Bib2vec: An Embedding-based Search System for Bibliographic Information
This work addresses the need for improved search systems in bibliographic databases, though it appears incremental as it builds on existing embedding techniques for a specific domain.
The authors tackled the problem of representing and searching bibliographic information by proposing an embedding model that captures relationships among elements, achieving high prediction ability and producing reasonable search results in the ACL Anthology Reference Corpus.
We propose a novel embedding model that represents relationships among several elements in bibliographic information with high representation ability and flexibility. Based on this model, we present a novel search system that shows the relationships among the elements in the ACL Anthology Reference Corpus. The evaluation results show that our model can achieve a high prediction ability and produce reasonable search results.