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Ranking - the algorithmic decision on how relevant an information artifact is for a given information need and the sorting of artifacts by their concluded relevancy - is an integral part of every search engine. In this book we investigate how structured Web data can be leveraged for ranking with the goal to improve the effectiveness of search. We propose new solutions for ranking using on-the-fly data integration and experimentally analyze and evaluate them against the latest baselines.
search --- information retrieval --- web data --- semantic search
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Due to the difficulties encountered by users of SmartShare - management software marketed by EASI - to find their documents within the various databases, a multi-DBs search engine must be incorporated into the software. Today, in the scientific world and in practice, more and more search engines no longer work simply on the superficial representation of words but infer the meaning of these words in order to better respond to queries. These search engines are known as semantic search engines. Therefore, the aim of this project-dissertation is twofold: the development of a multi-DBs search engine for SmartShare and the analysis of semantic extension possibilities. First, a literature review is conducted to provide an overview of existing intelligent search engines, their characteristics and architectures. Then, the characteristics to be provided to the search engine are listed on the basis of a functional analysis of the need carried out beforehand. Finally, a minimum viable product is developed and the business plan is drawn up. Then come the research question: Could the search engine developed for EASI be extended with semantic features? In order to answer this question, another research sub-question arises: Among features of existing semantic search engines, which ones are adapted to the search engine developed for EASI? To answer this sub-question, the different features stated in the literature review are cross-referenced with the characteristics to be provided to the search engine in order to meet the needs of users. Four semantic extensions are then studied in detail: TF-IDF as a sorting method, two mapping algorithms to integrate the meaning of search queries, topic detection, and the extension to multimedia retrieval.
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Complex networks are one of the most challenging research focuses of disciplines, including physics, mathematics, biology, medicine, engineering, and computer science, among others. The interest in complex networks is increasingly growing, due to their ability to model several daily life systems, such as technology networks, the Internet, and communication, chemical, neural, social, political and financial networks. The Special Issue “Computation in Complex Networks" of Entropy offers a multidisciplinary view on how some complex systems behave, providing a collection of original and high-quality papers within the research fields of: • Community detection • Complex network modelling • Complex network analysis • Node classification • Information spreading and control • Network robustness • Social networks • Network medicine
Technology: general issues --- city interaction network --- evolution model --- preferential attachment --- WeChat --- maximum likelihood --- chimera states --- coupled map lattice --- nilpotent matrix --- community detection --- membrane algorithm --- self-organizing map network --- complex networks --- optimization --- structural balance --- minimum memory based sign adjustment --- social networks --- NW network --- convergence --- complex system simulation --- cloud computing architecture --- service-oriented modeling --- semantic search framework --- QoS-based service selection --- cascading failures --- network topology --- null models --- SciSci --- knowledge evolution --- machine learning --- bridging centrality --- disjoint nodes --- disjunct nodes --- node similarity --- overlapping nodes --- Bayesian networks --- entropy --- socio-ecological system --- complex network --- chaotic time series --- Gaussian mixture model --- maximum mean discrepancy --- angiogenesis --- network properties --- variational inference --- graph neural network --- variational autoencoder --- network embedding --- online social networks --- social media --- information spreading --- information diffusion --- cross-entropy --- cross-domain recommendation --- sentiment analysis --- latent sentiment review feature --- non-linear mapping --- dissimilarity spaces --- support vector machines --- kernel methods --- computational biology --- systems biology --- protein contact networks --- data mining --- overlapping communities --- modularity --- literary works --- genre classification --- stylistic attributes --- lemmatization --- renormalisation process --- network growth --- inverse preferential attachment --- language networks --- language development --- multilayer complex networks --- stability --- spreading control --- graph neural networks --- node classification --- active learning --- graph representation learning --- city interaction network --- evolution model --- preferential attachment --- WeChat --- maximum likelihood --- chimera states --- coupled map lattice --- nilpotent matrix --- community detection --- membrane algorithm --- self-organizing map network --- complex networks --- optimization --- structural balance --- minimum memory based sign adjustment --- social networks --- NW network --- convergence --- complex system simulation --- cloud computing architecture --- service-oriented modeling --- semantic search framework --- QoS-based service selection --- cascading failures --- network topology --- null models --- SciSci --- knowledge evolution --- machine learning --- bridging centrality --- disjoint nodes --- disjunct nodes --- node similarity --- overlapping nodes --- Bayesian networks --- entropy --- socio-ecological system --- complex network --- chaotic time series --- Gaussian mixture model --- maximum mean discrepancy --- angiogenesis --- network properties --- variational inference --- graph neural network --- variational autoencoder --- network embedding --- online social networks --- social media --- information spreading --- information diffusion --- cross-entropy --- cross-domain recommendation --- sentiment analysis --- latent sentiment review feature --- non-linear mapping --- dissimilarity spaces --- support vector machines --- kernel methods --- computational biology --- systems biology --- protein contact networks --- data mining --- overlapping communities --- modularity --- literary works --- genre classification --- stylistic attributes --- lemmatization --- renormalisation process --- network growth --- inverse preferential attachment --- language networks --- language development --- multilayer complex networks --- stability --- spreading control --- graph neural networks --- node classification --- active learning --- graph representation learning
