ISA-bEL: Intelligent Search Algorithm based on Entity Linking

TL;DR

ISA-bEL introduces an entity linking-based search algorithm that enhances natural language understanding by leveraging linked entities and knowledge graphs to improve user intent detection.

Contribution

The paper proposes a novel search algorithm utilizing entity linking and knowledge graphs to better capture user intent in natural language interfaces.

Findings

Improved accuracy in intent detection using linked entities.

Enhanced retrieval performance with knowledge graph integration.

Demonstrated effectiveness in natural language processing pipelines.

Abstract

Nowadays, the way in which the people interact with computers has changed. Text- or voice-based interfaces are being widely applied in different industries. Among the most used ways of processing the user input are those based on intents or retrieval algorithms. In these solutions, important information of the user could be lost in the process. For the proposed natural language processing pipeline the entities are going to take a principal role, under the assumption that entities are where the purpose of the user resides. Entities fed with context will be projected to a specific domain supported by a knowledge graph, resulting in what has been named as linked entities. These linked entities serve then as a key for searching a top level aggregation concept within our knowledge graph.