EU H2020 Project "SIAM (Scaling Up Innovation through Analogy Mining)": description, partecipants, costs and EC-fundings

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SIAM project word cloud

Explore the words cloud of the SIAM project. It provides you a very rough idea of what is the project "SIAM" about.

grail maintained algorithms automating language principled retrieve representations scientific deep brothers variety sound coupled demonstrates water imbuing transfer cardboard world play despite aircraft components box accelerate analogs analogies data discovering roles artificial discovered made patents science similarity crowdsourcing original inventors twisting holy breakthroughs ai analogy head explosion scientists abstraction tools philosopher discovery serve analogical automatically progress multiple changing pipeline papers guiding techniques enabled starting online led tackle points content suggest keywords opportunity ideas revolutionize commonsense learning natural longstanding indicate chrysippus settings little unstructured unprecedented greek wave observing phenomenon wright domain creates structural core speculate datasets status describes metrics machine steerable explores preliminary feasibility intelligence allowed innovation

Project "SIAM" data sheet

The following table provides information about the project.

Coordinator	THE HEBREW UNIVERSITY OF JERUSALEM Organization address address: EDMOND J SAFRA CAMPUS GIVAT RAM city: JERUSALEM postcode: 91904 website: www.huji.ac.il contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.
Coordinator Country	Israel [IL]
Total cost	1˙373˙057 €
EC max contribution	1˙373˙057 € (100%)
Programme	1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
Code Call	ERC-2019-STG
Funding Scheme	ERC-STG
Starting year	2020
Duration (year-month-day)	from 2020-01-01 to 2024-12-31

#	participants	country	role	EC contrib. [€]
1	THE HEBREW UNIVERSITY OF JERUSALEM	IL (JERUSALEM)	coordinator	1˙373˙057.00

THE HEBREW UNIVERSITY OF JERUSALEM

IL (JERUSALEM)

coordinator

1˙373˙057.00

Project objective

'Many world-changing breakthroughs in science and technology were enabled by analogical transfer, as ideas from one domain were used to solve a problem in another. Observing water led the Greek philosopher Chrysippus to speculate that sound was a wave phenomenon; an analogy to twisting a cardboard box allowed the Wright brothers to design a steerable aircraft. Despite its value for innovation, very little progress has been made towards automating the process of analogy-finding in real-world settings, and the problem has maintained a longstanding status as a 'holy grail' in artificial intelligence (AI).

The goal of this proposal is to tackle head-on this important problem and develop principled tools for automatically discovering analogies in large, unstructured, natural-language datasets such as patents and scientific papers. Such tools could revolutionize a variety of fields, allowing scientists and inventors to retrieve useful content based on deep structural similarity rather than simple keywords. The explosion of data available online, coupled with novel machine learning and crowdsourcing techniques, creates an unprecedented opportunity to develop novel methods to accelerate innovation and discovery.

My approach explores the multiple roles AI and machine learning can play in the analogical innovation pipeline. This research will focus on the three core components of the pipeline -- (1) developing representations and similarity metrics to facilitate comparison between potential analogs, (2) imbuing the algorithms with commonsense knowledge and abstraction capabilities, and (3) guiding the adaptation of the discovered analogies to solve the original problem. For each component, the proposal demonstrates how recent advances suggest effective approaches, and describes our concrete preliminary results and ideas to serve as starting points and indicate the feasibility of this challenging project.'

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