Computer Science and Information Systems | |
An evaluation of keyword, string similarity and very shallow syntactic matching for a university admissions processing infobot | |
Nikolaos Polatidis1  Peter Hancox2  | |
[1] Department of Applied Informatics, University of Macedonia;School of Computer Science, University of Birmingham | |
关键词: chatbot; infobot; question-answering; Jaro string similarity; Jaro-Winkler string similarity; shallow syntactic processing; | |
DOI : 10.2298/CSIS121202065H | |
学科分类:社会科学、人文和艺术(综合) | |
来源: Computer Science and Information Systems | |
【 摘 要 】
âInfobotsâ are small-scale natural language question answering systems drawing inspiration from ELIZA-type systems. Their key distinguishing feature is the extraction of meaning from usersâ queries without the use of syntactic or semantic representations. Three approaches to identifying the usersâ intended meanings were investigated: keywordbased systems, Jaro-based string similarity algorithms and matching based on very shallow syntactic analysis. These were measured against a corpus of queries contributed by users of a WWW-hosted infobot for responding to questions about applications to MSc courses. The most effective system was Jaro with stemmed input (78.57%). It also was able to process ungrammatical input and offer scalability.
【 授权许可】
CC BY-NC-ND
【 预 览 】
Files | Size | Format | View |
---|---|---|---|
RO201904025001579ZK.pdf | 186KB | download |