Capturing User Reading Behaviors for Personalized Document Summarization

Conference · Fri Dec 31 23:00:00 EST 2010

OSTI ID:1006465

Xu, Songhua ^[1]; Jiang, Hao ^[2]; Lau, Francis ^[2]

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1. ORNL
2. University of Hong Kong, The

We propose a new personalized document summarization method that observes a user's personal reading preferences. These preferences are inferred from the user's reading behaviors, including facial expressions, gaze positions, and reading durations that were captured during the user's past reading activities. We compare the performance of our algorithm with that of a few peer algorithms and software packages. The results of our comparative study show that our algorithm can produce more superior personalized document summaries than all the other methods in that the summaries generated by our algorithm can better satisfy a user's personal preferences.

• Research Organization: Oak Ridge National Laboratory (ORNL)
• Sponsoring Organization: ORNL LDRD Director's R&D
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1006465
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING
ALGORITHMS
BEHAVIOR
HUMAN FACTORS ENGINEERING
INFORMATION RETRIEVAL
INFORMATION SYSTEMS
MAN-MACHINE SYSTEMS
PERFORMANCE