@inproceedings{ecdfb23ce5e64d9d970064a13ac55ef7,
title = "Discovery of intent through the analysis of visited sites",
abstract = "Discovering the intention(s) of a web surfer using the set of websites visited by the surfer within a given time interval, has its own financial reward. In this paper, we report the preliminary findings of our investigation for the discovery of the intention(s) of a surfer based on the hierarchical model of (stimuli, attention, and intention). The emphasis in this preliminary report is on the discovery of uni-token intentions. The proposed methodology is tested on 40 sites visited by a surfer by (a) determining the gist and intention of the visit for each website, (b) partitioning the intentions and (c) aggregating partitions such that each aggregate accurately reflects the surfer's intention(s) along with the number of intention changes within the given time interval of one day. The test results revealed 90% accuracy in the discovery of uni-token intentions.",
keywords = "Document's gist analysis, Gist strength, Intention analysis, Intention model, Intention strength",
author = "Hashemi, {Ray R.} and James LaPlant and Azita Bahrami and Thurber, {Kenneth J.}",
year = "2008",
language = "English",
isbn = "1601320752",
series = "Proceedings of the 2008 International Conference on Information and Knowledge Engineering, IKE 2008",
pages = "417--422",
booktitle = "Proceedings of the 2008 International Conference on Information and Knowledge Engineering, IKE 2008",
note = "2008 International Conference on Information and Knowledge Engineering, IKE 2008 ; Conference date: 14-07-2008 Through 17-07-2008",
}