@inproceedings{1feeabe486cc4994a616a835bb3232c4,
title = "Knowledgebase harvesting for user-adaptive systems through focused crawling and semantic web",
abstract = "The expansion and ever evolving web makes it difficult to find relevant information that best fits user's intentions. This paper introduces development of hybrid approach that addresses the issue of collecting large knowledgebase by fusing the thematic or focused crawling methodologies, with adaptive and semantic web concepts. Focused crawling ensures the goal directed search of data on the web, adaptive web environments establish proper content and link adaptation whilst semantic web inserts meaning to web documents from the sense of content and metadata. The thematic crawling process retrieved approximately 11,429 documents from 11,286 visited locations resulting in 9,807 database entries out of which 81 entries are classified as top ranked distributed in seven categories. On the next phase, a reasoning process was performed against the semantic ontology which comprised the top ranked documents as class individuals. Results indicated that retrieved relevant documents, together with assertions against class individuals from the ontology highly reflect the user browsing activities and intentions.",
keywords = "Adaptive web, Focused crawling, Ontologies, Semantic web",
author = "Bujar Raufi and Florije Ismaili and Jaumin Ajdari and Xhemal Zenuni",
note = "Publisher Copyright: {\textcopyright}2016 ACM.; 17th International Conference on Computer Systems and Technologies, CompSysTech 2016 ; Conference date: 23-06-2016 Through 24-06-2016",
year = "2016",
month = jun,
day = "23",
doi = "10.1145/2983468.2983510",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "323--330",
editor = "Angel Smrikarov and Boris Rachev",
booktitle = "Computer Systems and Technologies 17th International Conference, CompSysTech 2016 - Proceedings",
address = "United States",
}