Materializing knowledge bases via trigger graphs

The chase is a well-established family of algorithms used to materialize Knowledge Bases (KBs) for tasks like query answering under dependencies or data cleaning. A general problem of chase algorithms is that they might perform redundant computations. To counter this problem, we introduce the notion of Trigger Graphs (TGs), which guide the execution of the rules avoiding redundant computations. We present the results of an extensive theoretical and empirical study that seeks to answer when and how TGs can be computed and what are the benefits of TGs when applied over real-world KBs. Our results include introducing algorithms that compute (minimal) TGs. We implemented our approach in a new engine, called GLog, and our experiments show that it can be significantly more efficient than the chase enabling us to materialize Knowledge Graphs with 17B facts in less than 40 min using a single machine with commodity hardware.

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Entity Alignment between Knowledge Graphs Using Attribute Embeddings

Proceedings of the AAAI Conference on Artificial Intelligence ◽

10.1609/aaai.v33i01.3301297 ◽

2019 ◽

Vol 33 ◽

pp. 297-304 ◽

Cited By ~ 26

Author(s):

Bayu Distiawan Trisedya ◽

Jianzhong Qi ◽

Rui Zhang

Keyword(s):

Real World ◽

Graph Embedding ◽

Knowledge Bases ◽

Knowledge Graph ◽

World Knowledge ◽

Large Numbers ◽

Proposed Model ◽

Alignment Task ◽

Transitivity Rule ◽

Knowledge Graphs

The task of entity alignment between knowledge graphs aims to find entities in two knowledge graphs that represent the same real-world entity. Recently, embedding-based models are proposed for this task. Such models are built on top of a knowledge graph embedding model that learns entity embeddings to capture the semantic similarity between entities in the same knowledge graph. We propose to learn embeddings that can capture the similarity between entities in different knowledge graphs. Our proposed model helps align entities from different knowledge graphs, and hence enables the integration of multiple knowledge graphs. Our model exploits large numbers of attribute triples existing in the knowledge graphs and generates attribute character embeddings. The attribute character embedding shifts the entity embeddings from two knowledge graphs into the same space by computing the similarity between entities based on their attributes. We use a transitivity rule to further enrich the number of attributes of an entity to enhance the attribute character embedding. Experiments using real-world knowledge bases show that our proposed model achieves consistent improvements over the baseline models by over 50% in terms of hits@1 on the entity alignment task.

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An Empirical Study of Real-World WebAssembly Binaries

Proceedings of the Web Conference 2021 ◽

10.1145/3442381.3450138 ◽

2021 ◽

Author(s):

Aaron Hilbig ◽

Daniel Lehmann ◽

Michael Pradel

Keyword(s):

Empirical Study ◽

Real World

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An Improved Set-based Reasoner for the Description Logic 𝒟ℒD4,×†

Fundamenta Informaticae ◽

10.3233/fi-2021-2009 ◽

2021 ◽

Vol 178 (4) ◽

pp. 315-346

Author(s):

Domenico Cantone ◽

Marianna Nicolosi-Asmundo ◽

Daniele Francesco Santamaria

Keyword(s):

Semantic Web ◽

Set Theory ◽

Description Logic ◽

Knowledge Bases ◽

Query Answering ◽

Conjunctive Query ◽

Classification Problems ◽

Previous Version ◽

Decidable Fragment ◽

Stratified Set

We present a KE-tableau-based implementation of a reasoner for a decidable fragment of (stratified) set theory expressing the description logic 𝒟ℒ〈4LQSR,×〉(D) (𝒟ℒD4,×, for short). Our application solves the main TBox and ABox reasoning problems for 𝒟ℒD4,×. In particular, it solves the consistency and the classification problems for 𝒟ℒD4,×-knowledge bases represented in set-theoretic terms, and a generalization of the Conjunctive Query Answering problem in which conjunctive queries with variables of three sorts are admitted. The reasoner, which extends and improves a previous version, is implemented in C++. It supports 𝒟ℒD4,×-knowledge bases serialized in the OWL/XML format and it admits also rules expressed in SWRL (Semantic Web Rule Language).

