Finding within-organisation spatial information on the web


Autoria(s): Hou, Jun; Schulz, Ruth; Wyeth, Gordon; Nayak, Richi
Contribuinte(s)

Maher, Michael

Thiebaux, Sylvie

Data(s)

04/12/2015

Resumo

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.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/89596/

Relação

http://eprints.qut.edu.au/89596/1/Hou-etal-AuAI15.pdf

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.

http://purl.org/au-research/grants/ARC/DP140103216

Direitos

Copyright 2015 [Please consult the author]

Fonte

School of Electrical Engineering & Computer Science; Science & Engineering Faculty

Palavras-Chave #HTML pattern #Search engine #Spatial information extraction
Tipo

Conference Paper