Capturing User Reading Behaviors for Personalized Document Summarization

Conference · Sat Jan 01 00:00:00 EST 2011

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 Lab. (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE Laboratory Directed Research and Development (LDRD) Program
• DOE Contract Number: DE-AC05-00OR22725
• OSTI ID: 1006465
• Resource Relation: Conference: International Conference on Intelligent User Interfaces, Palo Alto, CA, USA, 20110213, 20110216
• Country of Publication: United States
• Language: English

Related Subjects

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