Automatic extraction of function-behaviour-state information from patents

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Innovation through pertinent patents research based on physical phenomena involved

One can find innovative solutions to complex industrial problems by looking for knowledge in patents. Traditional search using keywords in databases of patents has been widely used. Currently, different computational methods that limit human intervention have been developed. We aim to define a method to improve the search for relevant patents in order to solve industrial problems and specifically to deduce evolution opportunities. The non-automatic, semi-automatic, and automatic search methods use keywords. For a detailed keyword search, we propose as a basis the functional decomposition and the analysis of the physical phenomena involved in the achievement of the function to fulfill. The search for solutions to design a bi-phasic separator in deep offshore shows the method presented in this paper

ARIZ85 and patent-driven knowledge support

AbstractThe growing complexity of technical solutions, which encompass knowledge from different scientific fields, makes necessary, also for multi-disciplinary working teams, the consultation of information sources. Indeed, tacit knowledge is essential, but often not sufficient to achieve a proficient problem solving process. Besides, the most comprehensive tool of the TRIZ body of knowledge, i.e. ARIZ, requires, more or less explicitly, the retrieval of new knowledge in order to entirely exploit its potential to drive towards valuable solutions.A multitude of contributions from the literature support various common tasks encountered when using TRIZ and requiring additional information; most of them hold the objective of speeding up the generation of inventive solutions thanks to the capabilities of text mining techniques. Nevertheless, no global study has been conducted to fully disclose the effective knowledge requirements of ARIZ. With respect to this deficiency, the present paper illustrates an analysis of the algorithm with the specific objective of identifying the different types of information needs that can be satisfied by patents. The results of the investigation lay bare the most significant gaps of the research in the field. Further on, an initial proposal is advanced to structure the retrieval of relevant information from patent sources currently not supported by existing methodologies and software applications, so as to exploit the vast amount of technical knowledge contained in there. An illustrative experiment sheds light on the relevance of control parameters as input terms for the definition of search queries aimed at retrieving patents sharing the same physical contradiction of the problem to be treated

Knowledge based Approach for Formulating TRIZ Contradictions

AbstractThe article presents how to innovate a product using information extraction from patents literature to identify and overcome TRIZ contradictions. Each initial inventive situation has to be formulated in terms of contradictions in order to use the most effective tool for problem solving provided by the TRIZ theory.The authors propose, (1) an algorithm guiding the user to move from an indefinite problem situation to obtain a clearer problem formulation, following a process inspired to the ARIZ approach for fixing physical contradictions, and (2) some strategies and tools for selecting, acquiring and finally modeling the necessary information to improve the effectiveness in building the contradiction model.All those strategies have been implemented in a knowledge management tool called KOM, working as an automatic patent searching engine based on a functional oriented search. An exemplary application is presented to explain how KOM is integrated in the problem definition process

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

Time-varying model identification for time-frequency feature extraction from EEG data

A novel modelling scheme that can be used to estimate and track time-varying properties of nonstationary signals is investigated. This scheme is based on a class of time-varying AutoRegressive with an eXogenous input (ARX) models where the associated time-varying parameters are represented by multi-wavelet basis functions. The orthogonal least square (OLS) algorithm is then applied to refine the model parameter estimates of the time-varying ARX model. The main features of the multi-wavelet approach is that it enables smooth trends to be tracked but also to capture sharp changes in the time-varying process parameters. Simulation studies and applications to real EEG data show that the proposed algorithm can provide important transient information on the inherent dynamics of nonstationary processes

Forecasting the Spreading of Technologies in Research Communities

Technologies such as algorithms, applications and formats are an important part of the knowledge produced and reused in the research process. Typically, a technology is expected to originate in the context of a research area and then spread and contribute to several other fields. For example, Semantic Web technologies have been successfully adopted by a variety of fields, e.g., Information Retrieval, Human Computer Interaction, Biology, and many others. Unfortunately, the spreading of technologies across research areas may be a slow and inefficient process, since it is easy for researchers to be unaware of potentially relevant solutions produced by other research communities. In this paper, we hypothesise that it is possible to learn typical technology propagation patterns from historical data and to exploit this knowledge i) to anticipate where a technology may be adopted next and ii) to alert relevant stakeholders about emerging and relevant technologies in other fields. To do so, we propose the Technology-Topic Framework, a novel approach which uses a semantically enhanced technology-topic model to forecast the propagation of technologies to research areas. A formal evaluation of the approach on a set of technologies in the Semantic Web and Artificial Intelligence areas has produced excellent results, confirming the validity of our solution

Functional technology foresight. A novel methodology to identify emerging technologies

The speed and complexity of the technology evolution faced by modern societies need new approaches to the analysis and understanding of the world. Indeed, an exclusive focus on technological goals can miss to recognize all the stakeholders of a technology and address real user needs; moreover, on the one hand low signals are becoming more and more important in fast evolving markets, on the other hand the excess of hype, fashions, or vested interests sometimes deeply alter indicators. However, the so called Big Data promise to be a huge low cost set of valuable information, available and affordable to all (SMEs included). But, analyzing them is not trivial especially if we deal with academic papers and patents. To tackle these issues, the present paper proposes to apply a powerful methodological tool called Functional Analysis to the Technology Foresight process. Actually the rigorous study of the functions, that an artefact should perform to satisfy the user needs, provides a universal and thus unifying point of view, which is able to correlate the user perspective on the product with its technical features. Functional reasoning has been applied to (i) detect possible patterns of development, spotting missing elements and highlighting strengths as well as potential sources of failure; (ii) to enhance traditional bibliometric tools such as the analysis of S-curves and (iii), integrated with a natural language processing analysis toolchain, tailored for patent documents, to identify emerging technologies. The paper describes the functional approach to technology foresight activity, presents how to integrate it with text mining algorithms and experts’ domain knowledge, and finally discusses its benefits in the context of Technology Foresight also from an economic point of view, showing that oresight is affordable also for Small and Medium Enterprises