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International Conference on Emerging Technologies, ICET

作者： Qamar Mahmood Muhammad Abdul Qadir Muhammad Tanvir Afzal Center for Distributed and Semantic Computing Mohammad Ali Jinnah University Islamabad Pakistan

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.

关键词： Social network services Resource description framework semantics Ontologies Algorithm design and analysis Fluid flow measurement Manuals

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Knowledge discovery in hashtags#

Knowledge discovery in hashtags#

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International Conference on Emerging Technologies, ICET

作者： Rizwan Mehmood Hermann Maurer Muhammad Tanveer Afzal Institute for Information Systems and Computer Media Graz University of Technology Graz Austria Center for Distributed and Semantic Computing Mohammad Ali Jinnah University Islamabad Pakistan

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.

关键词： Twitter Data visualization Knowledge discovery Data mining Libraries Communities

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semantic Aware Implication and Satisfiability for Conjunctive Queries in semantic Caching

Semantic Aware Implication and Satisfiability for Conjunctiv...

引用

4th International Conference on Networked Digital Technologies, NDT 2012

作者： Abbas, Muhammad Azeem Qadir, Muhammad Abdul Ahmad, Munir Ali, Tariq Center for Distributed and Semantic Computing Mohammad Ali Jinnah University Islamabad Pakistan

ISBN: (纸本)9783642305061

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{pipe}3). Similarly complexity of finding "Is S implies T (S→T)" is O(S3+K) Where {pipe}S{pipe} is the number of distinct predicate attributes in S, and K is the number of predicate terms in T (S and T are conjunctive select-project-join(PSJ) queries). We show that with the induction of Cross Attribute Knowledge (CRA) the above complexity is reduced to O({pipe}S - CRA{pipe}3) and O({pipe}S - CRA{pipe}3+K) for satisfiability and implication respectively. © Springer-Verlag Berlin Heidelberg 2012.

关键词： Formal logic

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ERRAGMap: Visualization tool

ERRAGMap: Visualization tool

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8th International Conference on Information Science and Digital Content Technology, ICIDT 2012

作者： Gillani, Saira Naz, Sheneela Naeem, Muhammad Afzal, Muhammad Tanvir Qayyum, Amir M. A. Jinnah University Islamabad Pakistan Center of Excellence in Data Mining M. A. Jinnah University Islamabad Pakistan Distributed and Semantic Computing M. A. Jinnah University Islamabad Pakistan

ISBN: (纸本)9788988678695

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 geo spatial 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. © 2012 AICIT.

关键词： Visualization

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Adaptive Path Ranking Technique for Maximization of Gains of Bandwidth Aggregation over Heterogeneous Wireless Links

Adaptive Path Ranking Technique for Maximization of Gains of...

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International Conference on Broadband, Wireless computing, Communication and Applications (BWCCA)

作者： Syed Zubair Ahmad Muhammad Abdul Qadir Samiullah Khan Management Information System Pakistan Institute of Nuclear Scienceand Technology Islamabad Pakistan Center for Distributed and Semantic Computing Muhammad Ali Jinnah University Islamabad Pakistan

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.

关键词： Delay Servers Adaptation models Stochastic processes Bandwidth Estimation Throughput

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ERRAGMap: Visualization tool

ERRAGMap: Visualization tool

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International Conference on Digital Content, Multimedia Technology and its Applications (IDC)

作者： Saira Gillani Sheneela Naz Muhammad Naeem Muhammad Tanvir Afzal Amir Qayyum Center of Research in Networks & Telecom (CoReNeT) M. A. Jinnah University Islamabad Pakistan Center of Excellence in Data Mining M. A. Jinnah University Islamabad Pakistan Distributed & Semantic Computing M. A. Jinnah University Islamabad Pakistan

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.

关键词： Visualization Earth Graphical user interfaces Monitoring Earthquakes Computational modeling Irrigation

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Expertise identification and visualization

Expertise identification and visualization

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International Conference on computing and Networking Technology (ICCNT)

作者： Sheneela Naz Muhammad Naeem Muhammad Tanvir Afzal Amir Qayyum Research in Networks and Telecom (CoReNeT) M. A. Jinnah University Islamabad Pakistan Center of Excellence in Data Mining M. A. Jinnah University Islamabad Pakistan Distributed & Semantic Computing M. A. Jinnah University Islamabad Pakistan

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.

