Approaches to the Intelligent Subject Search

TL;DR

This paper explores automated semantic processing techniques for subject information search, focusing on query construction, filtering, and ranking of scientific data, supported by software architecture and pilot study results.

Contribution

It introduces new methods for building and qualifying search queries using semantic processing in scientific data retrieval.

Findings

Effective query filtering and ranking techniques identified

Software architecture for semantic search developed

Pilot study demonstrates improved search relevance

Abstract

This article presents main results of the pilot study of approaches to the subject information search based on automated semantic processing of mass scientific and technical data. The authors focus on technology of building and qualification of search queries with the following filtering and ranking of search data. Software architecture, specific features of subject search and research results application are considered.