Resolving Terminology Heterogeneity in Digital Forensics Using the Web

Frequency generators are devices that are widely used in the field of medicine in an attempt to effect chemical changes in the human body for the purpose of curing certain diseases. In addition, it is believed by many medical practitioners and researchers that frequencies can be generated, using sympathetic resonance to stimulate organ function or even to physically vibrate offending bacteria, viruses and parasites, resulting in their elimination from the human body. Digital forensics, which is rather a relatively new branch of forensic science, has attracted a wider array of people, such as computer professionals, law enforcement agencies and practitioners, that always need to cooperate in this profession. However, this has inflicted new problems with terminology heterogeneity within the domain, analogous to the offending bacteria, viruses and parasites in the human body, which needs to be resolved and/or eliminated. This paper therefore, proposes a new method that uses the Web in an attempt to resolve terminology heterogeneity in the digital forensic domain. The proposed method is based on ‘terminology frequency’ which is automatically generated by the Web each time new information is added. We refer to this frequency as the Web Terminology Frequency (WTF) in this paper. Web search engines are however employed as tools that have the ability to capture the terminology frequencies. Finally, we show how the computed WTF is used to deduce a method coined as the ‘Terminology Heterogeneity Resolver’ (TE-HERE) in this paper. Experiments conducted using the proposed TE-HERE method focuses on the digital forensic domain terminologies. However, in the authors’ opinion, the TE-HERE which is technically simple and does not require any human-annotated knowledge can as well be applied in other domains. This is because the findings presented in this paper indicate that the TE-HERE method produce influential results. TE-HERE is a novel approach to resolving terminology heterogeneity in digital forensics and constitutes the main contribution of this paper