Bio: Huang Chunlan is an academic researcher. The author has an hindex of 1, co-authored 1 publications receiving 1 citations.
04 Jun 2014
TL;DR: In this article, an information retrieval data fusion method based on retrieval result diversification is proposed, which can improve the validity and diversity of infused results and can also be applied to different types of infusion problems such as documents, pictures, medical records and the like.
Abstract: The invention discloses an information retrieval data fusion method based on retrieval result diversification. The method includes the following steps that suppose that totally t information retrieval systems exist, the same database is searched by the t information retrieval systems for the same inquiry, and t results are obtained; the number of times of a file, occurring in other results, of any result is counted; the difference value of each retrieval result i (1<=i<=t) serves as the difference weight; the use performance index ERR-IA20 is used for evaluation, an obtained performance value serves as the performance weight of each information retrieval system; the difference weight and the performance weight are combined, the comprehensive weight of each information retrieval system is calculated; the method is repeatedly used in one group of inquiries, the final weight of each information retrieval system is the average value obtained in all the inquiries; retrieval result infusion is performed on the calculated final weights with a linear combination method. The information retrieval data fusion method can improve the validity and the diversity of infused results and can also be applied to different types of infusion problems such as documents, pictures, medical records and the like.
11 Mar 2015
TL;DR: In this article, a data integration method supporting the diversification of information retrieval results is proposed. The method is mainly based on a complementary weight allocation strategy covered by a sub-theme.
Abstract: The invention discloses a data integration method supporting the diversification of information retrieving results. The method is mainly based on a complementary weight allocation strategy covered by a sub-theme. The calculation of the complementary weight mainly comprises the following steps of providing t information retrieving systems, retrieving a corresponding result r1, r2,...,rt from a same database by each information retrieving system for a given inquiry q; establishing a super result r on the basis of two results ri and rj; then evaluating the ri, rj and r by utilizing a performance index to obtain performance values, respectively recording the performance values as p , p and p , calculating the complementation degree of ri corresponding to rj according to the performance value, calculating the complementary weight ci of the calculation result ri (i is more than or equal to 1 and less than or equal to t), acquiring the complementary weight, and directly utilizing the complementary weight for the linear combination or as a part of the linear combined weight. By adopting the method, the novelty can be considered on the basis of diversification, the complementation degree of a result to the integrity can be quantified, and the method can be used for integrating various types such as texts, pictures and the like.