Natural Language Processing (NLP) – A Solution for Knowledge Extraction from Patent Unstructured Data

AbstractPatents are valuable source of knowledge and are extremely important for assisting engineers and decisions makers through the inventive process. This paper describes a new approach of automatic extraction of IDM (Inventive Design Method) related knowledge from patent documents. IDM derives from TRIZ, the theory of Inventive problem solving, which is largely based on patent's observation to theorize the act of inventing. Our method mainly consists in using natural language techniques (NLP) to match and extract knowledge relevant to IDM Ontology. The purpose of this paper is to investigate on the contribution of NLP techniques to effective knowledge extraction from patent documents. We propose in this paper to firstly report on progress made so far in data mining before describing our approach

The experiment in living

This article engages with debates about widening participation in social research by examining a specific form of public action and knowledge, namely experiments in sustainable living. I propose that these experiments may be approached as forms of social research, and as such offer special opportunities for social research to insert itself into wider societal research arrangements. The article develops the notion of the multifarious instrument which highlights that genres of public action may be put to divergent purposes which may not always be distinguished. I argue that may turn living experiments into critical sites of research, where sociologists may confront and challenge prevailing narrow formattings of the purpose of everyday experiments. I explore this claim further through two case studies: an analysis of sustainable living blogs, and an artistic experiment called Spiral Drawing Sunrise

Applications of TRIZ and Axiomatic Design: A Comparison to Deduce Best Practices in Industry☆

Abstract In the first decade of 2000s, several contributions have illustrated methods combining TRIZ and Axiomatic Design (AD). The strength of the connection was found in the complementary objectives AD and TRIZ pursue. AD is supposed to analyze the problem and structure it in the most convenient way, while TRIZ should solve the minimum number of design conflicts that are intrinsically present in a case study. Nevertheless, despite the promising match between AD and TRIZ, no conjoint application strategy has emerged as a reference, neither in academia, nor in industry. Conversely, the quantity has dropped of scientific papers contextually making reference to both methodologies. Some studies attempt to remark the methodological problems concerning the combination of AD and TRIZ. In a different perspective, the authors performed an application-oriented study, in order to point out the industrial domains for which the methodologies result the most suitable. The survey highlights that TRIZ is mostly employed for mass-market products, while AD is basically used to develop systems that industrial organizations make use of. The authors discuss the consequences of these findings, inferring how design can benefit from TRIZ and AD heuristics and the practical cases in which they are likely to be combined successfully

Improving interoperability on industrial standards through ontologies

Interoperability refers to the effective exchange of information and understanding to collectively pursue common objectives. System developers commonly use ontologies to enhance semantic and syntactic interoperability within this context. This work aims to evaluate the contribution of ontology in making explicit the meaning of the entities described in a Piping and Instrumentation Diagram (P&ID) model and to provide an architecture that allows the representation of a P&ID in ontological knowledge bases. To understand the semantics of the P&ID entities and relations, we map each class of the P&ID to the corresponding entity of the Offshore Petroleum Production Plant Ontology (O3PO). The ontology describes the definition of each vocable associated with the axioms that clarify and regulate the meaning and utilization of this vocabulary. We intend to guarantee that the integration of P&ID with other models respects the original semantics and avoids unintended data exchanges. We follow this ontological analysis with a case study of a model that conforms to the Data Exchange in the Process Industry (DEXPI) specification, intended to provide homogeneous data interchange between CAD systems from diverse vendors. The ontological analysis of the DEXPI P&ID specification, to build a relation with a well-founded ontology, raises a set of desirable properties for a model intended for use in interoperability. While achieving technical interoperability between DEXPI P&IDs and ontologies represented in OWL is evident, we identified several challenges within the realm of semantic interoperability, specifically concerning clarity/intelligibility, conciseness, extendibility, consistency, and essence. These issues present significant hurdles to achieving seamless systems integration. Moreover, if the DEXPI standard were to evolve into a de facto standard for representing P&IDs across a broader range of domains than initially intended, these highlighted issues could potentially bottleneck its adoption and hinder its integration into different systems.Interoperabilidade se refere à troca efetiva de informação e entendimento na busca por objetivos comuns. Neste contexto, desenvolvedores de sistemas comumente utilizam ontologias para aprimorar a interoperabilidade semântica e sintática. O objetivo deste trabalho é avaliar a contribuição da ontologia para tornar explícito o significado das entidades descritas em um modelo de Diagrama de Tubulação e Instrumentação (DTI) e fornecer uma arquitetura que permita a representação de um DTI em bases de conhecimento ontológicas. Para entender a semântica das entidades e relações do DTI, mapeamos cada classe do DTI para a entidade correspondente da Ontologia de Planta de Produção de Petróleo Offshore (O3PO). A ontologia descreve a definição de cada vocábulo associado com os axiomas que esclarecem e regulam o significado e a utilização desse vocabulário. Pretendemos garantir que a integração do DTI com outros modelos respeite a semântica original e, assim, evite trocas de dados não intencionais. Seguimos essa análise ontológica com um estudo de caso de um modelo que se conforma à especificação "Data Exchange in the Process Industry" (DEXPI), destinada a fornecer uma troca de dados homogênea entre sistemas CAD de diversos fabricantes. A análise ontológica da especificação DEXPI DTI, para construir uma relação com uma ontologia bem fundamentada, levanta um conjunto de propriedades desejáveis para um modelo destinado a ser usado na interoperabilidade. Embora a conquista da interoperabilidade técnica entre DTIs DEXPI e ontologias representadas em OWL seja evidente, diversos desafios foram identificados no âmbito da interoperabilidade semântica, especificamente em relação à clareza/inteligibilidade, concisão, extensibilidade, consistência e essência. Essas questões representam obstáculos significativos para alcançar uma integração de sistemas perfeita. Além disso, se o padrão DEXPI evoluir para um padrão de facto para a representação de DTIs em um conjunto mais amplo de domínios do que inicialmente pretendido, essas questões destacadas poderiam potencialmente atrasar sua adoção e dificultar sua integração em sistemas diferentes

