A natural language interface to a graph-based bibliographic information retrieval system

• Published in: Data & knowledge engineering 2017-09, Vol.111, p.73-89
• Main Authors: Zhu, Yongjun, Yan, Erjia, Song, Il-Yeol
• Format: Article
• Language: English
• Subjects: Data and knowledge visualization; Digital libraries; Graph database; Information retrieval; Natural language interface
• ISSN: 0169-023X; 1872-6933
• DOI: 10.1016/j.datak.2017.06.006

With the ever-increasing volume of scientific literature, there is a need for a natural language interface to bibliographic information retrieval systems to retrieve relevant information effectively. In this paper, we propose one such interface, NLI-GIBIR, which allows users to search for a variety of bibliographic data through natural language. NLI-GIBIR makes use of a novel framework applicable to graph-based bibliographic information retrieval systems in general. This framework incorporates algorithms/heuristics for interpreting and analyzing natural language bibliographic queries via a series of text- and linguistic-based techniques, including tokenization, named entity recognition, and syntactic analysis. We find that our framework, as implemented in NLI-GIBIR, can effectively represent and address complex bibliographic information needs. Thus, the contributions of this paper are as follows: First, to our knowledge, it is the first attempt to propose a natural language interface for graph-based bibliographic information retrieval. Second, we propose a novel customized natural language processing framework that integrates a few original algorithms/heuristics for interpreting and analyzing bibliographic queries. Third, we show that the proposed framework and natural language interface provide a practical solution for building real-world bibliographic information retrieval systems. Our experimental results show that the presented system can correctly answer 39 out of 40 example natural language queries with varying lengths and complexities.