AICLIROct 2, 2020

Building Large Lexicalized Ontologies from Text: a Use Case in Automatic Indexing of Biotechnology Patents

arXiv:2010.00860v115 citations
Originality Synthesis-oriented
AI Analysis

This work addresses the need for fine-grained indexing in semantic search applications, specifically for biotechnology patents, and appears incremental as it builds on existing ontology-building methods.

The paper tackles the problem of building large lexicalized ontologies from text for semantic search, presenting the TyDI tool and methods, and demonstrates its potential in a biotechnology patent indexing use case.

This paper presents a tool, TyDI, and methods experimented in the building of a termino-ontology, i.e. a lexicalized ontology aimed at fine-grained indexation for semantic search applications. TyDI provides facilities for knowledge engineers and domain experts to efficiently collaborate to validate, organize and conceptualize corpus extracted terms. A use case on biotechnology patent search demonstrates TyDI's potential.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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