Building the profile of web events based on website measurement

Xu, Z; Xuan, J; Zhu, Y; Wei, X

Building the profile of web events based on website measurement

Xu, Z Xuan, J

Zhu, Y Wei, X

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Electrical Engineering, 2018, 422 pp. 3 - 10
Issue Date:: 2018-01-01

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Field	Value	Language
dc.contributor.author	Xu, Z	en_US
dc.contributor.author	Xuan, J https://orcid.org/0000-0002-8367-6908	en_US
dc.contributor.author	Zhu, Y	en_US
dc.contributor.author	Wei, X	en_US
dc.date.issued	2018-01-01	en_US
dc.identifier.citation	Lecture Notes in Electrical Engineering, 2018, 422 pp. 3 - 10	en_US
dc.identifier.isbn	9789811031861	en_US
dc.identifier.issn	1876-1100	en_US
dc.identifier.uri	http://hdl.handle.net/10453/133384
dc.description.abstract	© Springer Nature Singapore Pte Ltd. 2018. Nowadays, Web makes it possible to study emergencies from web information due to its real-time, open, and dynamic features. After the emergence of a web event, there will be numerous websites publishing webpages to cover this web event. Measuring temporal features in evolution course of web events can help people timely know and understand which events are emergencies, so harms to the society caused by emergencies can be reduced. In this paper, website preference is formally defined and mined by three proposed strategies which are all explicitly or implicitly based on the three-level networks: website-level, webpage-level and keyword-level. An iterative algorithm is firstly introduced to calculate outbreak power of web events, and increased web pages of events, increased attributes of events, distribution of attributes in web pages and the relationships of attributes are embedded into this iterative algorithm as the variables. By means of prior knowledge, membership grade of web events belong to each type can be calculated, and then the type of web events can be discriminated. Experiments on real data set demonstrate the proposed algorithm is both efficient and effective, and it is capable of providing accurate results of discrimination.	en_US
dc.relation.ispartof	Lecture Notes in Electrical Engineering	en_US
dc.relation.isbasedon	10.1007/978-981-10-3187-8_1	en_US
dc.title	Building the profile of web events based on website measurement	en_US
dc.type	Conference Proceeding
utslib.citation.volume	422	en_US
utslib.for	0806 Information Systems	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	422	en_US

Abstract:

© Springer Nature Singapore Pte Ltd. 2018. Nowadays, Web makes it possible to study emergencies from web information due to its real-time, open, and dynamic features. After the emergence of a web event, there will be numerous websites publishing webpages to cover this web event. Measuring temporal features in evolution course of web events can help people timely know and understand which events are emergencies, so harms to the society caused by emergencies can be reduced. In this paper, website preference is formally defined and mined by three proposed strategies which are all explicitly or implicitly based on the three-level networks: website-level, webpage-level and keyword-level. An iterative algorithm is firstly introduced to calculate outbreak power of web events, and increased web pages of events, increased attributes of events, distribution of attributes in web pages and the relationships of attributes are embedded into this iterative algorithm as the variables. By means of prior knowledge, membership grade of web events belong to each type can be calculated, and then the type of web events can be discriminated. Experiments on real data set demonstrate the proposed algorithm is both efficient and effective, and it is capable of providing accurate results of discrimination.

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http://hdl.handle.net/10453/133384