1,720,979 research outputs found
Ontology: Querying languages and development
No full textOntologies are a key support to provide a shared understanding of knowledge domains. Their flexibility and usefulness is witnessed in a variety of scenarios, from knowledge-based retrieval to projects like the Semantic Web. The possibility to express semantic information gave birth to a new class of query languages specifically designed. We will give an overview of one of such languages called SPARQL. SPARQL is the W3C standard to query data represented in RDF, another W3C standard. By using examples, we illustrate the structure of a SPARQL query. Then, we give an overview of popular ontology management tools
CAKES: Cross-lingual wikipedia knowledge enrichment and summarization
No full textWikipedia is a huge source of multilingual knowledge curated by human contributors. Wiki articles are independently written in the various languages and may cover different perspectives about a given subject. The aim of this paper is to exploit Wikipedia multilingual information for knowledge enrichment and summarization. Investigating the link structure of a Wiki article in a source language and comparing it with the structure of articles about the same subject written in other languages gives insights about the body of knowledge shared among languages. This investigation is also useful to identify knowledge perspectives not covered in the source language but covered in other languages. We implemented these ideas in CAKES, which: i) exploits Wikipedia information on the fly without requiring any data preprocessing; ii) enables to specify the set of languages to be considered and; iii) ranks subjects interesting for a given article on the basis of their popularity among languages
Structural Characterization of Graph Navigational Languages
No full textGraph navigational languages define binary relations in terms of pair of nodes in a graph subject to the existence of a path satisfying a certain regular expression. The goal of this paper is to give a novel characterization of navigational languages in terms of the structure of the graph embracing the results of a query. We define novel graph-based query evaluation semantics and efficient algorithms able to represent and capture intermediate nodes/edges linking pairs of nodes in the answer. We enhance the language of Nested Regular Expressions (NREs) with our machineries, thus defining the language of Structural NREs (sNREs)
Querying graphs with preferences
No full textThis paper presents GuLP a graph query language that enables to declaratively express preferences. Preferences enable to order the answers to a query and can be stated in terms of nodes/edge attributes and complex paths. We present the formal syntax and semantics of GuLP and a polynomial time algorithm for evaluating GuLP expressions. We describe an implementation of GuLP in the GuLP-it system, which is available for download. We evaluate the GuLP-it system on real-world and synthetic data. Copyright 2013 ACM
Ontology: Definition languages
No full textOntologies are artifacts used to model and represent in an explicit way knowledge related to a particular domain in terms of concepts, relations between concepts and axioms. In this article we provide an overview of ontology languages that have been defined under the umbrella of the W3C consortium. These language are characterized by different levels of expressiveness, starting from RDF, a simple language to express statements in the form of triples, to OWL, which enables very expressive forms of inference
From Node Embeddings to Triple Embeddings
No full textAn extended version of this paper has been published at the the 34th AAAI Conference on Artificial Intelligence (AAAI) with the title “Learning Triple Embeddings from Knowledge Graphs”. Graph embedding techniques allow to learn high-quality low-dimensional graph representations useful in various tasks, from node classification to clustering. Knowledge graphs are particular types of graphs characterized by several distinct types of nodes and edges. Existing knowledge graph embedding approaches have only focused on learning embeddings of nodes and predicates. However, the basic piece of information stored in knowledge graphs are triples and thus, an interesting problem is that of learning embeddings of triples as a whole. In this paper we report on Triple2Vec, a new technique to directly compute triple embeddings in knowledge graphs. Triple2Vec leverages the idea of line graph and extends it to the context of knowledge graphs. Embeddings are then generated by adopting the SkipGram model, where sentences are replaced with walks on a wighted version of the line graph
Community deception: from undirected to directed networks
No full textCommunity deception is about hiding a target community that wants to remain below the radar of community detection algorithms. The goal is to devise algorithms that, given a maximum number of updates (e.g., edge additions and removal), strive to find the best way to perform such updates in order to hide the target community inside the community structure found by a detection algorithm. So far, community deception has only been studied for undirected networks, although many real-world networks (e.g., Twitter) are directed. One way to overcome this problem would be to treat the network as undirected. However, this approach discards potentially helpful information in the edge directions (e.g., A follows B does not imply that B follows A). The aim of this paper is threefold. First, to give an account of the state-of-the-art community deception techniques in undirected networks underlying their peculiarities. Second, to investigate the community deception problem in directed networks and to show how deception techniques proposed for undirected networks should be modified and adapted to work on directed networks. Third, to evaluate deception techniques both in undirected and directed networks. Our experimental evaluation on a variety of (large) directed networks shows that techniques that work well for undirected networks fail short when directly applied to directed networks, thus underlying the need for specific approaches
Web maps and their algebra
No full textA map is an abstract visual representation of a region, taken from a given space, usually designed for final human consumption. Traditional cartography focuses on the mapping of Euclidean spaces by using some distance metric. In this paper we aim at mapping the Web space by leveraging its relational nature. We introduce a general mathematical framework for maps and an algebra. Finally, we discuss the feasibility of maps suitable for interpretation not only by humans but also by machines
Knowledge maps of Web graphs
No full textIn this short note we give an overview of our research concerning cartography on the Web and its challenges. We present a mathematical formalism to capture the notion of map on theWeb, which allows to automatize the construction of maps
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