Satoshi Morinaga

• NEC Corporation

The paper describes a reference architecture for open marketplaces to be used for networked stakeholders in industrial production ecosystems. The motivation for such an endeavor comes from the idea to apply the basic principle of the platform economy to offer functions of an asset “as a service” to industrial production, including the associated su...

The Automated Negotiating Agents Competition (ANAC) is a yearly-organized international contest in which participants from all over the world develop intelligent negotiating agents for a variety of negotiation problems. To facilitate the research on agent-based negotiation, the organizers introduce new research challenges every year. ANAC 2019 pose...

In the very near future, we anticipate that more and more artificially intelligent agents will be deployed to represent individuals and institutions. Automated negotiation environments are a mechanism by which to coordinate the behavior of such agents. Most existing work on automated negotiation assumes a context that is predefined, and hence, stat...

To provide a latent variable model estimation apparatus capable of implementing the model selection at high speed even if the number of model candidates increases exponentially as the latent state number and the kind of the observation probability increase. A variational probability calculating unit 71 calculates a variational probability by maximi...

To provide an information spread scale prediction device capable of accurately predicting the number of future contributions for a specific topic in SNS and the like. The information spread scale prediction device includes: a learning text data input unit which acquires learning text data from a specific website; a node influence learning unit whic...

Multi-dimensional data visualization is an important research topic that has been receiving increasing attention. Several techniques that apply scatterplot matrices have been proposed to represent multi-dimensional data as a collection of two-dimensional data visualization spaces. Typically, when using the scatterplot-based approach it is easier to...

An asset network systemic risk (ANWSER) model is presented to investigate the impact of how shadow banks are intermingled in a financial system on the severity of financial contagion. Particularly, the focus of this study is the impact of the following three representative topologies of an interbank loan network between shadow banks and regulated b...

It had been believed in the conventional practice that the risk of a bank going bankrupt is lessened in a straightforward manner by transferring the risk of loan defaults. But the failure of American International Group in 2008 posed a more complex aspect of financial contagion. This study presents an extension of the asset network systemic risk mo...

To provide a discriminant model learning device capable of efficiently learning a discriminant model on which domain knowledge indicating user's knowledge or analysis intention for a model is reflected while keeping fitting to data. A query candidate storage means 81 stores candidates of a query as a model to be given with domain knowledge indicati...

Most time-varying data in our daily life is multi-variate. Moreover, most of such time-varying data contains both numeric and categorical values. It is often meaningful to visualize both of them as they are often correlated. We aim to visualize every value in such time-varying data in a single display space so that we can discover interesting relat...

An active metric learning device includes a metric application data analysis unit, a metric optimization unit, and an attribute clustering unit. The metric application data analysis unit is formed with a metric applying module for calculating the distance between data to be analyzed, a data analyzing module for analyzing the data using a predetermi...

Multidimensional data visualization is an important research topic that has been receiving increasing attention. Several techniques that use parallel coordinate plots have been proposed to represent all dimensions of data in a single display space. In addition, several other techniques that apply scatter plot matrices have been proposed to represen...

Kernel functions, the number of which is set in advance, are linearly coupled to generate the most suitable Kernel function for a data classification. An element Kernel generating unit 102 generates a plurality of element Kernel functions K1-Kp by using a plurality of distance functions (distance scales) d1-dp prepared in advance. A Kernel optimizi...

This study presents an ANWSER model (asset network systemic risk model) to quantify the risk of financial contagion which manifests itself in a financial crisis. The transmission of financial distress is governed by a heterogeneous bank credit network and an investment portfolio of banks. Bankruptcy reproductive ratio of a financial system is compu...

Recently, the acquisition of knowledge from big data analysis is becoming an essential feature of business efficiency. However, the analysis of big data can be troublesome because it often involves the collection and storage of mixed data based on different patterns or rules (heterogeneous mixture data). This has made the heterogeneous mixture prop...

The European sovereign debt crisis has impaired many European banks. The distress on the European banks may transmit worldwide, and result in a large-scale knock-on default of financial institutions. This study presents a computer simulation model to analyze the risk of insolvency of banks and defaults in a bank credit network. Simulation experimen...

This paper proposes an online mixture modeling methodology in which individual components can have different marginal distributions and dependency structures. Mixture models have been widely studied and applied to various application areas, including density estimation, fraud/failure detection, image segmentation, etc. Previous research has been al...

In this paper, we propose a framework to make the text clustering process, as a whole, efficient. In a real text clustering task, an analyst usually has some expectation on the results in mind. However, a single run of a clustering algorithm on the preprocessed data would not satisfy the expectation. Then the analyst faces labor-intensive trials fo...

Our main contribution is to propose a novel model selection methodology, expectation minimization of description length (EMDL), based on the minimum description length (MDL) principle. EMDL makes a significant impact on the combinatorial scalability issue pertaining to the model selection for mixture models having types of components. A goal of suc...

Due to the advancement of user participated web services, consumer generated media (CGM), such as grapevine communications on blogs and bulletin boards, are about to influence real society enormously. This paper introduces a number of text mining technologies intended for an integrated analysis of such CGM information (cyber space), television news...

It becomes increasingly important to automatically discover business knowledge from large databases in order to drastically reduce operators costs in the areas of CRM (Customer Relationship Management), knowledge management, Web marketing, etc. This paper introduces NEC's technology concept of Knowledge Organization and data mining engines designed...

We propose a new text mining system which extracts characteristic contents from given documents. We define Key semantics as characteristic sub-structures of syntactic dependencies in the given documents, and consider the following three tasks in this paper: 1)Key semantics extraction: extracting characteristic syntactic dependency structures not on...

In a wide range of business areas dealing with text data streams, including CRM, knowledge management, and Web monitoring services, it is an important issue to discover topic trends and analyze their dynamics in real-time. Specifically we consider the following three tasks in topic trend analysis: 1)Topic Structure Identification; identifying what...

We consider the situation where a number of agents are distributed and each of them collects a data sequence generated according to an unknown probability distribution. Here each of the distributions is specified by common parameters and individual parameters e.g., a normal distribution with an identical mean and a different variance. Here we intro...

Knowing the reputations of your own and/or competitors products is important for marketing and customer relationship management. It is, however, very costly to collect and analyze survey data manually. This paper presents a new framework for mining product reputations on the Internet. It automatically collects people's opinions about target product...

Knowing the reputations of your own and/or competitors' products is important for marketing and customer relationship management. It is, however, very costly to collect and analyze survey data manually. This paper presents a new framework for mining product reputations on the Internet. It automatically collects people's opinions about target produc...

We present an abstract model, the domain-partition model, of fault-tolerant systems (FTSs) in order to solve the reliability maximization problem under given redundancy. The domain-partition model is an abstraction of a reconfigurable device with several versions of circuit configuration. Unlike existing models that deal with specific FTSs, our mod...

The α‐parameter for autoassociative neural networks is introduced here. This parameter allows the memory capacity of such networks to be derived without use of techniques such as the replica method and signal‐to‐noise analysis. The results of the derivation explain those obtained from simulation experiments, with the derivation relying simply on as...

Our main contribution is to propose a novel model selection methodology, ex- pectation minimization of information criterion (EMIC). EMIC makes a significant impact on the combinatorial scalability issue pertaining to the model selection for mixture models having types of components. A goal of such problems is to optimize types of components as wel...

In this paper, we investigate underestimation of sector concentration risk caused by as- signing borrowers to wrong sectors. We consider a multi-factor default-mode Merton model with infinite granularity, and evaluate the influence of a portfolio manager's mis-assignment of borrowers on estimation of model parameters and risk computation. The evalu...