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The purpose of this paper is to show how the documentation movement associated with the utopian thinkers Paul Otlet and Henri La Fontaine relied on patent offices as well as the documents most closely associated with this institutional setting – the patents themselves – as central to the formation of the document category. The main argument is that patents not only were subjected to and helped construct, but also in fact engineered the development of technoscientific order during 1895–1937.

The paper draws on an interdisciplinary approach to intellectual property, document theory and insights from media archeology. Focused on the historical period 1895–1937, this study allows for an analysis that encapsulates and accounts for change in a number of comparative areas, moving from bibliography to documentation and from scientific to technoscientific order. Primary sources include Paul Otlet’s own writings, relevant contemporary sources from the French documentation movement and the Congrès Mondial de la documentation universelle in 1937.

By understanding patent offices and patents as main drivers behind those processes of sorting and classification that constitute technoscientific order, this explorative paper provides a new analytical framework for the study of intellectual property in relation to the history of information and documentation. It argues that the idea of the document may serve to rethink the role of the patent in technoscience, offering suggestions for new and underexplored venues of research in the nexus of several overlapping research fields, from law to information studies.

Debates over the legitimacy and rationale of intellectual property have raged for many years without signs of abating. Universities, research centers, policy makers, editors and scholars, research funders, governments, libraries and archives all have things to say on the legitimacy of the patent system, its relation to innovation and the appropriate role of intellectual property in research and science, milieus that are of central importance in the knowledge-based economy. The value of this paper lies in proposing a new way to approach patents that could show a way out of the current analytical gridlock of either/or that for many years has earmarked the “openness-enclosure” dichotomy. The combination of intellectual property scholarship and documentation theory provides important new insight into the historical networks and processes by which patents and documents have consolidated and converged during the twentieth century.

Large collections of patent documents disclosing novel, non-obvious technologies are publicly available and beneficial to academia and industries. To maximally exploit its potential, searching these patent documents has increasingly become an important topic. Although much research has processed a large size of collections, a few studies have attempted to integrate both patent classifications and specifications for analyzing user queries. Consequently, the queries are often insufficiently analyzed for improving the accuracy of search results. This paper aims to address such limitation by exploiting semantic relationships between patent contents and their classification.

The contributions are fourfold. First, the authors enhance similarity measurement between two short sentences and make it 20 per cent more accurate. Second, the Graph-embedded Tree ontology is enriched by integrating both patent documents and classification scheme. Third, the ontology does not rely on rule-based method or text matching; instead, an heuristic meaning comparison to extract semantic relationships between concepts is applied. Finally, the patent search approach uses the ontology effectively with the results sorted based on their most common order.

The experiment on searching for 600 patent documents in the field of Logistics brings better 15 per cent in terms of F-Measure when compared with traditional approaches.

The research, however, still requires improvement in which the terms and phrases extracted by Noun and Noun phrases making less sense in some aspect and thus might not result in high accuracy. The large collection of extracted relationships could be further optimized for its conciseness. In addition, parallel processing such as Map-Reduce could be further used to improve the search processing performance.

The experimental results could be used for scientists and technologists to search for novel, non-obvious technologies in the patents.

High quality of patent search results will reduce the patent infringement.

The proposed ontology is semantically enriched by integrating both patent documents and their classification. This ontology facilitates the analysis of the user queries for enhancing the accuracy of the patent search results.

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.

Despite their daunting reputation, patent documents, or copies of them, are in fact remarkably easy to acquire. Although some million patent specifications are published each year for approximately half that number of new inventions, confusion is in general avoided because of the influence of the World Intellectual Property Organization (WIPO), which enables the 40 patent offices to work together in the cause of universal availability, to standardize their documents and to designate them uniquely. The somewhat complicated publication sequence and numbering systems of patents, both in the UK and overseas, are explained. There are many sources of supply for published patent specifications, both national and international, public and private sector, to meet varying needs, whether document or information‐centred. Amongst these are the patent offices (both national and international), regional sub‐offices, national technical libraries, depository centres and various private sector services. Finally, a reminder is given that the Science Reference and Information Service is itself a specialist both in the supply of patent documents and in information about them.

In an era of rapidly expanding digital content, the number of e‐documents and the amount of knowledge frequently overwhelm the R&D teams and often impede intellectual property management. The purpose of this paper is to develop an automatic patent summarization method for accurate knowledge abstraction and effective R&D knowledge management.

This paper develops an integrated approach for automatic patent summary generation combining the concepts of key phrase recognition and significant information density. Significant information density is defined based on the domain‐specific key concepts/phrases, relevant phrases, title phrases, indicator phrases and topic sentences of a given patent document.

The document compression ratio and the knowledge retention ratio are used to measure both quantitative and qualitative outcomes of the new summarization methodology. Both measurements indicate the significant benefits and superior results of the method.

In order to implement the methodology with practical success, the accurate and efficient pre‐processing of identifying key concepts and relevant phrases of patent documents is required. The approach relies on a powerful text‐mining engine as the pre‐process module for key phrase extraction.

The methodology helps R&D companies consistently and automatically process, extract and summarize the core knowledge of related patent documents. This enabling technology is critical to R&D companies when they are competing to create new technologies and products for short life cycle marketplaces.