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Utilizing commodity hardware and software to distribute a real-world application: maximizing reuse while improving performance

Software Practice and Experience ◽

10.1002/spe.651 ◽

2005 ◽

Vol 35 (7) ◽

pp. 621-641

Author(s):

Michael Davis ◽

Randy Smith ◽

Brandon Dixon ◽

Allen Parrish ◽

David Cordes

Keyword(s):

Real World ◽

Commodity Hardware ◽

Real World Application

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Hybrid optimization algorithms by various structures for a real-world inverse scheduling problem with uncertain due-dates under single-machine shop systems

Neural Computing and Applications ◽

10.1007/s00521-018-3472-7 ◽

2018 ◽

Vol 31 (9) ◽

pp. 4595-4612 ◽

Cited By ~ 4

Author(s):

Jianhui Mou ◽

Liang Gao ◽

Qianjian Guo ◽

Rufeng Xu ◽

Xinyu Li

Keyword(s):

Single Machine ◽

Real World ◽

Optimization Algorithms ◽

Hybrid Optimization ◽

Scheduling Problem ◽

Due Dates ◽

Machine Shop ◽

Hybrid Optimization Algorithms ◽

Inverse Scheduling

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DATAtourist

International Journal of Decision Support System Technology ◽

10.4018/ijdsst.2021040104 ◽

2021 ◽

Vol 13 (2) ◽

pp. 62-84

Author(s):

Boudjemaa Boudaa ◽

Djamila Figuir ◽

Slimane Hammoudi ◽

Sidi mohamed Benslimane

Keyword(s):

Software Engineering ◽

Knowledge Acquisition ◽

Software Architecture ◽

Recommender Systems ◽

Real World ◽

Mobile Application ◽

Knowledge Bases ◽

User Requirements ◽

World Knowledge ◽

Points Of Interest

Collaborative and content-based recommender systems are widely employed in several activity domains helping users in finding relevant products and services (i.e., items). However, with the increasing features of items, the users are getting more demanding in their requirements, and these recommender systems are becoming not able to be efficient for this purpose. Built on knowledge bases about users and items, constraint-based recommender systems (CBRSs) come to meet the complex user requirements. Nevertheless, this kind of recommender systems witnesses a rarity in research and remains underutilised, essentially due to difficulties in knowledge acquisition and/or in their software engineering. This paper details a generic software architecture for the CBRSs development. Accordingly, a prototype mobile application called DATAtourist has been realized using DATAtourisme ontology as a recent real-world knowledge source in tourism. The DATAtourist evaluation under varied usage scenarios has demonstrated its usability and reliability to recommend personalized touristic points of interest.

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Pervasive Computing in the Supermarket

Social and Organizational Impacts of Emerging Mobile Devices ◽

10.4018/978-1-4666-0194-9.ch010 ◽

2012 ◽

pp. 172-185 ◽

Cited By ~ 4

Author(s):

Darren Black ◽

Nils Jakob Clemmensen ◽

Mikael B. Skov

Keyword(s):

Empirical Study ◽

Real World ◽

Context Awareness ◽

Empirical Evaluation ◽

Context Aware ◽

Uniform Pattern ◽

User Attention ◽

Context Aware System ◽

Mobile Context ◽

Interactive Experience

Shopping in the real world is becoming an increasingly interactive experience as stores integrate various technologies to support shoppers. Based on an empirical study of supermarket shoppers, the authors designed a mobile context-aware system called the Context-Aware Shopping Trolley (CAST). The purpose of CAST is to support shopping in supermarkets through context-awareness and acquiring user attention, thus, the authors’ interactive trolley guides and directs shoppers in the handling and finding of groceries. An empirical evaluation showed that shoppers using CAST behaved differently than shoppers using a traditional trolley. Specifically, shoppers using CAST exhibited a more uniform pattern of product collection and found products more easily while travelling a shorter distance. As such, the study finds that CAST supported the supermarket shopping activity.

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The innovative personal potential: the content of the concept and empirical study

SHS Web of Conferences ◽

10.1051/shsconf/20196900057 ◽

2019 ◽

Vol 69 ◽

pp. 00057

Author(s):

Valeriia Kapustina ◽

Eugenia Bykova

Keyword(s):

Theoretical Analysis ◽

Empirical Study ◽

Personality Traits ◽

Real World ◽

Self Esteem ◽

State Technical ◽

Behavioral Component ◽

Simple Idea ◽

Cognitive Component ◽

New Information

The article is devoted to the theoretical analysis of an innovative personal potential as a psychological construct. Well-known definitions of an innovative personal potential have such characteristics as openness to new information and experience (cognitive component), a desire to change/willingness to create something new (motivational component), innovative activity (behavioral component) and value-semantic system (axiological component). The empirical study of an innovative personal potential of student was held in Novosibirsk State Technical University. Authors used psychological tests (KTS by D. Keirsey, TAS by S. Badner; Tests by F. Williams, the scale of self-esteem of an innovative personality traits by N.M. Lebedeva, A.N. Tatarko, “Problems of the real world” by R. Sternberg). The sample included 177 students. The correlational analysis showed that students, who consider themselves innovative persons, show interest, plays with ideas, reflects on the hidden meaning. They are tolerant to new situations, to the emergence of possible difficulties, they tend to be open, relaxed, free, mobile, trendwatching and are able to deviate from obvious and generally accepted things and develop a simple idea to make it more interesting. Also, it is found that Rational and Idealist types have more apparent characteristics of an innovative personal potential.

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