Abstract
Entity-based applications, such as expert search or online social networks where users search for persons, require high-quality datasets of named entity references. Obtaining such high-quality datasets can be achieved by automatically extracting metadata from Web pages. In this work, we focus on the identification of the named entity that corresponds to the owner of a particular Web page, for example, a home page or an organizational staff Web page. More specifically, from a set of named entities that have already been extracted from a Web page, we identify the one which corresponds to the owner of the home page. First, we develop a set of features which are combined in a scoring function to select the named entity of the Web page owner. Second, we formulate the problem as a classification problem in which a pair of a Web page and named entity is classified as being associated or not. We evaluate the proposed approaches on a set of Web pages in which we have previously identified named entities. Our experimental results show that we can identify the named entity corresponding to the owner of a home page with accuracy over 90%.
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
Preview
Unable to display preview. Download preview PDF.
References
Bikel, D.M., Miller, S., Schwartz, R., Weischedel, R.: Nymble: a high-performance learning name-finder. In: Procs. of the 5th ANLC, pp. 194–201 (1997)
Chang, C.C., Lin, C.J.: Libsvm: A library for support vector machines. ACM Trans. Intell. Syst. Technol. 2, 27:1–27:27 (2011)
Changuel, S., Labroche, N., Bouchon-Meunier, B.: Automatic web pages author extraction. In: Procs. of the 8th FQAS, pp. 300–311 (2009)
Chieu, H.L., Ng, H.T.: Named entity recognition with a maximum entropy approach. In: Procs. of the 7th Conference on Natural Language Learning at HLT-NAACL 2003, CONLL 2003, vol. 4, pp. 160–163 (2003)
Culotta, A., Bekkerman, R., McCallum, A.: Extracting social networks and contact information from email and the web. In: CEAS (2004)
Culotta, A., Wick, M., Hall, R., McCallum, A.: First-order probabilistic models for coreference resolution. In: Procs. of HLT/NAACL, pp. 81–88 (2007)
Finkel, J.R., Grenager, T., Manning, C.: Incorporating non-local information into information extraction systems by gibbs sampling. In: Procs. of the 43rd Annual Meeting on ACL, pp. 363–370 (2005)
Gollapalli, S.D., Giles, C.L., Mitra, P., Caragea, C.: On identifying academic homepages for digital libraries. In: Procs. of the 11th JCDL, pp. 123–132 (2011)
Kato, Y., Kawahara, D., Inui, K., Kurohashi, S., Shibata, T.: Extracting the author of web pages. In: Procs. of the 2nd ACM WICOW, pp. 35–42 (2008)
Lafferty, J.D., McCallum, A., Pereira, F.C.N.: Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In: Procs. of the 18th ICML, pp. 282–289 (2001)
Minkov, E., Wang, R.C., Cohen, W.W.: Extracting personal names from email: applying named entity recognition to informal text. In: Procs. of the Conf. on HLT and EMNLP, HLT 2005, pp. 443–450 (2005)
Ng, V., Cardie, C.: Improving machine learning approaches to coreference resolution. In: Procs. of the 40th Annual Meeting on ACL, ACL 2002, pp. 104–111 (2002)
Shi, Y., Wang, M.: A dual-layer crfs based joint decoding method for cascaded segmentation and labeling tasks. In: Procs. of the 20th IJCAI, pp. 1707–1712 (2007)
Takeuchi, K., Collier, N.: Use of support vector machines in extended named entity recognition. In: Procs. of the 6th Conference on Natural Language Learning, COLING 2002, vol. 20, pp. 1–7 (2002)
Tang, J., Zhang, D., Yao, L.: Social network extraction of academic researchers. In: Procs. of the 7th ICDM, pp. 292–301 (2007)
Zheng, S., Zhou, D., Li, J., Giles, C.L.: Extracting author meta-data from web using visual features. In: Procs. of the 7th ICDMW, pp. 33–40 (2007)
Zhu, J., Nie, Z., Wen, J.R., Zhang, B., Ma, W.Y.: 2d conditional random fields for web information extraction. In: Procs. of the 22nd ICML, pp. 1044–1051 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Plachouras, V., Rivière, M., Vazirgiannis, M. (2012). Named Entity Recognition and Identification for Finding the Owner of a Home Page. In: Tan, PN., Chawla, S., Ho, C.K., Bailey, J. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2012. Lecture Notes in Computer Science(), vol 7301. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30217-6_46
Download citation
DOI: https://doi.org/10.1007/978-3-642-30217-6_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-30216-9
Online ISBN: 978-3-642-30217-6
eBook Packages: Computer ScienceComputer Science (R0)