New frontiers in qualitative longitudinal research: an agenda for research

This paper outlines the state of the art in qualitative longitudinal methodology, reflecting on more than 10 years of development since a previous special issue on QLR was published by the International Journal of Social Research Methodology in 2003. The papers presented in this special issue emerge from a methodological innovation network that brought together an international community of researchers in order to map new frontiers for the method. This paper summarises the development of the method from a design to a sensibility, identifying three new frontiers as part of a future research agenda including: the need for a processual imaginary; experimentation with temporal perspectives and orientations and explicating the temporal affordances of our methods

Using Cyber-enabled Transaction Data to Study Productivity and Innovation in Organizations

This paper draws on recent research in a wide variety of disciplines to identify the key elements necessary to build an empirical infrastructure that will advance research on one of the key building blocks of science and innovation policy: organizations. We argue that cyber-tools and new data will permit researchers to examine the innovation process |both successes and failures| and explore business performance and business dynamics at the level of the appropriate economic entity. We develop a roadmap that outlines how the new data can be developed, from harvesting the web to direct observation from deep within companies. The paper identifies a set of research questions and an approach whose pursuit could be used to develop a national research data infrastructure for the study of innovation and organizational performance. One key element of the approach is to identify and study innovation processes within organizations by collecting data on inputs and outcomes of innovation projects (or initiatives) within organizations. Another is the collection of representative data by business function/processes across firms, a proven statistical and economic approach (Sturgeon et al. 2006, Brown 2008, Lewin et al 2008). Finally, we argue that the work to develop new data from deep within firms should involve the participation of computer and information scientists. Opportunities for quasi experimental approaches to data collection, and noninvasive techniques to harvest data from within firms (i.e., auto-populating of researcher databases) need to be explored. More generally, the bringing together of scientists to consider business microdata privacy/access and data collection from organizations is itself significant, with potential for creating opportunities in a broad range of applications.

Opportunity Identification for New Product Planning: Ontological Semantic Patent Classification

Intelligence tools have been developed and applied widely in many different areas in engineering, business and management. Many commercialized tools for business intelligence are available in the market. However, no practically useful tools for technology intelligence are available at this time, and very little academic research in technology intelligence methods has been conducted to date. Patent databases are the most important data source for technology intelligence tools, but patents inherently contain unstructured data. Consequently, extracting text data from patent databases, converting that data to meaningful information and generating useful knowledge from this information become complex tasks. These tasks are currently being performed very ineffectively, inefficiently and unreliably by human experts. This deficiency is particularly vexing in product planning, where awareness of market needs and technological capabilities is critical for identifying opportunities for new products and services. Total nescience of the text of patents, as well as inadequate, unreliable and untimely knowledge derived from these patents, may consequently result in missed opportunities that could lead to severe competitive disadvantage and potentially catastrophic loss of revenue. The research performed in this dissertation tries to correct the abovementioned deficiency with an approach called patent mining. The research is conducted at Finex, an iron casting company that produces traditional kitchen skillets. To \u27mine\u27 pertinent patents, experts in new product development at Finex modeled one ontology for the required product features and another for the attributes of requisite metallurgical enabling technologies from which new product opportunities for skillets are identified by applying natural language processing, information retrieval, and machine learning (classification) to the text of patents in the USPTO database. Three main scenarios are examined in my research. Regular classification (RC) relies on keywords that are extracted directly from a group of USPTO patents. Ontological classification (OC) relies on keywords that result from an ontology developed by Finex experts, which is evaluated and improved by a panel of external experts. Ontological semantic classification (OSC) uses these ontological keywords and their synonyms, which are extracted from the WordNet database. For each scenario, I evaluate the performance of three classifiers: k-Nearest Neighbor (k-NN), random forest, and Support Vector Machine (SVM). My research shows that OSC is the best scenario and SVM is the best classifier for identifying product planning opportunities, because this combination yields the highest score in metrics that are generally used to measure classification performance in machine learning (e.g., ROC-AUC and F-score). My method also significantly outperforms current practice, because I demonstrate in an experiment that neither the experts at Finex nor the panel of external experts are able to search for and judge relevant patents with any degree of effectiveness, efficiency or reliability. This dissertation provides the rudiments of a theoretical foundation for patent mining, which has yielded a machine learning method that is deployed successfully in a new product planning setting (Finex). Further development of this method could make a significant contribution to management practice by identifying opportunities for new product development that have been missed by the approaches that have been deployed to date

A Systematic review of ontology-based approach and decision-making (DM) to improve public service delivery (PSD)

A systematic review of the DM literature on PSD was performed with the aim to build an operational ontology-based for decision makers. Five public administration journals were screened on the subject with more than 200 articles found. 29 articles were shortlisted, categorised, summarised, and applied to outline the influential factors in DM for PSD. The result of the systematic reviews also provided a brief clarification on the requirement for the creation of a more citizen-centric and coordinated eco-system for efficient PSD underpinned by effective DM