NEC

About: NEC is a company organization based out in Tokyo, Japan. It is known for research contribution in the topics: Signal & Layer (electronics). The organization has 33269 authors who have published 57670 publications receiving 835952 citations. The organization is also known as: NEC Corporation & NEC Electronics Corporation.

Context in Web Search.

Abstract: Web search engines generally treat search requests in isolation. The results for a given query are identical, independent of the user, or the context in which the user made the request. Nextgeneration search engines will make increasing use of context information, either by using explicit or implicit context information from users, or by implementing additional functionality within restricted contexts. Greater use of context in web search may help increase competition and diver-

A unifying framework for detecting outliers and change points from non-stationary time series data

Abstract: We are concerned with the issues of outlier detection and change point detection from a data stream. In the area of data mining, there have been increased interest in these issues since the former is related to fraud detection, rare event discovery, etc., while the latter is related to event/trend by change detection, activity monitoring, etc. Specifically, it is important to consider the situation where the data source is non-stationary, since the nature of data source may change over time in real applications. Although in most previous work outlier detection and change point detection have not been related explicitly, this paper presents a unifying framework for dealing with both of them on the basis of the theory of on-line learning of non-stationary time series. In this framework a probabilistic model of the data source is incrementally learned using an on-line discounting learning algorithm, which can track the changing data source adaptively by forgetting the effect of past data gradually. Then the score for any given data is calculated to measure its deviation from the learned model, with a higher score indicating a high possibility of being an outlier. Further change points in a data stream are detected by applying this scoring method into a time series of moving averaged losses for prediction using the learned model. Specifically we develop an efficient algorithms for on-line discounting learning of auto-regression models from time series data, and demonstrate the validity of our framework through simulation and experimental applications to stock market data analysis.

A read-static-noise-margin-free SRAM cell for low-V/sub dd/ and high-speed applications

Abstract: To help overcome limits to the speed of conventional SRAMs, we have developed a read-static-noise-margin-free SRAM cell. It consists of seven transistors, several of which are low-Vth nMOS transistors used to achieve both low-VDD and high-speed operations. For the same speed, the area of our proposed SRAM is 23% smaller than that of a conventional SRAM. Further, we have fabricated a 64-kb SRAM macro using 90-nm CMOS technology and have obtained with it a minimum VDD of 440 mV and a 20-ns access time with a 0.5-V supply.

Unintrusive customization techniques for Web advertising

Abstract: Most online advertisement systems in place today use the concept of consumer targeting: each user is identified and, according to his or her system setup, browsing habits and available off-line information, categorized in order to customize the advertisements for highest user responsiveness. This constant monitoring of a user's online habits, together with the trend to centralize this data and link it with other databases, continuously nurtures fears about the growing lack of privacy in a networked society. In this paper, we propose a novel technique of adapting online advertisement to a user's short term interests in a non-intrusive way. As a proof-of-concept we implemented a dynamic advertisement selection system able to deliver customized advertisements to users of an online search service or Web directory. No user-specific data elements are collected or stored at any time. Initial experiments indicate that the system is able to improve the average click-through rate substantially compared to random selection methods.