Person Entity Profiling Framework: Identifying, Integrating and Visualizing Online Freely Available Entity-Related Information

TL;DR

This paper introduces a novel framework for real-time online entity profiling that searches, analyzes, and visualizes rich, interconnected information about entities from freely available web sources, enhancing understanding beyond traditional methods.

Contribution

The study presents a new entity search framework that generates structured, visual entity-relation graphs without predefined relation types, improving interpretability and user understanding.

Findings

Framework effectively searches and consolidates entity information

Visualizations are well-received and aid user comprehension

Component evaluations show high performance in entity and relation identification

Abstract

When we consider our CV, it is full of entities that we are or were associated with and that define us in some way(s). Such entities include where we studied, where we worked, who we collaborated with on a project or on a paper etc. Entities we are linked to are part of who we are and may reveal about what we are interested in. Hence, we can view any CV as a graph of interlinked entities, where nodes are entities and edges are relations between them. This study proposes a novel entity search framework that in response to a real-time query about an entity, searches, crawls, analyzes and consolidates relevant information that is freely available on the Web about the entity of interest, culminating in the generation a profile of the searched entity. Unlike typical entity search settings, in which a ranked list of entities related to the target entity over a pre-specified relation is processed, we present and visualize rich information about the entity of interest as a typed entity-relation graph without an apriori definition of the types of related entities and relations. This view is structured and compact, making it easy to understand as well as interpret. It enables the user to learn not only about the entity in question, but also about related entities, thereby obtaining a better understanding of the entity in question. We evaluated each of the frameworks components separately and then performed an overall evaluation of the framework, its visualization and the interest of users in the results. The results show that the proposed framework performs entity searches, related entity identification and relation identification very well and that it satisfies users needs.