ACM Home Page
Please provide us with feedback. Feedback
User-oriented document summarization through vision-based eye-tracking
Full text PdfPdf (661 KB)
Source
International Conference on Intelligent User Interfaces archive
Proceedings of the 13th international conference on Intelligent user interfaces table of contents
Sanibel Island, Florida, USA
SESSION: Summarization table of contents
Pages 7-16  
Year of Publication: 2009
ISBN:978-1-60558-168-2
Authors
Songhua Xu  Zhejiang University, Yale University & The University of Hong Kong
Hao Jiang  The University of Hong Kong, Hong Kong, Hong Kong
Francis C.M. Lau  The University of Hong Kong, Hong Kong, Hong Kong
Sponsors
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery
SIGART: ACM Special Interest Group on Artificial Intelligence
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 40,   Downloads (12 Months): 256,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1502650.1502656
What is a DOI?

ABSTRACT

We propose a new document summarization algorithm which is personalized. The key idea is to rely on the attention (reading) time of individual users spent on single words in a document as the essential clue. The prediction of user attention over every word in a document is based on the user's attention during his previous reads, which is acquired via a vision-based commodity eye-tracking mechanism. Once the user's attentions over a small collection of words are known, our algorithm can predict the user's attention over every word in the document through word semantics analysis. Our algorithm then summarizes the document according to user attention on every individual word in the document. With our algorithm, we have developed a document summarization prototype system. Experiment results produced by our algorithm are compared with the ones manually summarized by users as well as by commercial summarization software, which clearly demonstrates the advantages of our new algorithm for user-oriented document summarization.


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
Bibliography summarization papers. http://www.summarization.com/summ.pdf, last updated on October 20, 2008. last visited on December 11, 2008.
 
2
 
3
A. Bulling, J. A.Ward, H. Gellersen, and G. Tröster. Robust recognition of reading activity in transit using wearable electrooculography. In Pervasive '08: Proceedings of the 6th International Conference on Pervasive Computing, pages 19--37, 2008.
4
 
5
E. H. Chi, M. Gumbrecht, and L. Hong. Visual foraging of highlighted text: An eye-tracking study. In HCII '07: Proceedings of HCI International Conference, pages 589--598, 2007.
 
6
The New York Times Company. The New York Times, http://www.nytimes.com/, last visited on December 11, 2008.
 
7
T. Darrell, N. Checka, A. Oh, and L. Morency. Exploring vision-based interfaces: How to use your head in dual pointing tasks. MIT AI Memo 2002-001, 2002.
8
 
9
G. Dupret, V. Murdock, and B. Piwowarski. Web search engine evaluation using clickthrough data and a user model. In WWW '07: Proceedings of International Conference on World Wide Web, Banff, Canada, 2007.
 
10
G. Erkan and D. Radev. Lexrank: Graph-based lexical centrality as salience in text summarization. Journal of Artificial Intelligence Research (JAIR), 22:457--479, 2004.
 
11
American Association for the Advancement of Science. Science magazine, http://www.sciencemag.com/, last visited on December 11, 2008.
12
13
14
 
15
D. Gorodnichy. Perceptual cursor-a solution to the broken loop problem in vision-based hands-free computer control devices. National Research Council Canada Publication, NRC-48472:1--23, 2006.
16
17
 
18
 
19
 
20
21
22
 
23
K. S. Jones. What might be in a summary. In Information Retrieval 93: Von der Modellierung zur Anwendung, pages 9--26, 1993.
24
25
 
26
K.-N. Kim and R. Ramakrishna. Vision-based eye-gaze tracking for human computer interface. SMC '99: Proceedings of IEEE International Conference on Systems, Man, and Cybernetics, 2:324--329, 1999.
 
27
28
 
29
Y.-P. Lin, Y.-P. Chao, C.-C. Lin, and J.-H. Chen. Webcam mouse using face and eye tracking in various illumination environments. EMBS '05: Proceedings of 27th IEEE Annual International Conference of Engineering in Medicine and Biology Society, pages 3738--3741, 2005.
30
 
31
 
32
 
33
Microsoft. Word (software), http://office.microsoft.com/word/, Microsoft Corporation, last visited on December 11, 2008.
34
 
35
D. Radev, T. Allison, S. Blair-Goldensohn, J. Blitzer, A. C¸ elebi, S. Dimitrov, E. Drabek, A. Hakim, W. Lam, D. Liu, J. Otterbacher, H. Qi, H. Saggion, S. Teufel, M. Topper, A. Winkel, and Z. Zhang. MEAD--A platform for multidocument multilingual text summarization. In LREC '04: The 2nd International Conference on Language Resources and Evaluation, Lisbon, Portugal, May 2004.
36
37
38
 
39
G. Salton and C. Buckley. Improving retrieval performance by relevance feedback. Journal of the American Society for Information Science, 41(4):288--297, 1990.
 
40
 
41
M.-C. Su, S.-Y. Su, and G.-D. Chen. A low-cost vision-based human-computer interface for people with severe disabilities. Biomedical Engineering Applications, Basis, and Communications, 17:284--292, 2005.
 
42
R. White, J. M. Jose, and I. Ruthven. Comparing explicit and implicit feedback techniques for web retrieval: Trec-10 interactive track report. In TREC 2001.
 
43
44
 
45
S. Xu, Y. Zhu, H. Jiang, and F. C. M. Lau. A user-oriented webpage ranking algorithm based on user attention time. In AAAI '08: Proceedings of the 23rd AAAI Conference on Artificial Intelligence, pages 1255--1260, 2008, AAAI Press.
 
46
 
47
P. Zielinski. Opengazer: open-source gaze tracker for ordinary webcams (software), Samsung and The Gatsby Charitable Foundation. http://www.inference.phy.cam.ac.uk/opengazer/, last visited on December 11 2008.

Collaborative Colleagues:
Songhua Xu: colleagues
Hao Jiang: colleagues
Francis C.M. Lau: colleagues