Index to Library Trends Volume 38

published or submitted for publicatio

An Investigative Study Of Patents From An Engineering Design Perspective

Preservation and reuse of valuable design experience aids in the design of new products and processes. Product design repositories are presently being used as a means to preserve and later reuse design knowledge. As such, patent databases such as the United States Patent office and the European Patent Office offer design knowledge in the form of patents. Unfortunately, these sources of novel design solutions do not appear to have been have not been effectively used in the context of engineering design. In this research, the role of patents in a systematic design process is reviewed understand its utility in the design process. A major hurdle, in the reuse of patent design knowledge, is the lack of formal tools to support designers in understanding and applying the available information to new problems. Information theory fundamentals are used to study patent claim text which describes the subject matter of the patent and to develop an understanding of the information content within the text claim and other representations of the claim. Graph based representations are recognized as an effective way to represent design information. They are considered as ideal for modeling patent claims as they enable the direct use of the information as input to existing design processes and tools, such as function models, the core product model, and function-behavior-structure scheme. This new approach provides a designer-friendly model of patent claims and also enables the use of intelligent search mechanisms. Existing graph based product representation schemas are studied for their suitability to model patent claims. A new representation tailored for patent claims is proposed since, the existing schemas where found to be insufficient to efficiently model patent claim. Patent claims modeled using multiple representation schemas are compared with the models developed using the proposed representation, for the information content captured from claim text. The representation technique proposed here may aid in the retrieval of the relevant patent design information, thereby promoting use of patent information to aid designers. Further refinement and evaluation of the scheme along with the development of grammar and ontologies for a vocabulary is needed. This representation scheme, with existing search and retrieval methods, should help designers in generating both novel and practical concepts based on patent information

A Convolutional Neural Network-based Patent Image Retrieval Method for Design Ideation

The patent database is often used in searches of inspirational stimuli for innovative design opportunities because of its large size, extensive variety and rich design information in patent documents. However, most patent mining research only focuses on textual information and ignores visual information. Herein, we propose a convolutional neural network (CNN)-based patent image retrieval method. The core of this approach is a novel neural network architecture named Dual-VGG that is aimed to accomplish two tasks: visual material type prediction and international patent classification (IPC) class label prediction. In turn, the trained neural network provides the deep features in the image embedding vectors that can be utilized for patent image retrieval and visual mapping. The accuracy of both training tasks and patent image embedding space are evaluated to show the performance of our model. This approach is also illustrated in a case study of robot arm design retrieval. Compared to traditional keyword-based searching and Google image searching, the proposed method discovers more useful visual information for engineering design.Comment: 11 pages, 11 figure

Patent Data for Engineering Design: A Critical Review and Future Directions

Patent data have long been used for engineering design research because of its large and expanding size, and widely varying massive amount of design information contained in patents. Recent advances in artificial intelligence and data science present unprecedented opportunities to develop data-driven design methods and tools, as well as advance design science, using the patent database. Herein, we survey and categorize the patent-for-design literature based on its contributions to design theories, methods, tools, and strategies, as well as the types of patent data and data-driven methods used in respective studies. Our review highlights promising future research directions in patent data-driven design research and practice.Comment: Accepted by JCIS

Keyword Based Search and its Limitations in the Patent Document to Secure the Idea from its Infringement

AbstractIntellectual Properties (IP's) are attracting progressively growing popularity for corporate houses and the academia in the current years. Patent system is one of them which generate high economical values of the IP rights. This in turn calls for the increased work responsibility of patent prior art search to generate effective patent search reports for the innovator (s). In the field of patent innovations, prior knowledge of innovative steps of the technologies developed so far must be known to innovator (s). In the present research work, technology/ patent search based on keywords has been investigated to arrive at the usefulness of the methodology particularly for the case of patent documents. The present paper helps to figure out the limitations and the scope of the methodology for patent prior art search based on extent of the keywords

Spherical harmonics coeffcients for ligand-based virtual screening of cyclooxygenase inhibitors

Background: Molecular descriptors are essential for many applications in computational chemistry, such as ligand-based similarity searching. Spherical harmonics have previously been suggested as comprehensive descriptors of molecular structure and properties. We investigate a spherical harmonics descriptor for shape-based virtual screening. Methodology/Principal Findings: We introduce and validate a partially rotation-invariant three-dimensional molecular shape descriptor based on the norm of spherical harmonics expansion coefficients. Using this molecular representation, we parameterize molecular surfaces, i.e., isosurfaces of spatial molecular property distributions. We validate the shape descriptor in a comprehensive retrospective virtual screening experiment. In a prospective study, we virtually screen a large compound library for cyclooxygenase inhibitors, using a self-organizing map as a pre-filter and the shape descriptor for candidate prioritization. Conclusions/Significance: 12 compounds were tested in vitro for direct enzyme inhibition and in a whole blood assay. Active compounds containing a triazole scaffold were identified as direct cyclooxygenase-1 inhibitors. This outcome corroborates the usefulness of spherical harmonics for representation of molecular shape in virtual screening of large compound collections. The combination of pharmacophore and shape-based filtering of screening candidates proved to be a straightforward approach to finding novel bioactive chemotypes with minimal experimental effort

Natural Language Processing in-and-for Design Research

We review the scholarly contributions that utilise Natural Language Processing (NLP) methods to support the design process. Using a heuristic approach, we collected 223 articles published in 32 journals and within the period 1991-present. We present state-of-the-art NLP in-and-for design research by reviewing these articles according to the type of natural language text sources: internal reports, design concepts, discourse transcripts, technical publications, consumer opinions, and others. Upon summarizing and identifying the gaps in these contributions, we utilise an existing design innovation framework to identify the applications that are currently being supported by NLP. We then propose a few methodological and theoretical directions for future NLP in-and-for design research

Special Libraries, January 1966

Volume 57, Issue 1https://scholarworks.sjsu.edu/sla_sl_1966/1000/thumbnail.jp

Total Technology Space Map as a Digital Platform

A strand of recent studies utilized complete patent databases and classification systems to construct large network maps of patent technology classes, which might approximate the total technology space. It has been argued that such maps are useful for competitive intelligence analysis, technology road mapping, innovation decision support, and so on in the literature. In this paper, we illustrate the InnoGPS system to integrate such a map with various map-based visual analytic functions for technology navigation, positioning, neighborhood exploration, path finding and information retrieval. These analytics are either descriptive, predictive or prescriptive. During the process of developing InnoGPS, we have conceived a wide spectrum of other potential applications of the total technology space map for consumers, business, education and so on. These possibilities together with the difficulty to construct an accurate technology space representation suggest the strategic value to develop the total technology space map as a digital platform for any applications to discover, manage or represent any data, information and knowledge related to technologies, and to nurture an ecosystem of developers and users

Government Information Quarterly. Volume 7, no. 2: National Aeronautics and Space Administration Scientific and Technical Information Programs. Special issue

NASA scientific and technical information (STI) programs are discussed. Topics include management of information in a research and development agency, the new space and Earth science information systems at NASA's archive, scientific and technical information management, and technology transfer of NASA aerospace technology to other industries