Genetic algorithm implementation for effective document subject search
This addresses document retrieval efficiency for users in information search systems, but appears incremental as it applies an existing method to a specific domain.
The paper tackles the problem of identifying relevant documents in subject search by implementing a genetic algorithm to generate effective search queries and classify results, but does not provide concrete performance numbers.
This paper describes the software implementation of genetic algorithm for identifying and selecting most relevant results received during sequentially executed subject search operations. Simulated evolutionary process generates sustainable and effective population of search queries, forms search pattern of documents or semantic core, creates relevant sets of required documents, allows automatic classification of search results. The paper discusses the features of subject search, justifies the use of a genetic algorithm, describes arguments of the fitness function and describes basic steps and parameters of the algorithm.