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Datainsamling med Web Usage Mining: Lagringsstrategier för loggning av serverdata
University of Skövde, School of Informatics.
2014 (Swedish)Independent thesis Basic level (degree of Bachelor), 20 credits / 30 HE creditsStudent thesisAlternative title
Data Collection with Web Usage Mining : Storage strategies for logging server side data (English)
Abstract [sv]

Webbapplikationers komplexitet och mängden avancerade tjänster ökar. Loggning av aktiviteter kan öka förståelsen över användares beteenden och behov, men används i för stor mängd utan relevant information. Mer avancerade system medför ökade krav för prestandan och loggning blir än mer krävande för systemen. Det finns behov av smartare system, utveckling inom tekniker för prestandaförbättringar och tekniker för datainsamling. Arbetet kommer undersöka hur svarstider påverkas vid loggning av serverdata, enligt datainsamlingsfasen i web usage mining, beroende på lagringsstrategier. Hypotesen är att loggning kan försämra svarstider ytterligare. Experiment genomförs där fyra olika lagringsstrategier används för att lagra serverdata med olika tabell- och databasstrukturer, för att se vilken strategi som påverkar svarstiderna minst. Experimentet påvisar statistiskt signifikant skillnad mellan lagringsstrategierna enligt ANOVA. Lagringsstrategi 4 påvisar bäst effekt för prestandans genomsnittliga svarstid, jämfört med lagringsstrategi 2 som påvisar mest negativ effekt för den genomsnittliga svarstiden. Framtida arbete vore intressant för att stärka resultaten.

Abstract [en]

Web applications complexity and the amount of advanced services increases. Logging activities can increase the understanding of users behavior and needs, but is used too much without relevant information. More advanced systems brings increased requirements for performance and logging becomes even more demanding for the systems. There is need of smarter systems, development within the techniques for performance improvements and techniques for data collection. This work will investigate how response times are affected when logging server data, according to the data collection phase in web usage mining, depending on storage strategies. The hypothesis is that logging may degrade response times even further. An experiment was conducted in which four different storage strategies are used to store server data with different table- and database structures, to see which strategy affects the response times least. The experiment proves statistically significant difference between the storage strategies with ANOVA. Storage strategy 4 proves the best effect for the performance average response time compared with storage strategy 2, which proves the most negative effect for the average response time. Future work would be interesting for strengthening the results.

Place, publisher, year, edition, pages
2014. , 52 p.
Keyword [en]
Data Collection, Web Usage Mining, Storage strategies, Logging, Server side data, Response time, ANOVA
Keyword [sv]
Datainsamling, Lagringsstrategi, Lagringsstrategier, Loggning, Serverdata, Svarstider, ANOVA
National Category
Computer Science
Identifiers
URN: urn:nbn:se:his:diva-9467OAI: oai:DiVA.org:his-9467DiVA: diva2:725030
Subject / course
Computer Science
Educational program
Web Developer - Programming
Supervisors
Examiners
Available from: 2014-08-14 Created: 2014-06-14 Last updated: 2014-08-14Bibliographically approved

Open Access in DiVA

Datainsamling med Web Usage Mining(4988 kB)274 downloads
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File name FULLTEXT01.pdfFile size 4988 kBChecksum SHA-512
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Type fulltextMimetype application/pdf

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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Language
  • de-DE
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  • Other locale
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Output format
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