Multi-objective genetic programming strategies for topic-based search with a focus on diversity and global recall.

ABSTRACT: Topic-based search systems retrieve items by contextualizing the information seeking process on a topic of interest to the user. A key issue in topic-based search of text resources is how to automatically generate multiple queries that reflect the topic of interest in such a way that precision, recall, and diversity are achieved. The problem of generating topic-based queries can be effectively addressed by Multi-Objective Evolutionary Algorithms, which have shown promising results. However, two common problems with such an approach are loss of diversity and low global recall when combining results from multiple queries. This work proposes a family of Multi-Objective Genetic Programming strategies based on objective functions that attempt to maximize precision and recall while minimizing th

SUBMITTER: Baggio C 

PROVIDER: S-EPMC10702999 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature