Document similarity identification is one of the most significant problems of knowledge discovery and information retrieval. One way to perform these similarity measures is to analyze a citation graph of research pape...
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Document similarity identification is one of the most significant problems of knowledge discovery and information retrieval. One way to perform these similarity measures is to analyze a citation graph of research papers. If we have document citation information in the form of RDF graph, how we may identify the document similarity measures by using social network analysis techniques? We have answered this question by applying semantic social network analysis techniques on RDF citation graphs of research papers to identify the pair wise similarity between these papers. For performing social network analysis we have used classes of centrality degree and closeness centrality from SemSNA ontology. Concept of minimum cut/maximum flow from graph theory is used for quantification of similarity measure. In our experiment we have used Citeseer data set; it is found that our results are promising as compared to manual similarity measures by human for a subset of this data set. Our results are also encouragingly comparable to other citation link analysis techniques as well as content based similarity measures; this is the reason that we have focused on RDF citation based similarity measure. In future we are looking forward to use some citation ontology (such as CITO) to improve RDF graph construction for our proposed similarity measure technique.
Twitter is a breed of social networks that are playing a buoyant role in today's world communication. This paper is an attempt to apply knowledge discovery process on Twitter dataset comprising hashtags along with...
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Twitter is a breed of social networks that are playing a buoyant role in today's world communication. This paper is an attempt to apply knowledge discovery process on Twitter dataset comprising hashtags along with the visual analytic techniques whose purpose is to provide information to the people in such a way so that they understand concealed knowledge in the data effortlessly and meritoriously. We further analyze tweet text and metadata associated with each tweet for identification of useful patterns like "who talks to whom" and "how much". Our research reveals the impact of visualization and hierarchical clustering technique in analyzing similar groups of users. Further we investigate different social network measures that unveil the influence of users in the particular hashtags.
Finding satisfiability and implication results among queries is fundamental to several problems in databases especially in distributed databases. The known complexity of finding satisfiability of term S is O({pipe}S{p...
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Earthquakes are considered one of the major disastrous situations for any nation. The horrible earthquake may claim hundreds of lives, thousands of injuries and demolishing thousands of houses. When an earthquake hits...
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Bandwidth aggregation of heterogeneous wireless links faces numerous challenges in maximizing available connectivity services for mobile applications. One serious issue is the out-of-sequence arrival of packets at rec...
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Bandwidth aggregation of heterogeneous wireless links faces numerous challenges in maximizing available connectivity services for mobile applications. One serious issue is the out-of-sequence arrival of packets at receiver that is amplified by distribution of packets of a flow over multiple paths. These packets experience asymmetric path characteristics that results in diverse congestion states for traffic flow. This paper presents an adaptive mechanism for estimation of path suitability for a specific type of flow on the basis of end-to-end path statistics of delay, packet drop and available bandwidth. The proposed mechanism is also supported by a stochastic model that estimates delay with lesser computational complexity. The results of proposed approach have been validated through simulation as well. The results have shown robust performance of proposed mechanism in achieving acceptable quality-of-service levels during mobility with minimized out-of-sequence reception and reduced buffer occupancy.
Earthquakes are considered one of the major disastrous situations for any nation. The horrible earthquake may claim hundreds of lives, thousands of injuries and demolishing thousands of houses. When an earthquake hits...
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Earthquakes are considered one of the major disastrous situations for any nation. The horrible earthquake may claim hundreds of lives, thousands of injuries and demolishing thousands of houses. When an earthquake hits a nation then number of management bodies (such as: government organizations, non-government organizations (NGOs)) are actively involved in reinstating the damages. Generally, these organizations deal with stats of build and still-to-be build infrastructure (roads, buildings, and houses etc). Currently, this information is presented to the organizations as a raw text in huge amount. Therefore, it becomes difficult to highlight key areas where an immediate start of rehabilitation process is inevitable. In the past, some systems have been developed to present such information in structured form by using some visualization techniques. However, these tools are inadequate because of the following reasons: 1) Most of these tools are about geotechnical conditions of effected area and can provide help to describe seismic hazards 2) Some systems show trends of earthquakes in specific region. 3). None of the systems describe the rehabilitation process in an easily conceivable way. Therefore, this becomes an interesting and challenging research problem to build such a system that can overcome the above mentioned limitations of current techniques and systems. In this research, we present such a system called ERRAGMAP. This geospatial tool discovers and presents deep insight into the data related to rehabilitation of the destroyed houses in the earthquake affected areas. Our contributions in this research are as follows: 1) critical analysis of existing tools of visualization for earthquake rehabilitation systems 2) propose and develop a framework for converting raw data into actionable knowledge, 3) propose, develop and evaluate an innovative visualization technique.
Visual analysis of knowledge expertise is becoming an emerging field due to its vital and essential importance of discovering both expertise and experts in practical applications. There are numerous visualization tech...
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Visual analysis of knowledge expertise is becoming an emerging field due to its vital and essential importance of discovering both expertise and experts in practical applications. There are numerous visualization techniques which can identify the knowledge domains of research groups and communities. In this paper, we visualize and identify the expertise of an individual author based on the analysis of the author's profile and its available information in DBLP databases. We have presented an approach to analyze both knowledge domains of individual authors as well as topic wise experts. In order to validate and comparison, we use the Gephi visualization tool to observe what is similar (comparison) or difference (contrast) between our proposed methodology and Gephi.
semantic cache enhances the capability of conventional (page/tuple) cache by adopting the dynamic strategy to group the contents and semantics of already processed queries. Query processing and cache management are tw...
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Ontology Evaluation is one of the most critical phases in ontology engineering. Applications depending upon ontology can have serious and appalling problems if ontology itself is infected with errors. Therefore, ontol...
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Identification and assignment of (potential) experts to subject field is an important task in various settings and environments. In scientific domain, the identification of experts is normally based on number of facto...
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