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Time series classification is the most active research topics in time series data mining, because they cover a broad range of applications in many different domains. There are three important things that we need to consider in time series classification; representation, similarity measurement, and assignment strategy. Representation for time series is a technique that converts time series to feature...
The detection of similar structures in proteins has received considerable attention in the post-genome era. Protein structure alignment, which is similar to sequence alignment, can detect the structural homology between two proteins according to their three-dimensional structures. One of the simplest yet most robust techniques for finding optimal protein structure alignment is to maximize the contact...
. The parallelization of a Modified PrefixSpan method is proposed in this paper. The Modified PrefixSpan method is used to extract the frequent pattern from a sequence database. This system developed by authors requires the use of multiple computers connected in local area network. This system, which has a dynamic load balancing mechanism, is achieved through communication among multiple computers...
Time series classification is one of the most well-known grand challenges in many different application domains. Time series classification is the task of assigning a discrete class label to an unclassified time series. Three important key points should be considered in the design of time series classifiers: the feature expression for the time series, the definition of the distance function, and the...
In the era of big data, we are witnessing the rapid growth of a new type of information source. In particular, tweets are one of the most widely used microblogging services for situation awareness during emergencies. In our previous work, we focused on geotagged tweets posted on Twitter that included location information as well as a time and text message. We previously developed a real-time analysis...
Burst detection is one of the most popular techniques for extracting remarkable keywords in online social documents posted through social media. With the growing interest in geosocial media these days, many researchers are focusing on extracting geolocal keywords related to local topics and events from such social documents because of the increasing number of geo-annotated documents (e.g., geo-tagged...
Identifying similar structures in proteins has emerged as one of the most attractive research topics in the post-genome era. Protein structure alignment, which is similar to sequence alignment, identifies the structural homology between two protein structures according to their three-dimensional conformation. One of the simplest yet most robust techniques for optimizing protein structure alignment...
Geo-tagged documents on social media are usually related to local topics and events. Extracting areas of interest associated with local “attractive” topics from geo-tagged documents is one of the most important challenges in many application domains. In this paper, we propose a novel method for extracting the areas of interest from geo-tagged documents. There are two main steps in the proposed method...
Burstiness has been one of the most important criteria for extracting topics and events from documents posted on social media. Recently, researchers are focusing on extracting geolocal topics and events from such social documents because of the increasing number of geo-annotated documents (e.g., Geo-tagged tweets on Twitter). In our previous work, we developed a method for identifying local temporal...
Social photos are getting attention from researchers to extract real world topics, because users on social media have been posting social photos related to not only personal topics, but also social topics. We are developing curation techniques for social photos. This study proposes a new summarization method for results of keyword search on social photos. Social photos are photos that are posted on...
Recently, people have begun to diligently post their situation, particularly during a crisis, on social media, therefore, the enhancement of situation awareness using social data is one of the most attractive research subjects. In this paper, we propose a novel density-based spatiotemporal system with a photo image classifier. The photo image classifier, which allows the system to enhance situation...
Since social media started getting more attention from users on the Internet, social media has been one of the most important information source in the world. Especially, with the increasing popularity of social media, data posted on social media sites are rapidly becoming collective intelligence, which is a term used to refer to new media that is displacing traditional media. In this paper, we focus...
Proteins with similar three-dimensional structures usually have similar biological functions and interactions in living organisms. Thus, detecting similar structures in proteins is presently one of the most attractive research topics in computational biology. Many techniques for the comparison of protein structures are based on protein structure alignment. This is similar to sequence alignment, and...
In recent years, a huge number of researchers have been paying attention for developing new data mining techniques to detect topics and events in posted data on social media sites. In this paper, we focus on geotagged tweets posted on the Twitter site, which are referred to as georeferenced documents including not only short text message but also posted time and location. Burstiness is one of the...
With the increasing popularity of social media, data posted on social media sites are rapidly becoming collective intelligence, which is a term used to refer to new media that is displacing traditional media. In this paper, we focus on geotagged tweets on the Twitter site; such tweets are referred to as georeferenced documents because they include not only a short text message, but also the documents'...
Outliers are data objects that are not highly likely to occur. These are unusualness data objects such as errors, fraud data, and rare data. In the last few decades, outlier detection has attracted much attention from researchers, because it is widely used for many different application domains. Distance-based outlier detection, which is a non-parametric approach, identifies unusual data objects in...
Burstiness is the simplest but the most robust criterion for detecting topics and events in online documents. Online documents are referred to as document streams because they have a temporal order. Kleinberg's temporal burst detection algorithm is the most successful algorithm for detecting bursty periods related to a topic- or event-related keyword. Kleinberg's temporal burst detection algorithm...
An emerging topic in social media is the increase in the number of geo-annotated documents, which include not only posted time but also posted location. Social media users have been transmitting information about things they witnessed themselves in their daily life through such geo-annotated (georeferenced) documents. Georeferenced documents are usually related to not only personal topics but also...
The seismic design of highway bridges has been improved through the lessons learned from earthquake damage and advances in earthquake engineering. The Design Specifications for Highway Bridges, including a volume on seismic design, have been revised three times since the 1995 Kobe earthquake. This report presents the major changes and improvements in the seismic design techniques for highway bridge...
Nowadays, with the increasing attention being paid to social media, a huge number of georeferenced documents, which include location information, are posted on social media sites. People transmit and collect information over the Internet through these georeferenced documents. Georeferenced documents are usually related to not only personal topics but also local topics and events. Therefore, extracting...
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