Corporate document mining for technology intelligence: An analysis of needs, utilization and possibilities

This paper focuses on document data, one of the most significant sources for technology intelligence. To help organisations use their knowledge in documents effectively, this research aims to identify what organizations really want from documents and what might be possible to obtain from them. The research involves a literature review, a series of in-depth/on-site interviews and a descriptive analysis of document mining applications. The output of the research includes: a document mining framework; an analysis of the current condition of document mining in technology-based organisations together with their future requirements; and guidelines for introducing document mining into an organisation along with a discussion on the practical issues that are faced by users. Copyright © 2011 Inderscience Enterprises Ltd.

The Impact of Contract Type on Service Provider Information Requirements

This paper is concerned with the role of information in the servitization of manufacturing which has led to “the innovation of an organisation’s capabilities and processes as equipment manufacturers seek to offer services around their products” (Neely 2009, Baines et al 2009). This evolution has resulted in an information requirement (IR) shift as companies move from discrete provision of equipment and spare parts to long-term service contracts guaranteeing prescribed performance levels. Organisations providing such services depend on a very high level of availability and quality of information throughout the service life-cycle (Menor et al 2002). This work focuses on whether, for a proposed contract based around complex equipment, the Information System is capable of providing information at an acceptable quality and requires the IRs to be examined in a formal manner. We apply a service information framework (Cuthbert et al 2008, McFarlane & Cuthbert 2012) to methodically assess IRs for different contract types to understand the information gap between them. Results from case examples indicate that this gap includes information required for the different contract types and a set of contract-specific IRs. Furthermore, the control, ownership and use of information differs across contract types as the boundary of operation and responsibility changes.

Analysis of document-mining techniques and tools for technology intelligence: Discovering knowledge from technical documents

This research proposes a method for extracting technology intelligence (TI) systematically from a large set of document data. To do this, the internal and external sources in the form of documents, which might be valuable for TI, are first identified. Then the existing techniques and software systems applicable to document analysis are examined. Finally, based on the reviews, a document-mining framework designed for TI is suggested and guidelines for software selection are proposed. The research output is expected to support intelligence operatives in finding suitable techniques and software systems for getting value from document-mining and thus facilitate effective knowledge management. Copyright © 2012 Inderscience Enterprises Ltd.

Structuring technological information for technology roadmapping: Data mining approach

Most research on technology roadmapping has focused on its practical applications and the development of methods to enhance its operational process. Thus, despite a demand for well-supported, systematic information, little attention has been paid to how/which information can be utilised in technology roadmapping. Therefore, this paper aims at proposing a methodology to structure technological information in order to facilitate the process. To this end, eight methods are suggested to provide useful information for technology roadmapping: summary, information extraction, clustering, mapping, navigation, linking, indicators and comparison. This research identifies the characteristics of significant data that can potentially be used in roadmapping, and presents an approach to extracting important information from such raw data through various data mining techniques including text mining, multi-dimensional scaling and K-means clustering. In addition, this paper explains how this approach can be applied in each step of roadmapping. The proposed approach is applied to develop a roadmap of radio-frequency identification (RFID) technology to illustrate the process practically. © 2013 © 2013 Taylor & Francis.