Search results for "Information filter"
showing 6 items of 6 documents
Backbone of credit relationships in the Japanese credit market
2016
We detect the backbone of the weighted bipartite network of the Japanese credit market relationships. The backbone is detected by adapting a general method used in the investigation of weighted networks. With this approach we detect a backbone that is statistically validated against a null hypothesis of uniform diversification of loans for banks and firms. Our investigation is done year by year and it covers more than thirty years during the period from 1980 to 2011. We relate some of our findings with economic events that have characterized the Japanese credit market during the last years. The study of the time evolution of the backbone allows us to detect changes occurred in network size,…
Bootstrap validation of links of a minimum spanning tree
2018
We describe two different bootstrap methods applied to the detection of a minimum spanning tree obtained from a set of multivariate variables. We show that two different bootstrap procedures provide partly distinct information that can be highly informative about the investigated complex system. Our case study, based on the investigation of daily returns of a portfolio of stocks traded in the US equity markets, shows the degree of robustness and completeness of the information extracted with popular information filtering methods such as the minimum spanning tree and the planar maximally filtered graph. The first method performs a "row bootstrap" whereas the second method performs a "pair bo…
Semantic infrastructure system with feedback: Application on traffic
2012
The Semantic Web is a powerful approach used by some intelligent applications to manage complex information in many different fields. Nevertheless, there are not standard tools to design and built the applications, therefore each problem need to be analysed separately in order to meet the requirements. In this paper is presented an overview of a system based on a semantic approach with the goal of managing real-time information. The paper studies the application of this system on ITS (Intelligent Transport Systems) as an example of a typical real-time information system. The system gathers real information from the users and the environment, making intelligent decisions and delivering real-…
Reputation or peer review? The role of outliers
2018
We present an agent-based model of paper publication and consumption that allows to study the effect of two different evaluation mechanisms, peer review and reputation, on the quality of the manuscripts accessed by a scientific community. The model was empirically calibrated on two data sets, mono- and multi-disciplinary. Our results point out that disciplinary settings differ in the rapidity with which they deal with extreme events—papers that have an extremely high quality, that we call outliers. In the mono-disciplinary case, reputation is better than traditional peer review to optimize the quality of papers read by researchers. In the multi-disciplinary case, if the quality landscape is…
A Semantic Similarity Measure for the SIMS Framework
2008
The amount of currently available digital information grows rapidly. Relevant information is often spread over different information sources. An efficient and flexible framework to allow users to satisfy ef- fectively their information needs is required. The work presented in this paper describes SIMS (Semantic Information Management System), a ref- erence architecture for a framework performing semantic annotation, search and retrieval of information from multiple sources. The work pre- sented in this paper focuses on a specific SIMS module, the SIMS Semantic Content Navigator, proposing an algorithm and the related implementa- tion to calculate a semantic similarity measure inside an OWL …
AN ONTOLOGY-BASED APPROACH TO PROVIDE PERSONNALIZED RECOMMENDATIONS USING A STOCHASTIC ALGORITHM
2011
International audience; The use of personalized recommender systems to assist users in the selection of products is becoming more and more popular and wide-spread. The purpose of a recommender system is to provide the most suitable items from an knowledge base, according the user knowledge, tastes, interests, ... These items are generally proposed as ordered lists. In this article, we propose to combine works from adaptive hypermedia systems, semantic web and combinatory to create a new kind of recommender systems suggesting combinations of items corresponding to the user.