVRENKO, V., HOBEHMAN, R., AND CAPUTO, D. 1999. Topic Based Novelty Detection - 1999 Summer Workshop at CLSP Final Report.
4. ALLAN, J. (ed.). 2002. Topic Detection and Tracking: Event-based Information Organization, Kluwer Academic Publishers.
5. BETTINI, C., JAJODIA, S., AND WANG, S. X. 2000. Time Granularities in Databases, Data Mining, and Temporal Reasoning. Springer-Verlag Press, Berlin, Germany.
6. BETTINI, C. 2001. An investigation of time granularity. Bull. Italian Ass. AI (Special Issue on Management of Temporal Information). .XIV, 1 (March).
7. BRANTS, T., CHEN, F., AND FARAHAT, A. 2003. A system for new event detection. In Proceedings of the 26th International Conference on Research and Development in Information Retrieval (SIGIR'03). 330-337.
8. BRAUN, R. K. and KANESHIRO, R. 2003. Exploring topic pragmatics for new event detection in TDT-2003. In Proceedings of the Topic Detection and Tracking Workshop (Nov.) Gaithersburg, MD, 17-18.
9. CARBONELL, J., YANG, Y., LAFFERTY, J., BROWN, R. D., PIERCE, T., AND LIU, X. 1999. CMU report on TDT-2: Segmentation, detection and tracking. In Proceedings of the DARPA Broadcast News Workshop. San Francisco, CA, 117-120.
10. COMBI, C., FRANCESCHET, M., AND PERON, A. 2004. Representing and reasoning about temporal granularities. J. Logic Compu. 14, 1, 51-77.
11. FERRO, L., GERBER, L., MANI, I., SUNDHEIM, B., AND WILSON, G. 2005. TIDES: 2005 Standard for the Annotation of Temporal Expressions. Available at http://timex2.mitre.org/index.htm.
12. FRANZ, M., ITTYCHERIAH, A., MCCARLEY J. S., AND WARD, T. 2001. First story detection: Combining similarity and novelty-based approaches. S. TDT 2001 Workshop. IBM.
13. GORALWALLA, I. A., LEONTIEV, Y., Özsu, M. T., SZAFRON, D., AND COMBI, C. 2001. Temporal granularity: Completing the puzzle. J. Intelli. Inform. Syst. 16, 41-63.
14. HUNTER, A. 2002. Merging structured text using temporal knowledge. J. Data Knowl. Engin. 41, 29-66.
15. KIM, P. et al. 2003. Extracting temporal information from Korean news articles for event detection and tracking. In Proceedings of the 20th International Conference on Computer Processing of Oriental Languages. 392-401.
16. KIM, P. and MYAENG, S. H. 2004. Usefulness of temporal information automatically extracted from news articles for topic tracking. ACM Trans. Asian Lang. Inform, Process. 3, 4, 227-242.
17. KLEINBERG, J. 2002. Bursty and hierarchical structure in streams. In Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery in Data Mining (SIGKDD'02). 91-101.
18. KUMARAN, G. and ALLAN, J. 2004. Text classification and named entities for new event detection. In Proceedings of the 27th International Conference on Research and Development in Information Retrieval (SIGIR'04). 297-304.
19. LARKEY, L. S., FENG, F., CONNELL, M., AND LAVRENKO, V. 2004. Language-specific models in multilingual topic tracking. In Proceedings of the 27th International Conference on Research and Development in Information Retrieval (SIGIR'04). 402-409.
20. LI, B. 2003. Studies on topic tracking and detection in Chinese news stories. Ph.D. thesis, Department of Computer Science and Technology, Peking University, Beijing, China (June).
21. LI, B., LI, W., LU, Q., AND WU, M. 2005. Profile-based event tracking. In: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'05). 631-632.
22. MAKKONEN, J. AND AHONEN-MYKA, H. 2003. Utilizing temporal information in topic detection and tracking. In Proceedings of 7th European Conference on Research and Advanced Technology for Digital Libraries (ECDL'03). 393-404.
23. MAKKONEN, J., AHONEN-MYKA, H., AND SALMENKIVI, M. 2004. Simple semantics in topic detection and tracking. Inform. Retriev. 7, 347-368.
24. MEI, Q. AND ZHAI, C. 2005. Discovering evolutionary theme patterns from text: An exploration of temporal text mining. In Proceedings of the 11th ACM SIGKDD International Conference on Knowledge Discovery in Data Mining (SIGKDD'05). 198-207.
25. NIST. 2004. The 2004 Topic Detection and Tracking (TDT2004) Task Definition and Evaluation Plan. Available at http://www.nist.gov/ speech/tests/tdt/tdt2004/.
26. SALTON, G. 1989. Automatic Text Processing: The Transformation, Analysis, and Retrieval of Information by Computer. Addison-Wesley, Reading, PA.
27. SALTON, G., WONG, A., AND YANG, C. S. 1975. A vector space model for automatic indexing. Comm. ACM 18, 11, 613-620.
28. WITTEN, I. H. AND FRANK, E. 2000. Data Mining: Practical Machine Learning Tools with Java Implementations. Morgan Kaufmann, San Francisco, CA.
29. YANG, Y., PIERCE, T., AND CARBONELL, J. 1998. A study on retrospective and online event detection. In Proceedings of the 21st ACM SIGIR International Conference on Research and Development in Information Retrieval (SIGIR'98). 28-36.
30. YANG, Y., CARBONELL, J., BROWN, R., PIERCE, T., ARCHIBALD, B. T., AND LIU, X. 1999. Learning approaches for detecting and tracking news events. IEEE Intell. Syst. 14, 4, 32-43.