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Identifying the sense of a word within a context is a challenging problem and has many applications in natural language processing. This assignment problem is called word sense disambiguation (WSD). Many papers in the literature focus on English language and data. Our dataset consists of 1400 sentences translated to Turkish from the Penn Treebank Corpus. This paper seeks to address and discuss 6 different...
The construction of knowledge graph of dangerous goods (KGDG) is with great significance of inferring relative information of dangerous goods, developing corresponding policy for its storage and transport, preventing disaster caused by dangerous goods(DG), and providing emergency plan when the disaster happens. Since distributed representation of natural language is an effective method for knowledge...
Recently, big data have special concerns from researchers, this due to the valuable information can be collected from it. LSA has an effective performance in classification, and information retrieval, since it deals with the semantics of the words. In this paper, we proposed a distributed text classification approach based on LSA, and Cosine Similarity, and can be applied to big data. The proposed...
Data staging has been shown to be very effective for supporting data intensive in-situ workflows and coupling of applications. Experimental sciences are increasingly becoming collaborative among geographically distributed teams, and include experimental instruments and HPC facilities. This new way of doing science poses new challenges due to data sizes, complexity of computation, and the use of wide...
Highly dynamic distributed applications often require flexible coordination among several autonomous components. Space-based middleware provides a suitable, data-driven coordination paradigm for such scenarios, where distributed peers exchange data and commands in a scalable and decoupled way using shared tuple spaces. In its basic form, such a middleware supports access to a data storage and (blocking)...
The Semantic Data are built from triples, that contain subjects, predicates and objects. On the other hand we can consider the triples as edges. The subject and the object are the nodes and the predicate is the label of the edge. In this view the Semantic Data define a graph. This graph can be very large, because a Semantic Dataset contains millions of triples. To query this dataset we can use the...
Recent work has demonstrated the emergence of semantic object-part detectors in activation patterns of convolutional neural networks (CNNs), but did not account for the distributed multi-layer neural activations in such networks. In this work, we propose a novel method to extract distributed patterns of activations from a CNN and show that such patterns correspond to high-level visual attributes....
With the advent of IoT (Internet of Things) age, considerable web services are emerging rapidly in service communities, which places a heavy burden on the target users' service selection decisions. In this situation, various techniques, e.g., collaborative filtering (i.e., CF) is introduced in service recommendation to alleviate the service selection burden. However, traditional CF-based service recommendation...
In this work we focus on integrity and consistency of data accessed and manipulated by multiple collaborating users, and stored in an (untrusted) hosted service. This is a problem, aspects of which have been studied in isolation in hitherto distinctcommunities. Consistency is one of the cardinal problems of distributed computing. Integrity of hosted data has been studied over the last decade, and...
With technologies developed in the Internet of Things, embedded devices can be built into every fabric of urban environments and connected to each other; and data continuously produced by these devices can be processed, integrated at different levels, and made available in standard formats through open services. The data, obviously f a form of ‘big data', is now seen as the most valuable asset in...
In the social computing environment, the complete information about an individual is usually distributed in heterogeneous social networks, which are presented as linked data. Synthetically recognizing and integrating these distributed and heterogeneous data for efficiently information searching is an important but challenging work. In this paper, a dynamic weight (DW)-based similarity calculation...
MapReduce greatly alleviates the burdens of programmers and gradually becomes an application programming standard on cloud computing nowadays, because the run-time system of cloud computing can automatically handle the issues of paralleled and distributed programming on behalf of programmers at run time. Although MapReduce can strongly benefit programmers on developing cloud computing applications,...
Recent development and exponential growth in the field of IT generates large volume of data every day in a variety of domains such as Social networks, Health care, Government sectors etc. These data are voluminous, varied and ever increasing at an unprecedented pace which makes storage and computing a mammoth task. Generally the time taken to execute a query and return the results, increases exponentially...
Malaria is a leading cause of death in Africa. Many organizations, NGO’s, and government agencies are collaborating to prevent, control, and eliminate malaria. In order to succeed in these shared goals, an integrated, consistent knowledge source to empower informed decision-making is required. Malaria surveillance is currently performed using dynamic, interconnected, systems which require rapid data...
Smart contracts might encode legal contracts written in natural language to represent the contracting parties’ shared understandings and intentions. The issues and research challenges involved in the validation and verification of smart contracts, particularly those running over blockchains and distributed ledgers, are explored.
Data replication is an important research area, as reliable access to data makes up the base of most of IT services. High operation availabilities, low operation costs and data consistency are major target conflicts in almost every data replication research. In this paper, we introduce a data semantics and data encoding-based data replication strategy called Semantic Data Replication (SDR). SDR focuses...
Our previous work suggested a method to connect online shopping services with social funding projects in order to provide a plenty of donating places for users to provide their shopping rewards and to improve the donation culture in our society. In this paper, we discuss the structure to implement the method using Apache Kafka, a well-known distributed publish/subscribe system, and present several...
The need for distributed database systems increases day by day due to the need of running organizations from different locations. The efficiency and performance of distributed query processing depends on fragmentation and allocation method used. Usually, the fragmentation solutions are based on empirical data and analyzing query patterns. These methods can only be applied for the existing distributed...
Thanks to their ability to return interesting objects in a database, the skyline queries have received considerable attention from the database community over the last few years. Skyline analysis is a powerful tool in a wide spectrum of real applications including multi-criteria optimal decision making, preference answering and many applications where uncertain, imprecise and noisy data inherently...
High-performance computing (HPC) systems face increasingly critical metadata management challenges, especially in the approaching exascale era. These challenges arise not only from exploding metadata volumes but also from increasingly diverse metadata, which contains data provenance and user-defined attributes in addition to traditional POSIX metadata. This "rich" metadata is critical to...
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