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Complex networks are one of the most challenging research focuses of disciplines, including physics, mathematics, biology, medicine, engineering, and computer science, among others. The interest in complex networks is increasingly growing, due to their ability to model several daily life systems, such as technology networks, the Internet, and communication, chemical, neural, social, political and financial networks. The Special Issue “Computation in Complex Networks" of Entropy offers a multidisciplinary view on how some complex systems behave, providing a collection of original and high-quality papers within the research fields of: • Community detection • Complex network modelling • Complex network analysis • Node classification • Information spreading and control • Network robustness • Social networks • Network medicine
Technology: general issues --- city interaction network --- evolution model --- preferential attachment --- WeChat --- maximum likelihood --- chimera states --- coupled map lattice --- nilpotent matrix --- community detection --- membrane algorithm --- self-organizing map network --- complex networks --- optimization --- structural balance --- minimum memory based sign adjustment --- social networks --- NW network --- convergence --- complex system simulation --- cloud computing architecture --- service-oriented modeling --- semantic search framework --- QoS-based service selection --- cascading failures --- network topology --- null models --- SciSci --- knowledge evolution --- machine learning --- bridging centrality --- disjoint nodes --- disjunct nodes --- node similarity --- overlapping nodes --- Bayesian networks --- entropy --- socio-ecological system --- complex network --- chaotic time series --- Gaussian mixture model --- maximum mean discrepancy --- angiogenesis --- network properties --- variational inference --- graph neural network --- variational autoencoder --- network embedding --- online social networks --- social media --- information spreading --- information diffusion --- cross-entropy --- cross-domain recommendation --- sentiment analysis --- latent sentiment review feature --- non-linear mapping --- dissimilarity spaces --- support vector machines --- kernel methods --- computational biology --- systems biology --- protein contact networks --- data mining --- overlapping communities --- modularity --- literary works --- genre classification --- stylistic attributes --- lemmatization --- renormalisation process --- network growth --- inverse preferential attachment --- language networks --- language development --- multilayer complex networks --- stability --- spreading control --- graph neural networks --- node classification --- active learning --- graph representation learning --- n/a
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Complex networks are one of the most challenging research focuses of disciplines, including physics, mathematics, biology, medicine, engineering, and computer science, among others. The interest in complex networks is increasingly growing, due to their ability to model several daily life systems, such as technology networks, the Internet, and communication, chemical, neural, social, political and financial networks. The Special Issue “Computation in Complex Networks" of Entropy offers a multidisciplinary view on how some complex systems behave, providing a collection of original and high-quality papers within the research fields of: • Community detection • Complex network modelling • Complex network analysis • Node classification • Information spreading and control • Network robustness • Social networks • Network medicine
city interaction network --- evolution model --- preferential attachment --- WeChat --- maximum likelihood --- chimera states --- coupled map lattice --- nilpotent matrix --- community detection --- membrane algorithm --- self-organizing map network --- complex networks --- optimization --- structural balance --- minimum memory based sign adjustment --- social networks --- NW network --- convergence --- complex system simulation --- cloud computing architecture --- service-oriented modeling --- semantic search framework --- QoS-based service selection --- cascading failures --- network topology --- null models --- SciSci --- knowledge evolution --- machine learning --- bridging centrality --- disjoint nodes --- disjunct nodes --- node similarity --- overlapping nodes --- Bayesian networks --- entropy --- socio-ecological system --- complex network --- chaotic time series --- Gaussian mixture model --- maximum mean discrepancy --- angiogenesis --- network properties --- variational inference --- graph neural network --- variational autoencoder --- network embedding --- online social networks --- social media --- information spreading --- information diffusion --- cross-entropy --- cross-domain recommendation --- sentiment analysis --- latent sentiment review feature --- non-linear mapping --- dissimilarity spaces --- support vector machines --- kernel methods --- computational biology --- systems biology --- protein contact networks --- data mining --- overlapping communities --- modularity --- literary works --- genre classification --- stylistic attributes --- lemmatization --- renormalisation process --- network growth --- inverse preferential attachment --- language networks --- language development --- multilayer complex networks --- stability --- spreading control --- graph neural networks --- node classification --- active learning --- graph representation learning --- n/a
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