Graph-based text representation is one of the important preprocessing steps in data and text
mining, Natural Language Processing (NLP), and information retrieval approaches. The …

Subjective paper evaluation is a tricky and tiresome task to do by manual labor. Insufficient
understanding and acceptance of data are crucial challenges while analyzing subjective …

In graph-based structural pattern recognition, the idea is to transform patterns into graphs
and perform the analysis and recognition of patterns in the graph domain—commonly …

Natural Language Processing (NLP) is a scientific discipline which is found at the
intersection of fields such as Artificial Intelligence, Linguistics, and Cognitive Psychology …

For information retrieval and text-mining, a robust scalable framework is required to
represent the information extracted from documents and enable visualization and query of …

This paper develops techniques to extract conceptual graphs from a patent claim using
syntactic information (POS, and dependency tree) and semantic information (background …

The exponential growth of available electronic data is almost useless without efficient tools
to retrieve the right information at the right time. This is especially crucial in the context of …

Abstract The Harmonized System of tariff nomenclature created by the Brussels-based
World Customs Organization is widely applied to standardize traded products with Code …

Conceptual graphs allow for powerful and computationally affordable representation of the
semantic contents of natural language texts. We propose a method of comparison …

As cross-lingual information retrieval is attracting increasing attention, tools that measure
cross-lingual semantic similarity between documents are becoming desirable. In this paper …