Web Usage Mining by Means of Multidimensional Sequence Alignment Methods

Hay, Birgit; Wets, Geert; Vanhoof, Koen

doi:10.1007/978-3-540-39663-5_4

Cited by 6 publications

(2 citation statements)

References 15 publications

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“…As mentioned above, Xiao et al, [34] compared different representation schemes, and Kumar et al, [5] [6] and Hay et al, [30] compared performances of their proposed method with another method or distance. Shahabi et al, [41] conducted an experiment to evaluate the performance of their path mining method that fully considers Web users' navigation path and viewing time.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Users’ Web Navigation Behavior using GRPA with Variable Length Markov Chains

Madhuri¹,

Chandulal²,

Ramya³

et al. 2011

IJDKP

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Section: Introductionmentioning

confidence: 99%

Analysis of Users’ Web Navigation Behavior using GRPA with Variable Length Markov Chains

Madhuri¹,

Chandulal²,

Ramya³

et al. 2011

IJDKP

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“…If the behavior is standardized enough, the succession of acts in the sequence is stereotyped within a taxon and the criterion of position can be fully applied for comparison among different individuals and taxa (Baerends, 1958; Tinbergen, 1963; Wenzel, 1992). In this respect, some algorithms of sequence alignment have been applied tentatively for non‐phylogenetic classification and comparisons of sequences (Abbott, 1995; Wilson et al., 1999; Hay et al., 2003; van der Aalst et al., 2003).…”

mentioning

confidence: 99%

Phylogenetic analysis and alignment of behavioral sequences by direct optimization

et al. 2006

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We propose a new approach to consider behavioral data in phylogenetic analyses. We show that behavior can be described as sequences of repeated units, and that these behavioral sequences can be analyzed under direct optimization in a way similar to molecular data. This approach provides repeatable hypotheses of homology for behavior when traditional criteria result in multiple alternatives or do not allow to propose any. We exemplify this approach by analyzing the calling songs of the North American Gryllus species under direct optimization. We first use two alternative coding schemes to describe the temporal patterns of the songs as sequences of repeated simple behaviors. We submit these behavioral data to phylogenetic analysis under direct optimization, first as separate analyses, and second in combination with molecular data and additional acoustic characters. The results show that the coding option that consists of discretizing the silent parts of the songs: (1) allows description of the songs in a more precise way; (2) discriminates further the songs between species; and (3) enhances the phylogenetic content of the behavioral sequences. Our study demonstrates that behavioral sequences can be transformed so that they can be used in genuine phylogenetic analysis, in isolation or combined with other data sets. We discuss how this approach may provide phylogenetic signal where none or little is usually available, and the applications to the study of the evolution of behavioral evolution.

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Identification of Underestimated and Overestimated Web Pages Using PageRank and Web Usage Mining Methods

Kapusta

Munk

Drlík

2015

Transactions on Computational Collective Intelligence XVIII

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Web Usage Mining by Means of Multidimensional Sequence Alignment Methods

Cited by 6 publications

References 15 publications

Analysis of Users’ Web Navigation Behavior using GRPA with Variable Length Markov Chains

Analysis of Users’ Web Navigation Behavior using GRPA with Variable Length Markov Chains

Phylogenetic analysis and alignment of behavioral sequences by direct optimization

Identification of Underestimated and Overestimated Web Pages Using PageRank and Web Usage Mining Methods

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