Amsterdam, Noord-Holland, Nederland
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Publicaties
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Information Reuse Networks: Detection & Credit Attribution
Workshop On Information In Networks (WIN)
User generated content has grown enormously in forums, blogs, and social media since the rise of theWeb. Inside and outside firms, this vast amount of information can be leveraged to promote information exchange, awareness, and productivity as with repurposed contract clauses or modular code. The purpose of our research is to develop a novel, efficient and scalable approach to detect and promote reuse by rewarding the providers of original content. More specifically, we find chains of reuse in…
User generated content has grown enormously in forums, blogs, and social media since the rise of theWeb. Inside and outside firms, this vast amount of information can be leveraged to promote information exchange, awareness, and productivity as with repurposed contract clauses or modular code. The purpose of our research is to develop a novel, efficient and scalable approach to detect and promote reuse by rewarding the providers of original content. More specifically, we find chains of reuse in any kind of text or software. Detecting reuse then serves as the basis for a Credit Attribution System. This application deals with the problem of finding the quantity of content reuse in a reference corpus, estimating the value of downstream repurposed content, and rewarding sources of foundational ideas. The tools are useful both to motivate information sharing (supply) and provide a visual trace of idea networks when information seeking (demand).
Andere auteursPublicatie weergeven
Patenten
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Method For Tracking And Tracing Idea Reuse
Ingediend op US 61/706558
We have developed algorithms to detect the reuse of information and provide credit back to the original source of that information.
One part of the algorithm recursively detects chains of reused content regardless of how far back the chain proceeds. This is analogous to a plagiarism detection algorithm with the modification that it detects not merely the presence of overlapping content but also the progression and ordering of content that has been reused multiple times, accounting for…We have developed algorithms to detect the reuse of information and provide credit back to the original source of that information.
One part of the algorithm recursively detects chains of reused content regardless of how far back the chain proceeds. This is analogous to a plagiarism detection algorithm with the modification that it detects not merely the presence of overlapping content but also the progression and ordering of content that has been reused multiple times, accounting for changes in authorship at each iteration. Human intervention or prior attribution, as in the case of care exercised to quote or cite reused content, can be helpful but is not required. The algorithm can account for perturbations in which the essence of an idea is described using different language.
A second part of the algorithm seeks to establish the relative value of reused and novel content then apportion the value from reused content back to original sources of novel content. Distinguishing value from quantity is essential because it is often possible to develop a succinct expression of an important idea and a long-winded expression of an unimportant idea. The algorithm can account for superadditivity (or subadditivity), which occurs when the value of the combined ideas is greater (or less) than the sum of the parts. The algorithm is also provably "fair" in a rigorous economic sense of granting to each party his or her marginal contribution to the whole.
A third part of the invention is a set of efficiency improvements pertaining to the prior two algorithms. The pure theoretically optimal algorithms are difficult to compute for reasons of mathematical complexity thus we have devised a series of shortcuts to shorten the computation time. In one instantiation, the invention can be applied to any form of text based content such as word processed documents or software. In another instantiation, it can be applied to digital imagery and sound as in the case of art, and music.Andere bedenkers
Projecten
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Bits of Stock
- heden
Bits of Stock rewards shoppers with stock as they shop with their favorite brands. Like cashback but with stock.
Xeco Labs helped setting up the infrastructure and backend services for Bits of Stock and lead the technology until and through the launching of the Bits app in the AppStore.Andere bijdragersProject weergeven -
Index People Portal
- heden
Index People is an asset management company in Haarlem, The Netherlands. In this project we built their next generation investment portfolio management and reporting tool. As part of this project a lot of their back-office operations and processes are optimized. Their investors also got a brand new reporting portal to get more insights out of their investment portfolio and performance.
This project is built using Django framework and PostgreSQL DB and all financial calculations are done…Index People is an asset management company in Haarlem, The Netherlands. In this project we built their next generation investment portfolio management and reporting tool. As part of this project a lot of their back-office operations and processes are optimized. Their investors also got a brand new reporting portal to get more insights out of their investment portfolio and performance.
This project is built using Django framework and PostgreSQL DB and all financial calculations are done using Pandas and Numpy. Moreover, a bidirectional sync mechanism is built between their Salseforce and the Django backend.Andere bijdragersProject weergeven -
Coinograph
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Coinograph is the Swiss army knife we're building for cryptocurrency traders offering them tools and signals for trade opportunities. For now our focus is on traders active on Telegram platform.
Andere bijdragersProject weergeven
Onderscheidingen
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Huygens Scholarship
Netherlands Organization for International Cooperation in Higher Education
Was awarded the HSP Scholarship to study Grid Computing master’s program at University of Amsterdam
Talen
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Persian
Moedertaal of tweetalig
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English
Volledige professionele vaardigheid
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Moedertaal of tweetalig
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Turkish
Beperkte werkvaardigheid
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Arabic
Basisvaardigheid
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Dutch
Beperkte werkvaardigheid
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