Abstract
This paper studies cold start Cumulative Citation Recommen dation (CCR) for Knowledge Base Acceleration (KBA), whose objective is to detect potential citations for target entities without existing KB entries from a volume of stream documents. Unlike routine CCR, in which target entities are identified by a reference KB, cold start CCR is more common since lots of less popular entities do not have any KB entry in practice. We propose a two-step strategy to address this problem: (1) event-based sentence clustering and (2) document ranking. In addition, to build effective rankers, we develop three kinds of features based on the clustering results: time range, local profile and action pattern. Empirical studies on TREC-KBA-2014 dataset demonstrate the effectiveness of the proposed strategy and the novel features.
This work was done when the first author was visiting Microsoft Research Asia.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Balog, K., Ramampiaro, H.: Cumulative citation recommendation: classification vs. ranking. In: SIGIR, pp. 941–944. ACM (2013)
K. Balog, H. Ramampiaro, N. Takhirov, and K. Nørvåg.: Multi-step classification approaches to cumulative citation recommendation. In: OAIR, pp. 121–128. ACM (2013)
Bonnefoy, L., Bouvier, V., Bellot, P.: A weakly-supervised detection of entity central documents in a stream. In: SIGIR, pp. 769–772. ACM (2013)
Fader, A., Soderland, S., Etzioni, O.: Identifying relations for open information extraction. In: EMNLP, pp. 1535–1545. ACL (2011)
Frank, J.R., Kleiman-Weiner, M., Roberts, D.A., Niu, F., Zhang, C., Re, C., Soboroff, I.: Building an entity-centric stream filtering test collection for TREC 2012. In: TREC, NIST (2012)
Frank, J.R., Kleiman-Weiner, M., Roberts, D.A., Voorhees, E., Soboroff, I.: Evaluating stream filtering for entity profile updates in TREC 2012, 2013, and 2014. In: TREC, NIST (2014)
Robertson, S.E., Soboroff, I.: The TREC 2002 filtering track report. In: TREC, NIST (2002)
Wang, J., Song, D., Lin, C.-Y., Liao, L.: BIT and MSRA at TREC KBA CCR track 2013. In: TREC, NIST (2013)
Wang, J., Song, D., Wang, Q., Zhang, Z., Si, L., Liao, L., Lin, C.-Y.: An entity class-dependent discriminative mixture model for cumulative citation recommendation. SIGIR 2015, 635–644 (2015)
Acknowledgement
The authors would like to thank Jing Liu for his valuable suggestions and the anonymous reviewers for their helpful comments. This work is funded by the National Program on Key Basic Research Project (973 Program, Grant No. 2013CB329600), National Natural Science Foundation of China (NSFC, Grant Nos. 61472040 and 60873237), and Beijing Higher Education Young Elite Teacher Project (Grant No. YETP1198).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Wang, J., Jiang, J., Liao, L., Song, D., Zhang, Z., Lin, CY. (2016). Cold Start Cumulative Citation Recommendation for Knowledge Base Acceleration. In: Ferro, N., et al. Advances in Information Retrieval. ECIR 2016. Lecture Notes in Computer Science(), vol 9626. Springer, Cham. https://doi.org/10.1007/978-3-319-30671-1_63
Download citation
DOI: https://doi.org/10.1007/978-3-319-30671-1_63
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-30670-4
Online ISBN: 978-3-319-30671-1
eBook Packages: Computer ScienceComputer Science (R0)