Takahiko Shintani

• University of Electro-Communications

We propose a method to extract a set of viewpoint locations and a set of locations of interest from a given set of location-direction-enabled photographs having embedded information regarding the location and direction of the shot. A viewpoint location is a location from which many photographs are taken. A location of interest is a location that th...

We propose a method for constructing a geometric graph for generating routes that summarize a geographical area and also have visual continuity by using a set of location-direction-enabled photographs. A location- direction-enabled photograph is a photograph that has information about the location (position of the camera at the time of shooting) an...

This paper focuses on the problem of m-Closest Keywords (mCK) queries over spatial web objects. An \(mCK\ query\) is to find the optimal set of objects (object-set) in the sense that they are the spatially-closest records and satisfy m user-given keywords. We propose a new approach called Pairwise Expansion to find an exact solution of mCK queries...

PC cluster is recently regarded as one of the most promising platforms for heavy data intensive applications, such as decision support query processing and data mining. We proposed some new parallel algorithms to mine association rule and generalized association rule with taxonomy and showed that PC cluster can handle large scale mining with them....

Until recently, workstations were overwhelmingly superior to personal computers in terms of performance. However, recent PC technology has dramatically increased its CPU, main memory, and cache memory performance. Therefore massively parallel computer systems are moving away from proprietary components such as CPU, disks, etc. to commodity parts. A...

Often, real world applications contain many missing values. In mining association rules from real datasets, treating missing values is an important problem. In this paper, we propose a pattern-growth based algorithm for mining association rules from data with missing values. No data imputations are performed. Each association rule is evaluated usin...

Rapid growth of internet access from mobile users puts much importance on location specific information on the web. An unique web service called Mobile Info Search (MIS) from NTT Laboratories gathers the information and provide location aware search facilities. We performed association rule mining and sequence pattern mining against the access log...

The rapid growth of Internet access from mobile users has emphasised the importance of location specific information on the Web. A unique Web service called Mobile Info Search (MIS) from NTT Laboratories gathers information and provides location aware search facilities. We performed association rule mining and sequence pattern mining against an acc...

Web mining can be classified into two categories, Web access log mining and Web structure mining. We performed association rule mining and sequence pattern mining against the access log which was accumulated at NTT Software Mobile Info Search portal site. The detailed Web log mining process and the rules we derived are reported. The parallel associ...

We performed association rule mining and sequence pattern mining against the access log which was accumulated at NTT Software Mobile Info Search portal site. Detail web log mining process and the rules we derived are reported in this paper. The integration of web data and relational database enables better management of web data. Some researches ha...

One of the most important problems in data mining is discovery of association rules in large database. In our previous study, we proposed parallel algorithms and candidate duplication based load balancing strategies for mining generalized association rules and showed our algorithms could attain good performance on 16 nodes parallel computer system....

. Data mining is becoming increasingly important since the size of databases grows even larger and the need to explore hidden rules from the databases becomes widely recognized. Currently database systems are dominated by relational database and the ability to perform data mining using standard SQL queries will definitely ease implementation of dat...

One of the most important problems in data mining is discovery of association rules in large database. We had proposed parallel algorithms for mining generalized association rules with classification hierarchy. In this paper, we implemented the proposed algorithms on a large scale PC cluster which consists of one hundred PCs interconnected by an AT...

A recent tendency in parallel computer design has been to use general-purpose components for system configuration elements such as CPUs, disks, and memories, which used to be specially developed. Although the connection network between the processors has been specially developed, it is now possible to configure a large-scale PC cluster with good pe...

In this paper, we propose four parallel algorithms (NPA, SPA, HPA and HPA-ELD) for mining association rules on shared-nothing parallel machines to improve its performance. In NPA, candidate itemsets are just copied amongst all the processors, which can lead to memory overflow for large transaction databases. The remaining three algorithms partition...

In this paper, we study the problem of mining sequential patterns in a large database of customer transactions. Since finding sequential patterns has to handle a large amount of customer transaction data and requires multiple passes over the database, it is expected that parallel algorithms help to improve the performance significantly. We consider...

Association rule mining recently attracted strong attention. Usually, the classification hierarchy over the data items is available. Users are interested in generalized association rules that span different levels of the hierarchy, since sometimes more interesting rules can be derived by taking the hierarchy into account. In this paper, we propose...

Data mining has been widely recognized as a powerful tool to explore added value from large-scale databases. One of data mining techniques, generalized association rule mining with taxonomy, is potential to discover more useful knowledge than ordinary flat association mining by taking application specific information into account. We proposed SQL q...

Association rule mining recently attracted strong attention. Usually, the classification hierarchy over the data items is available. Users are interested in generalized association rules that span different levels of the hierarchy, since sometimes more interesting rules can be derived by taking the hierarchy into account. In this paper, we propose...

superior to personal computers in terms of performance. However, recent PC technology has dramatically increased its CPU, main memory, and cache memory performance. Therefore massively parallel computer systems are moving away from proprietary components such as CPU, disks, etc. to commodity parts.

PC clusters have been studied intensively for next-generation large scale parallel computers. ATM technology is a strong candidate as a de facto standard of high speed communication networks. Therefore an ATM connected PC cluster is a very promising platform from the cost/performance point of view, as a future high performance computing environment...

We propose four parallel algorithms (NPA, SPA, HPA and HPA-ELD) for mining association rules on shared nothing parallel machines to improve its performance. In NPA, candidate itemsets are just copied amongst all the processors, which can lead to memory overflow for large transaction databases. The remaining three algorithms partition the candidate...

superior to personal computers in terms of performance.However, recent PC technology has dramaticallyincreased its CPU, main memory, and cachememory performance. Therefore massively parallelcomputer systems are moving away from proprietarycomponents such as CPU, disks, etc. to commodityparts.