arXiv subjects

Joshua Shinavier

Publications and source records attributed to Joshua Shinavier.

8 recordsLinked to original sources

arXiv2021

Threshold Queries in Theory and in the Wild

Threshold queries are an important class of queries that only require computing or counting answers up to a specified threshold value. To the best of our knowledge, threshold queries have been largely disregarded in the research literature, which is surprising considering how common they are in practice. In this paper, we present a deep theoretical analysis of threshold query evaluation and show that thresholds can be used to significantly improve the asymptotic bounds of state-of-the-art query evaluation algorithms. We also empirically show that threshold queries are significant in practice. In surprising contrast to conventional wisdom, we found important scenarios in real-world data sets in which users are interested in computing the results of queries up to a certain threshold, independent of a ranking function that orders the query results by importance.

cs.DB↗

arXiv2020

The Future is Big Graphs! A Community View on Graph Processing Systems

Graphs are by nature unifying abstractions that can leverage interconnectedness to represent, explore, predict, and explain real- and digital-world phenomena. Although real users and consumers of graph instances and graph workloads understand these abstractions, future problems will require new abstractions and systems. What needs to happen in the next decade for big graph processing to continue to succeed?

cs.DC↗

arXiv2019

Algebraic Property Graphs

We present a case study in applied category theory written from the point of view of an applied domain: the formalization of the widely-used property graphs data model in an enterprise setting using elementary constructions from type theory and category theory, including limit and co-limit sketches. Observing that algebraic data types are a common foundation of most of the enterprise schema languages we deal with in practice, for graph data or otherwise, we introduce a type theory for algebraic property graphs wherein the types denote both algebraic data types in the sense of functional programming and join-union E/R diagrams in the sense of database theory. We also provide theoretical foundations for graph transformation along schema mappings with by-construction guarantees of semantic consistency. Our data model originated as a formalization of a data integration toolkit developed at Uber which carries data and schemas along composable mappings between data interchange languages such as Apache Avro, Apache Thrift, and Protocol Buffers, and graph languages including RDF with OWL or SHACL-based schemas.

cs.DB↗

arXiv2010

Optimizing real-time RDF data streams

The Resource Description Framework (RDF) provides a common data model for the integration of "real-time" social and sensor data streams with the Web and with each other. While there exist numerous protocols and data formats for exchanging dynamic RDF data, or RDF updates, these options should be examined carefully in order to enable a Semantic Web equivalent of the high-throughput, low-latency streams of typical Web 2.0, multimedia, and gaming applications. This paper contains a brief survey of RDF update formats and a high-level discussion of both TCP and UDP-based transport protocols for updates. Its main contribution is the experimental evaluation of a UDP-based architecture which serves as a real-world example of a high-performance RDF streaming application in an Internet-scale distributed environment.

cs.AI↗

arXiv2010

Simulating information creation in social Semantic Web applications

Appropriate ranking algorithms and incentive mechanisms are essential to the creation of high-quality information by users of a social network. However, evaluating such mechanisms in a quantifiable way is a difficult problem. Studies of live social networks of limited utility, due to the subjective nature of ranking and the lack of experimental control. Simulation provides a valuable alternative: insofar as the simulation resembles the live social network, fielding a new algorithm within a simulated network can predict the effect it will have on the live network. In this paper, we propose a simulation model based on the actor-conceptinstance model of semantic social networks, then we evaluate the model against a number of common ranking algorithms.We observe their effects on information creation in such a network, and we extend our results to the evaluation of generic ranking algorithms and incentive mechanisms.

cs.CE↗

arXiv2010

The Dilated Triple

The basic unit of meaning on the Semantic Web is the RDF statement, or triple, which combines a distinct subject, predicate and object to make a definite assertion about the world. A set of triples constitutes a graph, to which they give a collective meaning. It is upon this simple foundation that the rich, complex knowledge structures of the Semantic Web are built. Yet the very expressiveness of RDF, by inviting comparison with real-world knowledge, highlights a fundamental shortcoming, in that RDF is limited to statements of absolute fact, independent of the context in which a statement is asserted. This is in stark contrast with the thoroughly context-sensitive nature of human thought. The model presented here provides a particularly simple means of contextualizing an RDF triple by associating it with related statements in the same graph. This approach, in combination with a notion of graph similarity, is sufficient to select only those statements from an RDF graph which are subjectively most relevant to the context of the requesting process.

cs.AI↗

arXiv2009

Exposing Multi-Relational Networks to Single-Relational Network Analysis Algorithms

Many, if not most network analysis algorithms have been designed specifically for single-relational networks; that is, networks in which all edges are of the same type. For example, edges may either represent "friendship," "kinship," or "collaboration," but not all of them together. In contrast, a multi-relational network is a network with a heterogeneous set of edge labels which can represent relationships of various types in a single data structure. While multi-relational networks are more expressive in terms of the variety of relationships they can capture, there is a need for a general framework for transferring the many single-relational network analysis algorithms to the multi-relational domain. It is not sufficient to execute a single-relational network analysis algorithm on a multi-relational network by simply ignoring edge labels. This article presents an algebra for mapping multi-relational networks to single-relational networks, thereby exposing them to single-relational network analysis algorithms.

cs.DM↗

arXiv2009

A Recommender System to Support the Scholarly Communication Process

The number of researchers, articles, journals, conferences, funding opportunities, and other such scholarly resources continues to grow every year and at an increasing rate. Many services have emerged to support scholars in navigating particular aspects of this resource-rich environment. Some commercial publishers provide recommender and alert services for the articles and journals in their digital libraries. Similarly, numerous noncommercial social bookmarking services have emerged for citation sharing. While these services do provide some support, they lack an understanding of the various problem-solving scenarios that researchers face daily. Example scenarios, to name a few, include when a scholar is in search of an article related to another article of interest, when a scholar is in search of a potential collaborator for a funding opportunity, when a scholar is in search of an optimal venue to which to submit their article, and when a scholar, in the role of an editor, is in search of referees to review an article. All of these example scenarios can be represented as a problem in information filtering by means of context-sensitive recommendation. This article presents an overview of a context-sensitive recommender system to support the scholarly communication process that is based on the standards and technology set forth by the Semantic Web initiative.

cs.DL↗