Title :
Topic Detection and Tracking for Chinese News Web Pages
Author :
Qiu, Jing ; Liao, Lejian ; Dong, Xiujie
Author_Institution :
Sch. of Comput. Sci., Beijing Inst. of Technol., Beijing
Abstract :
With the continuous growth in the number of available Web news sites and the diversity in their presentation of content, there is an increasing need in mining the news correlation on the Web to keep tracking of successive development of specific event. In this paper a new approach of topic tracking of Chinese news Web pages is presented. Temporal information extracted from news texts and "key Web contexts" extracted from HTML documents is used to improve the performance of dependency structure language model (DSLM). Experimental results are examined that shows the usefulness of our approach.
Keywords :
Web sites; information retrieval; Chinese news Web pages; HTML documents; Web news correlation mining; Web news sites; dependency structure language model; key Web contexts; news texts; temporal information extraction; topic detection; Computer science; Context modeling; Data mining; Electronic mail; Event detection; HTML; Information technology; Laboratories; Natural languages; Web pages; Topic tracking; content extraction; dependency structure language model; temporal information extraction;
Conference_Titel :
Advanced Language Processing and Web Information Technology, 2008. ALPIT '08. International Conference on
Conference_Location :
Dalian Liaoning
Print_ISBN :
978-0-7695-3273-8
DOI :
10.1109/ALPIT.2008.31
