Natural Language Processing and Fuzzy Tools for Business Processes in a Geolocation Context

Abstract

In the geolocation field where high-level programs and low-level devices coexist, it is often difficult to find a friendly user interface to configure all the parameters. The challenge addressed in this paper is to propose intuitive and simple, thus natural language interfaces to interact with low-level devices. Such interfaces contain natural language processing (NLP) and fuzzy representations of words that facilitate the elicitation of business-level objectives in our context. A complete methodology is proposed, from the lexicon construction to a dialogue software agent including a fuzzy linguistic representation, based on synonymy.

Stella

“…Object Geotagging Techniques. Many works have been conducted to geotag an object by using natural language processing (NLP) [30], incorporating user profile [7], or using machine learning techniques [31]. However, they suffer from two main limitations: (1) Each object type, e.g., text and image, requires its own tailored solution.…”

“…Motivated by the importance of applications that need geotagged data, there were several commercial and academic efforts for geotagging, e.g., see [30,31]. Unfortunately, most efforts are geared toward text-based data using natural language processing technique [30].…”

“…Motivated by the importance of applications that need geotagged data, there were several commercial and academic efforts for geotagging, e.g., see [30,31]. Unfortunately, most efforts are geared toward text-based data using natural language processing technique [30]. Meanwhile, there have been lack of research in image geotagging, where the state-of-the-art technique [31] suffers from low accuracy due to its over reliance with accurate training dataset.…”