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Patent analysis and mining are time-consuming and costly processes for companies, but nevertheless essential if they are willing to remain competitive. To face the overload induced by numerous patents, the idea is to automatically filter…
Applications such as textual entailment, plagiarism detection or document clustering rely on the notion of semantic similarity, and are usually approached with dimension reduction techniques like LDA or with embedding-based neural…
We consider inventions as novel combinations of existing technological capabilities. Patent data allow us to explicitly identify such combinatorial processes in invention activities. Unconsidered in the previous research, not every new…
In this paper, we extend some usual techniques of classification resulting from a large-scale data-mining and network approach. This new technology, which in particular is designed to be suitable to big data, is used to construct an open…
A crucial goal of funding research and development has always been to advance economic development. On this basis, a consider-able body of research undertaken with the purpose of determining what exactly constitutes economic impact and how…
Using the 138,751 patents filed in 2006 under the Patent Cooperation Treaty, co-classification analysis is pursued on the basis of three- and four-digit codes in the International Patent Classification (IPC, 8th edition). The…
One compelling use of citation networks is to characterize papers by their relationships to the surrounding literature. We propose a method to characterize papers by embedding them into two distinct "co-factor" spaces: one describing how…
The availability of large idea repositories (e.g., the U.S. patent database) could significantly accelerate innovation and discovery by providing people with inspiration from solutions to analogous problems. However, finding useful…
Algorithmic fairness has aroused considerable interests in data mining and machine learning communities recently. So far the existing research has been mostly focusing on the development of quantitative metrics to measure algorithm…
Valuing intangible assets under uncertainty remains a critical challenge in the strategic management of technological innovation due to the information asymmetry inherent in high-dimensional technical specifications. Traditional…
Understanding the topical evolution in industrial innovation is a challenging problem. With the advancement in the digital repositories in the form of patent documents, it is becoming increasingly more feasible to understand the innovation…
PaECTER is an open-source document-level encoder specific for patents. We fine-tune BERT for Patents with examiner-added citation information to generate numerical representations for patent documents. PaECTER performs better in similarity…
The present paper extends the literature investigating key drivers leading certain patents to exert a stronger influence on the subsequent technological developments (inventions) than other ones. We investigated six key determinants, as (i)…
We use an information-theoretic measure of linguistic similarity to investigate the organization and evolution of scientific fields. An analysis of almost 20M papers from the past three decades reveals that the linguistic similarity is…
In recent years several novel models were developed to process natural language, development of accurate language translation systems have helped us overcome geographical barriers and communicate ideas effectively. These models are…
A long-standing discussion is to what extent patents can be used to monitor trends in innovation activity. This study quantifies the amount and quality of information about actual innovation contained in the patent system, based on 4,460…
This article reviews the empirical evidence on the use of patent citations as a proxy for invention importance. It distinguishes between technical merit, private economic value, and social value, and surveys validation studies using expert…
In this study, we address the challenges in developing a deep learning-based automatic patent citation recommendation system. Although deep learning-based recommendation systems have exhibited outstanding performance in various domains…
While there has been substantial progress in learning suitable distance metrics, these techniques in general lack transparency and decision reasoning, i.e., explaining why the input set of images is similar or dissimilar. In this work, we…
This paper was was first drafted in 2001 as a formalization of the system described in U.S. patent U.S. 7,392,174. It describes a system for implementing a parser based on a kind of cross-product over vectors of contextually similar words.…