Methods and apparatus for retrieving and/or processing retrieved

Data processing: database and file management or data structures – Database design – Data structure types

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707 5, G06F 1730

Patent

active

060062185

ABSTRACT:
Information retrieval methods and apparatus which involve: 1) the generation of estimates regarding the probability that items included in search results are already known to the user and 2) the use of such knowledge probability estimates to influence the ranking of search results, are described. By discounting the ranking, or adjusting ranking values generated by a known search engine as a function of the knowledge probability estimates, the present invention reduces or eliminates the risk of locating known information near the top of a list of search results. This is advantageous since known information is generally of little interest to a user. In various embodiments the popularity of an item is used to estimate the probability that the item is already known to a user. In addition, in various embodiments one or more user controllable parameters are used in the generation of the knowledge probability estimates and/or the ranking of the search results to give the user an opportunity to have the ranking of the search results accurately reflect the user's knowledge. The present invention is particularly well suited to collaborative filtering based search systems. This is because collaborative filters make recommendations to a user based on historical information relating to, e.g., the popularity of items being considered for recommendation. This same popularity information can be used to estimate a users knowledge of a database item. Such items may include television shows, music, Internet sites, etc.

REFERENCES:
Balabanovic et al. "Fab: Content-based, collaborative recommendation" Communications of the ACM, pp 66-72.
Rus et al. "Customizing Information Capture and Access" ACM Transactions on Information Systems, vol. 15, No. 1, pp. 67-101, Jan. 1997.
Lam et al. "Detection of Shifts in User Interests for Personalized Information Filtering" SIGIR'96, ACM Website, pp. 327-335, Aug. 1996.

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