# Whois? Deep Author Name Disambiguation using Bibliographic Data

arXiv: https://arxiv.org/abs/2207.04772 · HTML: https://mlsanity.com/paper/2207.04772/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 42 references that are in the map.
- First posted on arXiv 11 Jul 2022.

## Builds on (most cited first, 11 of 11)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [node2vec: Scalable Feature Learning for Networks](https://mlsanity.com/paper/1607.00653/) (2016)
- [DeepWalk: Online Learning of Social Representations](https://mlsanity.com/paper/1403.6652/) (2014)
- [LINE: Large-scale Information Network Embedding](https://mlsanity.com/paper/1503.03578/) (2015)
- [PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks](https://mlsanity.com/paper/1508.00200/) (2015)
- [DeepER -- Deep Entity Resolution](https://mlsanity.com/paper/1710.00597/) (2017)
- [A Joint Model for Word Embedding and Word Morphology](https://mlsanity.com/paper/1606.02601/) (2016)
- [Name Disambiguation in Anonymized Graphs using Network Embedding](https://mlsanity.com/paper/1702.02287/) (2017)
- [Ethnicity sensitive author disambiguation using semi-supervised learning](https://mlsanity.com/paper/1508.07744/) (2015)
- [Author Name Disambiguation by Using Deep Neural Network](https://mlsanity.com/paper/1502.08030/) (2015)
- [Bayesian Non-Exhaustive Classification A Case Study: Online Name Disambiguation using Temporal Record Streams](https://mlsanity.com/paper/1607.05746/) (2016)

## Built on by (most cited first, 3 of 3)

- [Deep Author Name Disambiguation using DBLP Data](https://mlsanity.com/paper/2303.10067/) (2023)
- [PADME-SoSci: A Platform for Analytics and Distributed Machine Learning for the Social Sciences](https://mlsanity.com/paper/2303.18200/) (2023)
- [Recent Developments in Deep Learning-based Author Name Disambiguation](https://mlsanity.com/paper/2503.13448/) (2024)

## Abstract (arXiv)

As the number of authors is increasing exponentially over years, the number of authors sharing the same names is increasing proportionally. This makes it challenging to assign newly published papers to their adequate authors. Therefore, Author Name Ambiguity (ANA) is considered a critical open problem in digital libraries. This paper proposes an Author Name Disambiguation (AND) approach that links author names to their real-world entities by leveraging their co-authors and domain of research. To this end, we use a collection from the DBLP repository that contains more than 5 million bibliographic records authored by around 2.6 million co-authors. Our approach first groups authors who share the same last names and same first name initials. The author within each group is identified by capturing the relation with his/her co-authors and area of research, which is represented by the titles of the validated publications of the corresponding author. To this end, we train a neural network model that learns from the representations of the co-authors and titles. We validated the effectiveness of our approach by conducting extensive experiments on a large dataset.