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The article presents and discusses a methodological procedure based on the functional density of information, which can be used for value‐added processing of bibliographic databases with scientific and technological information to predict and recognise trends in research and development fields. The concept of functional information density can be applied in processing bibliographic databases by specific search fields, such as: number of documents by the publication year, number of articles and patents by year, patent assignee, patent applications and granted patents by country, international patents classification codes, and journal titles. The proposed information procedure was tested on the research topics microencapsulation technology, microencapsulated pesticides, microencapsulated repellents and superabsorbents, and was used as an information support for design of research hypotheses, planning of research, development and marketing of products.

The article seeks to address a methodological procedure based on keyword analysis and the structuring of data into information systems in the field of functional foods, a newly‐emerging scientific field within the broader scope of food sciences and technology.

An experiment was undertaken by selection of a research field or research subject, selection of search profile, selection and processing of relevant databases, keyword analysis, and the arrangement of data (keywords) according to tree‐structures. Keyword analysis was employed to identify narrower research fields within the broader scientific field. The structuring of data into systems was used to classify the terms within the particular narrow field. Keywords with higher and lower frequency were identified. A classification tree was set up, based on keywords (thesaurus‐based descriptors) extracted from the FSTA (Food Science and Technology Abstracts) database available online. The tree was supplemented and upgraded with some additional topical terms that have not as yet been included in the existing thesaurus. To serve as a comparison a completely new classification tree was designed, based on online full‐text data.

Comparison of the two trees suggests that the previous existing tree is sufficiently accurate in representing the field of functional foods, provided that it is upgraded with some additional terms. A more accurate classification should improve thesauri and consequently enhance retrieval in international databases.

Presents a methodology of database analysis which may serve to improve database patterns, especially with regard to information retrieval.

The purpose of this paper is to discuss the issue of relevance in full‐text patent document searches from the viewpoint of end‐users in science and technology. It aims to present three cases of patent document analysis for relevance, with an additional case of improved search profile with increased relevance, and to summarise the findings in the form of instructions for users.

Two methodological approaches were used for the analysis of patent documents: value‐added processing of the bibliographic part of patent documents for the identification of trends; and structuring of data into systems for the determination of patent relevance. Overall, four sets of full‐text patent documents were analysed, covering the topics of: microencapsulated phase change materials; digital photography and image sensors; patent document processing; and patent analysis.

Value‐added analysis of the bibliographic parts of patent documents is a quick and useful option for the recognition of research trends. However, where non‐relevant patent documents are present in a data set, automatic bibliographic analysis may lead to conclusions that are mathematically and statistically correct, but that are not reliable or may even be incorrect for the user's research. Non‐adequate terminology is one of the main obstacles to relevant patent searches, especially if well‐defined keywords are non‐existent, as with cases of newly emerging and fast developing scientific and technological fields.

Based on the bibliographic and content analyses of patent documents, the paper provides instructions for users in the form of ten general rules for increasing the relevance of full‐text patent document searches.