| AQUAM: automatic query formulation architecture for mobile applications |
| Full text |
Pdf
(855 KB)
|
Source
|
Mobile and Ubiquitous Multimedia
archive
Proceedings of the 7th International Conference on Mobile and Ubiquitous Multimedia
table of contents
Umeå, Sweden
SESSION: Smart multimedia applications and services
table of contents
Pages: 32-39
Year of Publication: 2008
ISBN:978-1-60558-192-7
|
|
Authors
|
|
Fotis Menemenis
|
Multimedia Knowledge Laboratory, Informatics and Telematics Institute, Thermi, Thessaloniki, Greece
|
|
Symeon Papadopoulos
|
Multimedia Knowledge Laboratory, Informatics and Telematics Institute, Thermi, Thessaloniki, Greece
|
|
Ben Bratu
|
Centre for Applications Research, Motorola Labs, Yvette, France
|
|
Simon Waddington
|
Centre for Applications Research, Motorola Labs, Basingstoke, UK
|
|
Yiannis Kompatsiaris
|
Multimedia Knowledge Laboratory, Informatics and Telematics Institute, Thermi, Thessaloniki, Greece
|
|
| Sponsor |
|
| Publisher |
|
| Bibliometrics |
Downloads (6 Weeks): 3, Downloads (12 Months): 34, Citation Count: 0
|
|
|
ABSTRACT
When a user performs a web search, the first query entered will frequently not return the required information. Thus, one needs to review the initial set of links and then to modify the query or construct a new one. This incremental process is particularly frustrating and difficult to manage for a mobile user due to the device limitations (e.g. keyboard, display). We present a query formulation architecture that employs the notion of context in order to automatically construct queries, where context refers to the article currently being viewed by the user. The proposed system uses semantic metadata extracted from the web page being consumed to automatically generate candidate queries. Novel methods are proposed to create and validate candidate queries. Further two variants of query expansion and a post-expansion validation technique are described. Finally, insights into the effectiveness of our system are provided based on evaluation tests of its individual components.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
 |
1
|
|
 |
2
|
|
| |
3
|
|
 |
4
|
Lev Finkelstein , Evgeniy Gabrilovich , Yossi Matias , Ehud Rivlin , Zach Solan , Gadi Wolfman , Eytan Ruppin, Placing search in context: the concept revisited, Proceedings of the 10th international conference on World Wide Web, p.406-414, May 01-05, 2001, Hong Kong, Hong Kong
[doi> 10.1145/371920.372094]
|
| |
5
|
Eric J. Glover , Gary W. Flake , Steve Lawrence , Andries Kruger , David M. Pennock , William P. Birmingham , C. Lee Giles, Improving Category Specific Web Search by Learning Query Modifications, Proceedings of the 2001 Symposium on Applications and the Internet (SAINT 2001), p.23, January 08-12, 2001
|
 |
6
|
|
 |
7
|
|
| |
8
|
S. Lawrence. Context in web search. IEEE Data Engineering Bulletin, 23(3):25--32, 2000.
|
| |
9
|
S. Patro, V. M. Malhotra, and D. Johnson. An algorithm to use feedback on viewed documents to improve web query. In WEBIST (Selected Papers), pages 177--189, 2006.
|
| |
10
|
|
| |
11
|
|
 |
12
|
|
|