An ontology-based mining approach for user search intent discovery
Shen, Yan, Li, Yuefeng, Xu, Yue, Iannella, Renato, Algarni, Abdulmohsen, & Tao, Xiaohui (2011) An ontology-based mining approach for user search intent discovery. In Cunningham, Sally Jo, Scholer, Falk, & Thomas, Paul (Eds.) ADCS 2011 : Proceedings of the Sixteenth Australasian Document Computing Symposium, Australian National University, Canberra, pp. 39-46.
This is the latest version of this eprint.
Discovering proper search intents is a vi- tal process to return desired results. It is constantly a hot research topic regarding information retrieval in recent years. Existing methods are mainly limited by utilizing context-based mining, query expansion, and user profiling techniques, which are still suffering from the issue of ambiguity in search queries. In this pa- per, we introduce a novel ontology-based approach in terms of a world knowledge base in order to construct personalized ontologies for identifying adequate con- cept levels for matching user search intents. An iter- ative mining algorithm is designed for evaluating po- tential intents level by level until meeting the best re- sult. The propose-to-attempt approach is evaluated in a large volume RCV1 data set, and experimental results indicate a distinct improvement on top precision after compared with baseline models.
Citation countsare sourced monthly fromand citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
|Item Type:||Conference Paper|
|Keywords:||Ontology mining, Search intent, LCSH, World knowledge|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)|
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > DISTRIBUTED COMPUTING (080500) > Web Technologies (excl. Web Search) (080505)
|Divisions:||Past > Schools > Computer Science|
Past > QUT Faculties & Divisions > Faculty of Science and Technology
|Copyright Owner:||Copyright 2011 The Authors.|
|Deposited On:||17 Jan 2012 13:17|
|Last Modified:||25 Jan 2012 15:48|
Available Versions of this Item
- An Ontology-based mining approach for user search intent discovery. (deposited 17 Jan 2012 07:48)
- An ontology-based mining approach for user search intent discovery. (deposited 17 Jan 2012 13:17)[Currently Displayed]
Repository Staff Only: item control page