Scientists map of mathematics how we make and innovate

A new study in Nature communication Scrutiny High-order cheap goods dynamics, attractive patterns identify how we add to the existing elements to make innovation, potentially shape our understanding of human creativity and innovation.

The novel – a common part of human life – refers to one of the two things. The first is the discovery of a single item, such as a place, song or an artist. The second cover makes new discoveries for everyone, such as technological development or drug discovery.

In this study, researchers aims to understand how both types of novels emerge. The team was headed by Prof. from Queen Mary University in London. Veto Latora did, who spoke to Phys.org about the work.

“I have always been attracted to creativity and innovation, which are driving forces of human progress. This paper is a sequence of theoretical and applicable functions of my research group, which to study and model mechanisms to understand creativity. For the goal of understanding, what makes a new idea, team, product or technology successful, “Pro. Letora said.

The team analyzed the real-world figures from three sources to study high-order cheaper goods.

Show for the first time

One of the main challenges with studying cheap goods is that most previous researches have focused on the first-order cheaper goods, that is, the first time the appearance of individual elements.

For example, something new food or first go to a new place. However, this approach ignores an important innovation system – adds existing elements to create something new.

For example, words can be placed together in different ways to create new poems or stories, or music notes can be added to create a new song. The latter is known as high-order cheaper goods.

Pro. Letora said, “In our study, we introduced and discovered a more common perception of innovation, which we named high-order novelty, which first appear together in two or more elements in a sequence. “

To simulate how these combinations are, the research team developed a framework called Edge-Dalited Random Walk with trigger or erwa.

Random Walk and Ervet

The ERRWT model is based on the random walk, a mathematical model that describes the development of a system based on the discretionary stages. In this method, the next position of the walker depends only on its current position.

The movement between the posts is completely random, there are similar possibilities with each movement in each direction.

Pro. Letora explained this process: “Imagine all the things we can find out, or all the ideas that we can describe as nodes of a network, whose links whose links whose links between two objects or concepts or concepts Represent equality. “

The innovation of the model lies in how it simulates the development of these networks. As the walker moves through the network, it does not just cross the existing routes-it creates new connections, triggers the emergence of new nodes, indicating that the real world search processes expand the possibilities of our horizon How do you do

Construction of new connections – when novel combinations are known – is known as the edge triggering, and strengthening the connections between frequently used combinations.

The team used this ERRWT model to analyze three datasets. He chose to analyze music listening patterns (last.fm), literary texts and books (Project Gutenbergs), and scientific articles (Symentic Scholars).

Pro. Letora explained how the model works, saying, “The more we listen to a song or we add two songs, the higher the possibility that we will repeat the song or association in the future. Also, it means that it means. It is also that the discovery of new songs or associations generate an extended place of opportunities that are available only to us, the moment we exist. “

Piles

The team found that the combinations followed the forecasted patterns, which is ruled by the law of Heaps, a power-law development relationship. It is a mathematical relationship that suggests how new combinations come out over time, providing a quantitative way to measure and predict innovative processes.

According to their simulation, various processes may have the same rate of discovering individual elements, but very different rates of discovery of combinations.

More especially, he found that for last.fm dataset, users with the same rate of searching for new songs can be very different ways to index these songs.

For literature dataset, he found that the writers generate new words union more often than introducing new words. Finally, scientific articles showed more creative term combinations than narrative texts, especially in the title of paper.

ERRWT showed how network structure and exploration patterns are co-developed, showing that reinforcement (strengthening existing paths) and triggering (making new connections) are essential to explain the real-world patterns.

Implication and future work

The new structure provides a new basis for understanding innovation and creativity, reducing the gap between personal discovery and combinatorial innovation.

Conclusions help us understand the relevance of this model, especially in view of how new scientists find out of the combination of existing knowledge. It can also inform the educational approach to creativity.

Pro. Letora commented, “To study creative processes and understand how new ideas emerge and how Novelty can trigger further discoveries, it is fundamental, if we can nurture the success and permanent development of our society Want to prepare effective intervention. We believe that our conclusions and proposed models can be used to answer questions about the rise and decline of ideas. “

The purpose of the research team is to make the model more normal and it also includes a social component, which is currently missing.

© 2025 Science X Network