Mining Semi-structured Data

TL;DR

This paper proposes a method using Formal Concept Analysis to index and query XML documents by combining their structural and content features, addressing challenges in knowledge discovery from semi-structured data.

Contribution

It introduces a novel approach that leverages Formal Concept Analysis to effectively handle both structure and content in XML data for improved querying.

Findings

Effective indexing of XML data using Formal Concept Analysis

Enhanced querying capabilities for structured and content features

Demonstrated applicability in knowledge discovery from semi-structured data

Abstract

The need for discovering knowledge from XML documents according to both structure and content features has become challenging, due to the increase in application contexts for which handling both structure and content information in XML data is essential. So, the challenge is to find an hierarchical structure which ensure a combination of data levels and their representative structures. In this work, we will be based on the Formal Concept Analysis-based views to index and query both content and structure. We evaluate given structure in a querying process which allows the searching of user query answers.