A document similarity approach using grammatical linkages with graph databases Online publication date: Mon, 21-Oct-2019
by V. Priya; K. Umamaheswari
International Journal of Enterprise Network Management (IJENM), Vol. 10, No. 3/4, 2019
Abstract: Document similarity had become essential in many applications such as document retrieval, recommendation systems, plagiarism checker, etc. Many similarity evaluation approaches rely on word-based document representation, because it is very fast. But these approaches are not accurate when documents with different language and vocabulary are used. When graph representation is used for documents they use some relational knowledge which is not feasible in many applications because of expensive graph operations. In this work a novel approach for document similarity computation which utilises verbal intent has been developed. This improves the similarity by increasing the number of linkages using verbs between two documents. Graph databases were used for faster performance. The performance of the system is evaluated using various metrics like cosine similarity, jaccard similarity and dice with different review datasets. The verbal intent-based approach has registered promising results based on the links between two documents.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Enterprise Network Management (IJENM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com