关键词： Visualization Data visualization Manuals Algorithm design and analysis Economics Reliability engineering Reliability theory

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Graph based query trimming algorithm for relational data semantic cache 10

Graph based query trimming algorithm for relational data sem...

引用

Proceedings of the International Conference on Management of Emergent Digital EcoSystems

作者： Ahmad, Munir Asghar, Sohail Qadir, M. Abdul Ali, Tariq Center for Distributed and Semantic Computing Mohammad Ali Jinnah University Islamabad Pakistan

ISBN: (纸本)9781450300476

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 two major activities for semantic caching. semantic caching demands efficient, correct and complete algorithms to process incoming queries. Efficiency of query processing activity in semantic cache mainly depends on query trimming. Query trimming process consists of two sub processes;query matching and query splitting. Efficient query matching and query splitting process will ensures the optimal query trimming process. In this paper, we have proposed query trimming algorithm by defining query matching algorithm and using query splitting algorithm from the literature. To optimize the query matching process we have proposed graph based semantic indexing scheme. On the basis of proposed indexing scheme we have designed query matching algorithm (qTrim). We have proved that complexity of graph based query matching algorithm is reduced to linear from exponential. Comparison of graph based (proposed) scheme is done with segment based scheme. On the basis of comparison and runtime complexity we have argued that the proposed algorithm is an optimum to trim the queries into sub-queries (probe and remainder). Copyright © 2010 ACM.

关键词： Query processing

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Evaluation of extended error taxonomy for OWL2

Evaluation of extended error taxonomy for OWL2

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2nd International Conference on Information and Emerging Technologies, ICIET 2010

作者： Sajid, Naseer Ahmed Qadir, Muhammad Abdul Ali, Tariq Center for Distributed and Semantic Computing Department of Computer Science Mohammad Ali Jinnah University Islamabad Pakistan

ISBN: (纸本)9781424480012

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, ontology should be consistent, complete and errors free. An error taxonomy using OWL constructs and axioms was developed to overcome the possibility of occurring errors in ontology. Recently, some new features have been proposed in OWL2 specification to overcome the limitation of expressive power of OWL. In this paper we evaluate the extended error taxonomy of OWL with the new features of OWL2. We also evaluate that while using OWL2 features, occurrence of possibility of new types of errors get reduced or not. On the basis of different examples for each error, we conclude that the error taxonomy is also valid for OWL2. This is because of the fact that every OWL ontology is a valid OWL2 ontology and every OWL2 ontology (excluding new features) is also a valid OWL ontology. The zero level circulatory errors can also be removed if we use the reflexive property and self restriction (local reflexive) property of OWL2. Otherwise, we have to generate a warning omission for zero level circulatory error. ©2010 IEEE.

关键词： Ontology

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Constructing experts profiles from Linked Open Data

Constructing experts profiles from Linked Open Data

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International Conference on Emerging Technologies

作者： Latif, Atif Afzal, Muhammad Tanvir Tochtermann, Klaus Graz University of Technology Knowledge Management Institute Know Center Graz Austria Centre for Distributed and Semantic Computing Mohammad Ali Jinnah University Islamabad Pakistan

ISBN: (纸本)9781424480586

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 factors like: number of publications, citation record, and experience etc. However, the discovered experts cannot be assigned reviewing duties immediately. One also need further information about expert like the country, university, service record, contributions, honors, and name of conferences/journals where the discovered expert is already serving as editor/reviewer. To some extent, this information can be found from search engines using heuristics, by applying Natural Language Processing, and Machine Learning techniques. However, the emergence of many semantically rich and structured datasets from Linked Open Data movement (LOD) can facilitate in more controlled search and fruitful results. This paper employs an automatic technique to find the required information about experts using LOD dataset. The expert profile is discovered, aggregated, clustered, structured, and visualized to the administration of peer-review system. The system has been implemented for an electronic journal such as Journal of Universal Computer Science (***). The proposed system facilitates *** administration to find potential reviewers for scientific papers to assign reviewing duties and to call new editors for computer science topics. © 2010 IEEE.

关键词： Linked data

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