Finding within-organisation spatial information on the web
Hou, Jun, Schulz, Ruth, Wyeth, Gordon, & Nayak, Richi (2015) Finding within-organisation spatial information on the web. In Maher, Michael & Thiebaux, Sylvie (Eds.) 28th Australasian Joint Conference on Artificial Intelligence (AI 2015), 30 November – 4 December 2015, Canberra, A.C.T.
Information available on company websites can help people navigate to the offices of groups and individuals within the company. Automatically retrieving this within-organisation spatial information is a challenging AI problem This paper introduces a novel unsupervised pattern-based method to extract within-organisation spatial information by taking advantage of HTML structure patterns, together with a novel Conditional Random Fields (CRF) based method to identify different categories of within-organisation spatial information. The results show that the proposed method can achieve a high performance in terms of F-Score, indicating that this purely syntactic method based on web search and an analysis of HTML structure is well-suited for retrieving within-organisation spatial information.
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|Item Type:||Conference Paper|
|Keywords:||HTML pattern, Search engine, Spatial information extraction|
|Divisions:||Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2015 [Please consult the author]|
|Deposited On:||29 Oct 2015 02:59|
|Last Modified:||18 Dec 2015 03:44|
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