Community structure in co-inventor networks affects time to first citation for patents

Doonan, William F.; Higham, Kyle; Governale, Michele; Zülicke, U.

doi:10.1007/s41109-019-0126-3

Cited by 5 publications

(6 citation statements)

References 45 publications

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“…The authors in reference [ 9 ] believe that preprocessing plays an important role in the dynamic recommender structure. In this study, a similarity criterion to the clustering algorithm is added, which shows that the simulation results show that the similarity of the results is much better than the previous clustering criteria.…”

Section: Related Workmentioning

confidence: 99%

A Movie Recommender System Based on User Profile and Artificial Bee Colony Optimization

Rajabi Kouchi,

Oftadeh Balani,

Esmaeilpour

et al. 2023

Computational Intelligence and Neuroscience

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In this study, a new algorithm for recommending movies to viewers has been proposed. To do this, the suggested method employs data mining techniques. The proposed method includes three steps for generating recommendations: “preprocessing of user profile information,” “feature extraction,” and “recommendation.” In the first step of proposed method, the user information will be examined and transformed into a form that can be handled in the next phases. In the second step of the proposed method, user attributes are then extracted as a collection of their individual qualities, as well as the average rating of each user for various genres. The bee colony optimization algorithm is then used to select the optimal features. Finally, in the third step of the proposed method, the ratings of similar users are utilized to offer movies to the target user, and the similarities between various users are determined using the characteristics calculated for them, as well as the Euclidean distance criteria. The proposed method was evaluated using the MovieLens database, and its output was assessed in terms of precision and recall criteria; these results show that the proposed method will increase the precision by an average of 1.39% and the recall by 0.8% compared to the compared algorithms.

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Section: Related Workmentioning

confidence: 99%

A Movie Recommender System Based on User Profile and Artificial Bee Colony Optimization

Rajabi Kouchi,

Oftadeh Balani,

Esmaeilpour

et al. 2023

Computational Intelligence and Neuroscience

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“…The purpose of this study is to investigate the relationship between collaboration and innovation performance in various countries and regions as assessed through their patenting activity over the period from 1978 to 2019 with a particular focus on women inventors. According to the existing literature, patents are a key driver of innovation and provide a valuable measure of countries’/regions’ inventiveness [ 15 ] because innovations emerge from the complex collaborations and interactions that exist among a diverse set of inventors. Various studies have proven, using theoretical and empirical approaches, that there is a relationship between collaboration and innovation performance [ 17 ].…”

Section: Conclusion and Policy Implicationsmentioning

confidence: 99%

“…Additionally, patents must contain citations to other patents to acknowledge the state of the art. “These citations are understood to represent knowledge flows between inventors and have been widely used to study various economic and social aspects of innovation dynamics” [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

Economic geography of innovation: The effect of gender-related aspects of co-inventor networks on country and regional innovation

Tahmooresnejad¹,

Turkina²

2023

PLoS ONE

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This paper focuses on the analysis of the effects of inventor networks on country and regional innovation. We use data from an OECD inventor database that spans more than forty years to build collaboration networks in which the network nodes are countries and regions, and linkages are patents produced by inventors from different regions and countries. We first investigate the network that includes all inventors and then analyze the network focusing on women inventors. We argue that both country and regional-level network centrality positively affect country and regional innovation (with stronger effects at the country level), and centrality in collaborations that involve women has an additional positive impact. We also find that women inventors’ share in the pool of inventors is positively associated with innovation quality both at the county and regional levels. Furthermore, our findings indicate that in the network of women inventors, countries and regions that are in cohesive clusters (formed by repeated interactions between interconnected actors) show stronger innovation performance. Our study also highlights important nuances between country-level and region-level effects.

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“…Some influential studies on smaller or more aggregated networks have been done in this field [167,168], and attempts to model and measure large-scale knowledge spreading phenomena on these collaboration networks are sure to follow. For example, one recent work [169] finds that the community structures in co-invention networks affect the timing of citations to new patents granted to inventors within these communities. That work illustrates the need for the application of more advanced network analysis tools than simple social distance approaches [167,168] to understand information diffusion in the co-invention network.…”

Section: Applications Of Network Sciencementioning

confidence: 99%

“…Networks derived from patent metadata may also provide information about patent quality, and in particular, those derived the projections of bipartite networks [111,349] such as the co-invention network of inventors, the co-assignment network of firms, and the co-classification network of technology categories, in addition to the individual characteristics of these entities. The network location of these metadata in their respective networks may have a large part to play in informing both the nature of knowledge flow between people [74,169] and the effect of unique combinations of expertise or technologies [209]. An interesting piece of work in this vein is the recent study of Morgan et al [350], the results of which highlight the institutional inequalities inherent in the diffusion of scientific knowledge.…”

Section: Inclusion Of Additional Variablesmentioning

confidence: 99%

Knowledge Diffusion and the Dynamics of Citation Accrual

Higham¹

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<p>The diffusion of knowledge through society proceeds like an invisible ripple that moves between agents through multiple information channels. However, some types of knowledge are recorded, systematised and digitised for the benefit of everyone. Patents and academic articles are examples of such codified knowledge. These documents also contain a common element that is utilised for linking new and established knowledge: citations. This thesis harnesses citations in patents and scientific articles as proxies for signifying the existence of knowledge flows between cited and citing documents, focusing primarily on the dynamics of citation accumulation and the mechanisms governing these dynamics. For this purpose, it is helpful to think of patents and their citations as nodes and links, respectively, in a network where new nodes join the network and distribute their citations among existing nodes. This mode of thinking leads directly to the question: How does the citation network grow? This thesis addresses that question both empirically and theoretically. Two mechanisms that can explain much of the observed citation dynamics are preferential attachment and node ageing. The former mechanism reflects the tendency for successful nodes (by citation count) to become even more successful, while the latter captures the propensity for knowledge to become obsolete over time. The independence of these phenomena is nontrivial, but has generally been assumed. We put this assumption to the test for both patent and scientific-article citation networks and found it to be generally true if precautions are taken to account for important context surrounding the meaning of citations. Achieving a clear separation of these mechanisms is found to be very useful both mathematically and empirically, as they can now be studied independently. Patents are particularly sophisticated documents, with various components holding specific legal meanings. Associating certain properties of these components with popularity in the form of citation accrual creates a rare opportunity to build a framework that can identify ex-ante node fitnesses and examine their effect on the growth of a citation network. We find that a significant portion of the preferential-attachment process observed in the patent-citation network can be attributed to basic properties of patents determined by their time of grant. Besides suggesting novel approaches towards estimating patent quality, the results of our work also provide a platform for gaining a deeper understanding of the various mechanisms that underpin the success-breeds-success dynamics ubiquitously observed in complex systems.</p>

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Community structure in co-inventor networks affects time to first citation for patents

Cited by 5 publications

References 45 publications

A Movie Recommender System Based on User Profile and Artificial Bee Colony Optimization

A Movie Recommender System Based on User Profile and Artificial Bee Colony Optimization

Economic geography of innovation: The effect of gender-related aspects of co-inventor networks on country and regional innovation

Knowledge Diffusion and the Dynamics of Citation Accrual

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