Paper: Identifying Non-Explicit Citing Sentences for Citation-Based Summarization.

ACL ID P10-1057
Title Identifying Non-Explicit Citing Sentences for Citation-Based Summarization.
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2010
Authors

Identifying background (context) informa- tion in scientific articles can help schol- ars understand major contributions in their research area more easily. In this paper, we propose a general framework based on probabilistic inference to extract such context information from scientific papers. We model the sentences in an article and their lexical similarities as a Markov Ran- dom Field tuned to detect the patterns that context data create, and employ a Belief Propagation mechanism to detect likely context sentences. We also address the problem of generating surveys of scien- tific papers. Our experiments show greater pyramid scores for surveys generated us- ing such context information rather than citation sentences alone.