190 Int. J. Business Intelligence and Data Mining, Vol. 11, No. 2, 2016 Copyright © 2016 Inderscience Enterprises Ltd. BNEMiner: mining biomedical literature for extraction of biological target, disease and chemical entities Sindhuja Gopalan and Sobha Lalitha Devi* AU-KBC Research Centre, MIT Campus, Anna University, Chennai, India Email: sindhujagopalan@au-kbc.org Email: sobha@au-kbc.org *Corresponding author Abstract: The paper presents a novel application to extract biomedical entities automatically using machine learning techniques from large volumes of biomedical text. The data in large quantities are accumulating day by day and requires automatic extraction of information. Data mining is the science of extracting information from large data. Biomedical Named entity recognition (BioNER) is the task of data mining that extracts named entities from biological texts. In this paper, we focus on developing a BioNER system for extraction of biological target, disease and chemical entities from biomedical texts. We developed the system using graphical based machine learning technique the CRFs. We have applied a set of diverse features containing standard lexical, syntactic and orthographic features combined with novel and biologically inspired features, action terms and process verbs. The system was evaluated with three widely recognised datasets. The results demonstrated the portability and the potency of the system. Keywords: data mining; biomedical entities; graph-based model; biologically motivated features; portability. Reference to this paper should be made as follows: Gopalan, S. and Devi, S.L. (2016) ‘BNEMiner: mining biomedical literature for extraction of biological target, disease and chemical entities’, Int. J. Business Intelligence and Data Mining, Vol. 11, No. 2, pp.190–204. Biographical notes: Sindhuja Gopalan is a Research Engineer working with the Computational Linguistic Research Group of AU-KBC Research Centre, Anna University, Chennai, India. Her research interests include semantic text processing (data mining and text mining) and discourse analysis. She holds a Masters in Bioinformatics. Currently, she is pursuing her PhD in BioNLP with Sobha Lalitha Devi. She has participated in international tasks like BioCreative international event and CoNLL Shared Task. She was a Visiting Research Scholar at Universidad Politècnica de València (UPV). Sobha Lalitha Devi is a Scientist in the Information Sciences Division of AU-KBC Research Centre, Anna University, Chennai, India. Her research interests are in the field of discourse analysis, text mining, information extraction and retrieval. She specialises in the area of anaphora resolution. She works in various genre such as new wires, biomedical texts and also in various families of language.