Patent ID: 7188101

Claim:
A computer-implemented data processing method for retrieving a subset of k items from a database of n items (n>>k), the method comprising: (a) determining largest set bk items (where b>1 and bk is a set larger than k) in the database of n items which have the greatest similarity to an input query t according to a given similarity function S, (b) selecting as the first member of the subset that item of said bk items having the highest similarity S to the query t, and (c) iteratively selecting and retrieving each successive member of the subset as that remaining item of said bk items having the highest quality Q, where Q is a given function of similarity S to the input query t and relative diversity RD, wherein relative diversity RD is a given function of the diversity of that remaining item with respect to the items selected during the previous iteration(s); wherein said input query t and each of the database items is defined in terms of a plurality of parameters, and wherein said similarity function S comprises conducting a comparison between corresponding parameters of the query t and of the item to which the query is being compared to obtain a feature similarity measurement, and summing the feature similarity measurements to arrive at a similarity measurement between the query t and the item to which the query is being compared: wherein said different feature similarity measurements are given different relative weightings; wherein said similarity function S is defined between a query t and an item c, each having n features for comparison, as: Similarity ⁡ ( t , c ) = ∑ i = 1 ⁢ … ⁢ ⁢ n ⁢ w i * sim ⁡ ( t i , c i ) ∑ i = 1 ⁢ … ⁢ ⁢ n ⁢ w i wherein sim(t i , c i ) is a given feature similarity measurement for feature i, and w i , is a weighting for feature i.