The World-Wide Web: quagmire or gold mine?
Communications of the ACM
Link prediction and path analysis using Markov chains
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Effective personalization based on association rule discovery from web usage data
Proceedings of the 3rd international workshop on Web information and data management
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Knowledge discovery from users Web-page navigation
RIDE '97 Proceedings of the 7th International Workshop on Research Issues in Data Engineering (RIDE '97) High Performance Database Management for Large-Scale Applications
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
REFEREE: an open framework for practical testing of recommender systems using ResearchIndex
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Duplicate detection in click streams
WWW '05 Proceedings of the 14th international conference on World Wide Web
Improving adaptation in web-based educational hypermedia by means of knowledge discovery
Proceedings of the sixteenth ACM conference on Hypertext and hypermedia
WAM-Miner: in the search of web access motifs from historical web log data
Proceedings of the 14th ACM international conference on Information and knowledge management
Incremental click-stream tree model: Learning from new users for web page prediction
Distributed and Parallel Databases
Mining and prediction of temporal navigation patterns for personalized services in e-commerce
Proceedings of the 2006 ACM symposium on Applied computing
An integrated efficient solution for computing frequent and top-k elements in data streams
ACM Transactions on Database Systems (TODS)
A framework of combining Markov model with association rules for predicting web page accesses
AusDM '06 Proceedings of the fifth Australasian conference on Data mining and analystics - Volume 61
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Representation and dimensionality reduction of semantically enriched clickstreams
Ph.D. '08 Proceedings of the 2008 EDBT Ph.D. workshop
A Consensus Recommender for Web Users
ADMA '07 Proceedings of the 3rd international conference on Advanced Data Mining and Applications
Expert Systems with Applications: An International Journal
Algorithms for clustering clickstream data
Information Processing Letters
Automated construction of web accessibility models from transaction click-streams
Proceedings of the 18th international conference on World wide web
Learning user clicks in web search
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Combination of Web page recommender systems
Expert Systems with Applications: An International Journal
A web page usage prediction scheme using sequence indexing and clustering techniques
Data & Knowledge Engineering
Markov model based mobile clickstream analysis with sub-day, day and week-scale transitions
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part III
A web-page usage prediction scheme using weighted suffix trees
SPIRE'07 Proceedings of the 14th international conference on String processing and information retrieval
Incorporating concept hierarchies into usage mining based recommendations
WebKDD'06 Proceedings of the 8th Knowledge discovery on the web international conference on Advances in web mining and web usage analysis
Learning user purchase intent from user-centric data
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
An integrated model for next page access prediction
International Journal of Knowledge and Web Intelligence
Towards tabbing aware recommendations
Proceedings of the First International Conference on Intelligent Interactive Technologies and Multimedia
Cleopatra: evolutionary pattern-based clustering of web usage data
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Clustering web sessions by levels of page similarity
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
iWed: an integrated multigraph cut-based approach for detecting events from a website
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
An exploratory analysis on user behavior regularity in the mobile internet
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
Mining significant usage patterns from clickstream data
WebKDD'05 Proceedings of the 7th international conference on Knowledge Discovery on the Web: advances in Web Mining and Web Usage Analysis
Short Survey: A taxonomy of web prediction algorithms
Expert Systems with Applications: An International Journal
A comparison of prediction algorithms for prefetching in the current web
Journal of Web Engineering
Web Page Prediction by Clustering and Integrated Distance Measure
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Timespent based models for predicting user retention
Proceedings of the 22nd international conference on World Wide Web
Effective web log mining and online navigational pattern prediction
Knowledge-Based Systems
Personalised web search using ACO with information scent
International Journal of Knowledge and Web Intelligence
You are how you click: clickstream analysis for Sybil detection
SEC'13 Proceedings of the 22nd USENIX conference on Security
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Predicting the next request of a user as she visits Web pages has gained importance as Web-based activity increases. Markov models and their variations, or models based on sequence mining have been found well suited for this problem. However, higher order Markov models are extremely complicated due to their large number of states whereas lower order Markov models do not capture the entire behavior of a user in a session. The models that are based on sequential pattern mining only consider the frequent sequences in the data set, making it difficult to predict the next request following a page that is not in the sequential pattern. Furthermore, it is hard to find models for mining two different kinds of information of a user session. We propose a new model that considers both the order information of pages in a session and the time spent on them. We cluster user sessions based on their pair-wise similarity and represent the resulting clusters by a click-stream tree. The new user session is then assigned to a cluster based on a similarity measure. The click-stream tree of that cluster is used to generate the recommendation set. The model can be used as part of a cache prefetching system as well as a recommendation model.