TY - GEN
T1 - Measuring the dynamic relatedness between Chinese entities orienting to news corpus
AU - Wang, Zhishu
AU - Yang, Jing
AU - Lin, Xin
PY - 2012
Y1 - 2012
N2 - The related applications are limited due to the static characteristics on existing relatedness calculation algorithms. We proposed a method aiming to efficiently compute the dynamic relatedness between Chinese entity-pairs, which changes over time. Our method consists of three components: using co-occurrence statistics method to mine the co-occurrence information of entities from the news texts, inducing the development law of dynamic relatedness between entity-pairs, taking the development law as basis and consulting the existing relatedness measures to design a dynamic relatedness measure algorithm. We evaluate the proposed method on the relatedness value and related entity ranking. Experimental results on a dynamic news corpus covering seven domains show a statistically significant improvement over the classical relatedness measure.
AB - The related applications are limited due to the static characteristics on existing relatedness calculation algorithms. We proposed a method aiming to efficiently compute the dynamic relatedness between Chinese entity-pairs, which changes over time. Our method consists of three components: using co-occurrence statistics method to mine the co-occurrence information of entities from the news texts, inducing the development law of dynamic relatedness between entity-pairs, taking the development law as basis and consulting the existing relatedness measures to design a dynamic relatedness measure algorithm. We evaluate the proposed method on the relatedness value and related entity ranking. Experimental results on a dynamic news corpus covering seven domains show a statistically significant improvement over the classical relatedness measure.
KW - Co-occurrence statistics
KW - Dynamic relatedness measure
KW - News corpus
UR - https://www.scopus.com/pages/publications/84864915308
U2 - 10.1007/978-3-642-31537-4_49
DO - 10.1007/978-3-642-31537-4_49
M3 - 会议稿件
AN - SCOPUS:84864915308
SN - 9783642315367
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 631
EP - 644
BT - Machine Learning and Data Mining in Pattern Recognition - 8th International Conference, MLDM 2012, Proceedings
T2 - 8th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2012
Y2 - 13 July 2012 through 20 July 2012
ER -