TY - GEN
T1 - A Passage-Level Text Similarity Calculation
AU - Liu, Ming
AU - Zheng, Zihao
AU - Qin, Bing
AU - Liu, Yitong
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - Along with the explosion of web information, information flow service has attracted the attentions of users. In this kind of service, how to measure the similarity between texts and further filter the redundant information collected from multiple sources becomes the key solution to meet user’s desire. One text often mentions several events. The core event mostly decides the main content carried by the text. It should take the pivotal position. For this reason, this paper aims to construct a passage-level event connection graph to model the relations among the events mentioned by one text. The core event can be revealed and is further chosen to measure the similarity between two texts. As shown by experimental results, after measuring text similarity from a passage-level event representation perspective, our unsupervised measuring method acquires superior results than unsupervised methods by a large margin and even comparable results with some popular supervised neuron based methods.
AB - Along with the explosion of web information, information flow service has attracted the attentions of users. In this kind of service, how to measure the similarity between texts and further filter the redundant information collected from multiple sources becomes the key solution to meet user’s desire. One text often mentions several events. The core event mostly decides the main content carried by the text. It should take the pivotal position. For this reason, this paper aims to construct a passage-level event connection graph to model the relations among the events mentioned by one text. The core event can be revealed and is further chosen to measure the similarity between two texts. As shown by experimental results, after measuring text similarity from a passage-level event representation perspective, our unsupervised measuring method acquires superior results than unsupervised methods by a large margin and even comparable results with some popular supervised neuron based methods.
KW - Event connection graph
KW - Passage-level event representation
KW - Text similarity calculation
KW - Vector tuning
UR - https://www.scopus.com/pages/publications/85093090991
U2 - 10.1007/978-3-030-60450-9_17
DO - 10.1007/978-3-030-60450-9_17
M3 - 会议稿件
AN - SCOPUS:85093090991
SN - 9783030604493
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 207
EP - 218
BT - Natural Language Processing and Chinese Computing - 9th CCF International Conference, NLPCC 2020, Proceedings
A2 - Zhu, Xiaodan
A2 - Zhang, Min
A2 - Hong, Yu
A2 - He, Ruifang
PB - Springer Science and Business Media Deutschland GmbH
T2 - 9th CCF International Conference on Natural Language Processing and Chinese Computing, NLPCC 2020
Y2 - 14 October 2020 through 18 October 2020
ER -