This research addresses a new perspective in R&D knowledge management, particularly in solving the knowledge‐overloading issue. The methodology helps R&D collaborative teams consistently to summarize the core knowledge of patent documents with efficiency. Efficient R&D knowledge management helps the firm to take advantage of IP positioning while avoiding patent conflict and infringement.

The purpose of this paper is to propose an objective method for technology forecasting (TF). For the construction of the proposed model, the paper aims to consider new approaches to patent mapping and clustering. In addition, the paper aims to introduce a matrix map and K‐medoids clustering based on support vector clustering (KM‐SVC) for vacant TF.

TF is an important research and development (R&D) policy issue for both companies and government. Vacant TF is one of the key technological planning methods for improving the competitive power of firms and governments. In general, a forecasting process is facilitated subjectively based on the researcher's knowledge, resulting in unstable TF performance. In this paper, the authors forecast the vacant technology areas in a given technology field by analyzing patent documents and employing the proposed matrix map and KM‐SVC to forecast vacant technology areas in the management of technology (MOT).

The paper examines the vacant technology areas for MOT patent documents from the USA, Europe, and China by comparing these countries in terms of technology trends in MOT and identifying the vacant technology areas by country. The matrix map provides broad vacant technology areas, whereas KM‐SVC provides more specific vacant technology areas. Thus, the paper identifies the vacant technology areas of a given technology field by using the results for both the matrix map and KM‐SVC.

The authors use patent documents as objective data to develop a model for vacant TF. The paper attempts to objectively forecast the vacant technology areas in a given technology field. To verify the performance of the matrix map and KM‐SVC, the authors conduct an experiment using patent documents related to MOT (the given technology field in this paper). The results suggest that the proposed forecasting model can be applied to diverse technology fields, including R&D management, technology marketing, and intellectual property management.

Most TF models are based on qualitative and subjective methods such as Delphi. That is, there are few objective models. In this regard, this paper proposes a quantitative and objective TF model that employs patent documents as objective data and a matrix map and KM‐SVC as quantitative methods.

This study aims to examine manually formulated queries and automatic query generation in an early phase of a patent “prior art” search.

The study was performed partly within a patent domain setting, involving three professional patent examiners, and partly in the context of the CLEF 2009 Intellectual Property (CLEF-IP) track. For the exploratory study of user-based query formulation, three patent examiners performed the same three simulated real-life patent tasks. For the automatic query generation, a simple term-weighting algorithm based on the RATF formula was used. The manually and automatically created queries were compared to analyse what kinds of keywords and from which parts of the patent documents were selected.

For user-formulated queries, it was found that patent documents were read in a specific order of importance and that the time varied. Annotations and collaboration were made while reading and selecting/ranking terms. Ranking terms was experienced to be harder than selecting terms. For the automatic formulated queries, it was found that the term frequencies used in the RATF alone will not quite approximate what terms will be judged as relevant query terms by the users. Simultaneously, the results suggest that developing a query generation tool for generating initial queries based on patent documents is feasible.

These preliminary but informative results need to be viewed in the light that only three patent experts were observed and that a small set of topics was used.

It is usually difficult to get access to the setting of the patent domain and the results of the study show that the methodology provided a feasible way to study manual and the manual query formulation of the patent engineer.

To begin with I should explain my relatively short acquaintance with documentation matters. Until three and a half years ago my experience was entirely on the examining side of the Patent Office and my acquaintance with the documentation side (or classification section as it is more familiarly known in the Patent Office) was limited to reorganizing several of my search files. Due to a series of retirements at the office I suddenly found myself translated to the Classification Section with the need to catch up very rapidly on classification theory and practice as it applied to patent documents, and in particular to become acquainted with the international organizations operative in this field.

Smart manufacturing can lead to disruptive changes in production technologies and business models in the manufacturing industry. This paper aims to identify technological topics in smart manufacturing by using patent data, investigating technological trends and exploring potential opportunities.

The latent Dirichlet allocation (LDA) topic modeling technique was used to extract latent technological topics, and the generalized linear mixed model (GLMM) was used to analyze the relative emergence levels of the topics. Topic value and topic competitive analyses were developed to evaluate each topic's potential value and identify technological positions of competing firms, respectively.

A total of 14 topics were extracted from the collected patent data and several fast growth and high-value topics were identified, such as smart connection, cyber-physical systems (CPSs), manufacturing data analytics and powder bed fusion additive manufacturing. Several leading firms apply broad R&D emphasis across a variety of technological topics, while others focus on a few technological topics.

The developed methodology can help firms identify important technological topics in smart manufacturing for making their R&D investment decisions. Firms can select appropriate technology strategies depending on the topic's emergence position in the topic strategy matrix.

Previous research studies have not analyzed the maturity levels of technological topics. The topic-based patent analytics approach can complement previous studies. In addition, this study provides a multi-valuation framework for exploring technological opportunities, thus providing valuable information that supports a more robust understanding of the technology landscape of smart manufacturing.

Discusses the factors that have contributed to the increased awareness and use of patents as sources of scientific and technical information. Examines the problems the growth in the number of patents has caused for traditional paper storage, the use of microform and CD‐ROM as solutions, and other patent services offered by the British Library. Concludes that the volume of patent documents has been a factor in the neglect of a valuable information source in the past, new services are helping disseminate the information more widely.