Search results for "Clickstream"

showing 3 items of 3 documents

Novel Version of PageRank, CheiRank and 2DRank for Wikipedia in Multilingual Network Using Social Impact

2020

International audience; Nowadays, information describing navigation behaviour of internet users are used in several fields, e-commerce, economy, sociology and data science. Such information can be extracted from different knowledge bases, including business-oriented ones. In this paper, we propose a new model for the PageRank, CheiRank and 2DRank algorithm based on the use of clickstream and pageviews data in the google matrix construction. We used data from Wikipedia and analysed links between over 20 million articles from 11 language editions. We extracted over 1.4 billion source-destination pairs of articles from SQL dumps and more than 700 million pairs from XML dumps. Additionally, we …

CheiRankPageRankSQLComputer sciencecomputer.internet_protocol01 natural sciences[INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI]010305 fluids & plasmaslaw.inventionCheiRankPageRanklaw0103 physical sciencesCentrality measures010306 general physicsClickstreamcomputer.programming_languageInformation retrievalGoogle matrixGoogle matrixPageviewsSocial impactPage viewcomputerClickstreamXMLWikipedia
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Analysis of clickstream data with mixture hidden markov models

2021

clickstream data sono un’importante fonte di informazioni per l’ecommerce, sebbene non siano semplici da gestire e convertire queste informazioni in un reale vantaggio competitivo non e un compito banale. In questo articolo, consid- ` eriamo l’applicazione dei mixture hidden Markov model a dati relativi al flusso di clickstream estratti dal portale e-commerce di un’azienda di servizi turistici. Sono stati individuati cluster relativi al comportamento di navigazione degli utenti e alla loro posizione geografica che forniscono indicazioni importanti per lo sviluppo di nuove strategie di business. Clickstream data is an important source of information for businesses, however it is not easy to …

Settore SECS-S/03 - Statistica EconomicaClickstream Data Online browsing behaviour Mixture hidden Markov models Tourism 2.0 Web mining
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Clickstream Data Analysis: A Clustering Approach Based on Mixture Hidden Markov Models

2023

Nowadays, the availability of devices such as laptops and cell phones enables one to browse the web at any time and place. As a consequence, a company needs to have a website so as to maintain or increase customer loyalty and reach potential new customers. Besides, acting as a virtual point-of-sale, the company portal allows it to obtain insights on potential customers through clickstream data, web generated data that track users accesses and activities in websites. However, these data are not easy to handle as they are complex, unstructured and limited by lack of clear information about user intentions and goals. Clickstream data analysis is a suitable tool for managing the complexity of t…

model selectionhidden Markov modelsSettore SECS-S/03 - Statistica Economicaentropy based scoremixture modelsbrowsing profilesclickstream data
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