Ontology-Based Filtering Mechanisms for Web Usage Patterns Retrieval

Vanzin, Mariângela; Becker, Karin; Ruiz, Duncan D.

doi:10.1007/11545163_27

Cited by 11 publications

(4 citation statements)

References 11 publications

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“…Nowadays, there is a rapidly expanding research trend that focuses on incorporating domain knowledge and ontologies into the the pattern mining process [16,5]. Yet there is no equivalent ot our study in the literature since the existing approaches merely focus on the taxonomic backbone of the ontology while possible domain relations and inter-object links are ignored.…”

Section: Patterns and Domain Knowledgementioning

confidence: 94%

“…A recent trend in WUM and log mining research has put the emphasis on the application of ontologies to the mining process [3,4,5,3]. Yet the content domain ontologies in these studies share a common limitation: They invariably represent concept taxonomies, sometimes even extracted in automated manner from the content pages of the underlying application for the purposes of WUM.…”

Section: Introductionmentioning

confidence: 99%

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A framework for mining meaningful usage patterns within a semantically enhanced web portal

Adda¹,

Valtchev

Missaoui

et al. 2010

Proceedings of the Third C* Conference on Computer Science and Software Engineering

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Section: Patterns and Domain Knowledgementioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

A framework for mining meaningful usage patterns within a semantically enhanced web portal

Adda¹,

Valtchev

Missaoui

et al. 2010

Proceedings of the Third C* Conference on Computer Science and Software Engineering

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“…Amit Bose et al, [15] proposed a framework for personalization combining usage information and domain knowledge based on ideas from bioinformatics and information retrieval. Vanzin et al [16] present ontology -based filtering mechanisms for retrieval of Web Usage patterns and the studies presented by Mehdi et al [17] proposed a framework XPMiner, which mines frequent patterns over ontology based pattern space. The studies assume that meta data of the web page contents can be typically organized into domain ontology and can be used in frequent pattern mining task.…”

Section: Related Workmentioning

confidence: 99%

Using Domain Ontology and Sequential Rule Mining for Extracting Behavior Patterns from Web Navigation Logs

Ramesh¹,

Rao²,

Govardhan³

2014

CVRJST

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Due to unprecedented growth of information on the Web and lack of structure in many Web sites, it became real challenge to the Web users to find relevant information. To solve this problem, Personalization becomes a popular solution to customize the World Wide Web environment toward the user's preferences. Recent studies show that Web Usage Mining plays an important role in designing recommendation systems. Classical Web Usage Mining does not take Semantics Knowledge into pattern discovery and recommendation process. Recent studies show that Ontology as domain knowledge can improve pattern's quality. Our work aims to incorporate semantics knowledge into Web Usage Mining process. ERMiner, a state-of-the art algorithm for Sequential rule mining is applied over the Semantic space to generate frequent Sequential rules. Experimental results shown are promising and proved that incorporating Semantic Knowledge into Web Usage Mining process can provide us with more quality patterns which consequently make the recommendation system more functional, smarter and comprehensive. The experimental results of our Web recommendation system show a significant improvement on the quality of the recommendations.

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“…While Yilmaz combines ontology and sequence information for sequence clustering, and Mabroukeh investigates sequential pattern mining and next step prediction. Vanzin et al [17] present ontology-based filtering mechanisms for retrieval of Web usage patterns, and more recently Mehdi et al [12] tackle the problem of mining meaniningful usage patterns and clarify the impact of ontologies to solve this problem. These works are restricted to only one domain and not cross-site browsing behavior.…”

Section: Related Workmentioning

confidence: 99%

Enabling Semantic Analysis of User Browsing Patterns in the Web of Data

Hoxha¹,

Junghans²,

Agarwal³

2012

Preprint

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A useful step towards better interpretation and analysis of the usage patterns is to formalize the semantics of the resources that users are accessing in the Web. We focus on this problem and present an approach for the semantic formalization of usage logs, which lays the basis for effective techniques of querying expressive usage patterns. We also present a query answering approach, which is useful to find in the logs expressive patterns of usage behavior via formulation of semantic and temporal-based constraints.We have processed over 30 thousand user browsing sessions extracted from usage logs of DBPedia and Semantic Web Dog Food. The logs are semantically formalized using respective domain ontologies and RDF representations of the Web resources being accessed. We show the effectiveness of our approach through experimental results, providing in this way an exploratory analysis of the way users browse the Web of Data.

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Ontology-Based Filtering Mechanisms for Web Usage Patterns Retrieval

Cited by 11 publications

References 11 publications

A framework for mining meaningful usage patterns within a semantically enhanced web portal

A framework for mining meaningful usage patterns within a semantically enhanced web portal

Using Domain Ontology and Sequential Rule Mining for Extracting Behavior Patterns from Web Navigation Logs

Enabling Semantic Analysis of User Browsing Patterns in the Web of Data

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