Title :
A Domain Identification Algorithm for Personalised Query Expansion with Contextual Information
Author :
Seher, I. ; Ginige, A. ; Shahrestani, S.A.
Author_Institution :
Univ. of Western Sydney, Sydney
Abstract :
Human communications are quite successful and seem to be very easy. Human communication is more successful when there is an implicit understanding of everyday situations of others who take part in the communication. Similar to human communication, if an automated system could keep or capture the contextual information related to a user and the query, then it could use this information to process the query, resulting more useful answers. As this contextual information depends on the query domain, if the automated system could identify the domain of the query, then it could expand the query with domain specific contextual information and user preferences related to the query domain. This paper briefs the requirements of such a query expansion and describes an algorithm to identify application domains of user queries.
Keywords :
data mining; query processing; relevance feedback; contextual information; domain identification algorithm; human communication; personalised query expansion; query processing; user preference; user queries; Application software; Australia; Context; Context-aware services; Data mining; Feedback; History; Humans; Mathematics; Ontologies;
Conference_Titel :
Computer and Information Science, 2007. ICIS 2007. 6th IEEE/ACIS International Conference on
Conference_Location :
Melbourne, Qld.
Print_ISBN :
0-7695-2841-4
DOI :
10.1109/ICIS.2007.16
