Analyzing Sustainability Literature in Maritime Studies with Text Mining

The Text Mining Handbook - Advanced Approaches in Analyzing Unstructured Data

Text mining is a new and exciting area of computer science research that tries to solve the crisis of information overload by combining techniques from data mining, machine learning, natural language processing, information retrieval, and knowledge management. Similarly, link detection – a rapidly evolving approach to the analysis of text that shares and builds on many of the key elements of te...

Text Mining in Analyzing the Presentation of Educational Trainers

This work deals with Text analysis that involves information retrieval through lexical analysis to learn word occurrence and distributions, pattern recognition, information extraction, data mining techniques and followed by visualization, and predictive analytics. The primary goal is to turn text into data for analysis, through application of natural language processing (NLP) and analytical too...

Text Mining of Biomedical Literature Repositories

There is an increasing interest in the development of biomedical text mining applications not only to enable improved literature search, but also to automatically detect pointers between biologically relevant entities described in articles and their corresponding records in existing annotation databases. The rapid growth of natural language data in biomedical sciences (including scientific arti...

Improving Literature-Based Discovery with Advanced Text Mining

Automated Literature Based Discovery (LBD) generates new knowledge by combining what is already known in literature. Facilitating large-scale hypothesis testing and generation from huge collections of literature, LBD could significantly support research in biomedical sciences. However, the uptake of LBD by the scientific community has been limited. One of the key reasons for this is the limited...

Visual Text Mining: Ensuring the Presence of Relevant Studies in Systematic Literature Reviews