@inproceedings{
 title = {Agents, bookmarks and clicks: A topical model of Web navigation},
 type = {inproceedings},
 year = {2010},
 keywords = {Agent-based model; Back button; Bookmarks; PageRan,Hypermedia systems; Hypertext systems; Markov pro,Navigation},
 pages = {229-233},
 websites = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77954945972&doi=10.1145%2F1810617.1810658&partnerID=40&md5=37b65d72bd226bc34db53516f5a0a035},
 city = {Toronto, ON},
 id = {b71033c2-d7be-39e8-966b-4bcff609f1f5},
 created = {2018-01-16T17:54:28.627Z},
 file_attached = {false},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 last_modified = {2018-03-12T19:03:19.219Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Meiss2010229},
 source_type = {conference},
 notes = {cited By 8; Conference of 21st ACM Conference on Hypertext and Hypermedia, HYPERTEXT 2010 ; Conference Date: 13 June 2010 Through 16 June 2010; Conference Code:81180},
 folder_uuids = {971e10ae-b1f7-4c4b-8f99-aa55f77a64f6},
 private_publication = {false},
 abstract = {Analysis has shown that the standard Markovian model of Web navigation is a poor predictor of actual Web traffic. Using empirical data, we characterize several properties of Web traffic that cannot be reproduced with Markovian models but can be explained by an agent-based model that adds several realistic browsing behaviors. First, agents maintain bookmark lists used as teleportation targets. Second, agents can retreat along visited links, a branching mechanism that can reproduce behavior such the back button and tabbed browsing. Finally, agents are sustained by visiting pages of topical interest, with adjacent pages being related. This modulates the production of new sessions, recreating heterogeneous session lengths. The resulting model reproduces individual behaviors from empirical data, reconciling the narrowly focused browsing patterns of individual users with the extreme heterogeneity of aggregate traffic measurements, and leading the way to more sophisticated, realistic, and effective ranking and crawling algorithms. Copyright 2010 ACM.},
 bibtype = {inproceedings},
 author = {Meiss, M R and Gonçalves, B and Ramasco, J J and Flammini, A and Menczer, F},
 doi = {10.1145/1810617.1810658},
 booktitle = {HT'10 - Proceedings of the 21st ACM Conference on Hypertext and Hypermedia}
}

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