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Entity tasks, such as linking, integration, and translation, are crucial for many search and NLP applications. For this purposed entity graphs have been manually built or automatically harvested. In this paper, we survey existing approaches abstracting these problems into a graph-based iterative matching on a pair of entity graphs.
IoT systems collect vast amounts of data which can be used in order to track and analyze the structure of future recorded data. However, due to limited computational power, bandwith, and storage capabilities, this data cannot be stored as is, but rather must be reduced in such a way so that the abilities to analyze future data, based on past data, will not be compromised. We propose a parameterized...
Inferring activities on smartphones is a challenging task. Prior works have elaborated on using sensory data from built-in hardware sensors in smartphones or taking advantage of location information to understand human activities. In this paper, we explore two types of data on smartphones to conduct activity inference: 1) Spatial-Temporal: reflecting daily routines from the combination of spatial...
This paper presents a two layer recurrent neural network employed in glass speed control transmitted by linear servo motor in Automated Optical Inspection (AOI) system platform. The recurrent neural network consists of an identifier and a controller, the identifier is used to catch a feedback signal from the position sensor and the controller is processed in microprocessor in order to supply an adaptive...
In recent years, researches of aspect-category-based sentiment analysis have been approached in terms of predefined categories. In this paper, we target two sub-tasks of SemEval-2014 Task 4 dedicated to aspect-based sentiment analysis: detecting aspect category and aspect category polarity. Also, a pre-identified set of aspect categories {food, price, service, ambience, miscellaneous} defined by SemEval-2014...
In 2006, we launched the Language Grid project to realize a distributed language service infrastructure on the Internet. Using the Language Grid, we worked with a nongovernmental organization since 2011 to support knowledge communications between agricultural experts in Japan and farmers in Vietnam via their children. We observed that a large community emerged to efficiently utilize nonmature machine...
In this paper, we propose an efficient approach to identify the opinion leader from group discussion. This approach is able to recognize the opinion leader without analyzing semantic and syntactic features, which may cost a lot more computing effort. We firstly propose algorithms to evaluate the degree of participation and the emotion expression from the speaking of each member during group discussion...
To solve large-scale constraint satisfaction problems, CSPs, ant colony optimization, ACO, based meta-heuristics has been effective. However, the naive ACO based method is sometimes inefficient because the method has only single pheromone trails. In this paper, we propose an ant colony optimization based meta-heuristics with multi pheromone trails in which artificial ants construct a candidate assignment...
The spatial clustering of highway traffic is of great interest to researchers and policy makers. In this paper, instead of using the microscopic traffic parameters in the traditional clustering methods, we introduce a new heterogeneity index clustering the sections of a highway based on differences in the content, a.k.a. “Heterogeneity”, in their flow, which can be used as a universal guideline for...
With the development of GPS and the popularity of smart phones and wearable devices, users can easily log their daily trajectories. Prior works have elaborated on mining trajectory patterns from raw trajectories. Trajectory patterns consist of hot regions and the sequential relationships among them, where hot regions refer the spatial regions with a higher density of data points. Note that some hot...
In the area of national language processing, performing machine learning technique on customer or movie review for sentiment analysis has been? frequently tried. While methods such as? support vector machine (SVM) were much favored in the 2000s, recently there is a steadily rising percentage of implementation with vector representation and artificial neural network. In this article we present an approach...
The puzzle game 2048, a single-player stochastic game played on a 4 × 4 grid, is the most popular among similar slide-and-merge games. One of the strongest computer players for 2048 uses temporal difference learning (TD learning) on so called N-tuple networks, where the shapes of the N-tuples are given by human based on characteristics of the game. In our previous work (Oka and Matsuzaki, 2016), the...
In this work, we address the problem of transfer learning for sequential recommendation model. Most of the state-of-the-art recommendation systems consider user preference and give customized results to different users. However, for those users without enough data, personalized recommendation systems cannot infer their preferences well or rank items precisely. Recently, transfer learning techniques...
This paper introduces a family of RoShamBo games, denoted by RSB(n,b,s,r) which means that n players simultaneously show a move among b possible moves with possible s winning regulations, at each round out of r round matches in total. The player who wins more after r rounds wins. A game informatical analysis of RSB(n,b,s,r) using game refinement measure is carried out, while experiments have been...
We in this paper introduce a novel data visualization package, called the ADD framework, to support responsive and adaptive data-driven visualization. Currently, interactive data visualization, which is generally achieved by Javascript-based libraries such as D3.js, cannot be easily manipulated as the responsive way like the RWD principle in the CSS design. Visualization of abundant information becomes...
In recent years, due to the rapid development of e-commerce, personalized recommendation systems have prevailed in product marketing. However, recommendation systems rely heavily on big data, creating a difficult situation for businesses at initial stages of development. We design several methods — including a traditional classifier, heuristic scoring, and machine learning — to build a recommendation...
The development of science is clear. From 1950 to 1990 we lived in a world of Contention, with as main question: Will Contention between Paradigms lead to a Paradigm Shift? This development is nicely described by Popper (Logic of Scientific Discovery), Kuhn (The Structure of Scientific Revolutions), Lakatos (The Methodology of Scientific Research Programmes), and Feyerabend (Against Method). In the...
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