TY - GEN
T1 - Data mining for navigation generating system with unorganized web resources
AU - Purwitasari, Diana
AU - Okazaki, Yasuhisa
AU - Watanabe, Kenzi
PY - 2008
Y1 - 2008
N2 - Users prefer to navigate subjects from organized topics in an abundance resources than to list pages retrieved from search engines. We propose a framework to cluster frequent itemsets (sets of common words) into topics, produce a hierarchical list, and then generate topics sequence from a collection of documents. The framework will regenerate a next sequence when users click a topic. Consider browsing to any topic as a kind of searching for that topic, the framework makes an inquiry using feature terms within the document representation of selected topic as query keywords. Our ranking method in searching process considers content analysis that still retaining spatial information of search keywords and link analysis of documents. Utilizing implementation of navigation generating system the experiments show that a navigation list from clustering results can be settled with regard to variance ratio of between and within distances. Agglomerative clustering is used in restructuring the extracted topics in order to produce a hierarchical navigation list.
AB - Users prefer to navigate subjects from organized topics in an abundance resources than to list pages retrieved from search engines. We propose a framework to cluster frequent itemsets (sets of common words) into topics, produce a hierarchical list, and then generate topics sequence from a collection of documents. The framework will regenerate a next sequence when users click a topic. Consider browsing to any topic as a kind of searching for that topic, the framework makes an inquiry using feature terms within the document representation of selected topic as query keywords. Our ranking method in searching process considers content analysis that still retaining spatial information of search keywords and link analysis of documents. Utilizing implementation of navigation generating system the experiments show that a navigation list from clustering results can be settled with regard to variance ratio of between and within distances. Agglomerative clustering is used in restructuring the extracted topics in order to produce a hierarchical navigation list.
UR - http://www.scopus.com/inward/record.url?scp=57849105532&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-85563-7_76
DO - 10.1007/978-3-540-85563-7_76
M3 - Conference contribution
AN - SCOPUS:57849105532
SN - 3540855629
SN - 9783540855620
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 598
EP - 605
BT - Knowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings
PB - Springer Verlag
T2 - 12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008
Y2 - 3 September 2008 through 5 September 2008
ER -