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Ontology-based entity matching in attributed graphs

Hanchao Ma, Morteza Alipourlangouri, Yinghui Wu, Fei Chiang, Jiaxing Pi
2019 Proceedings of the VLDB Endowment  
Keys for graphs incorporate the topology and value constraints needed to uniquely identify entities in a graph.  ...  We propose a new class of key constraints, Ontological Graph Keys (OGKs) that extend conventional graph keys by ontological subgraph matching between entity labels and an external ontology.  ...  This work is supported in part by USDA/NIFA 2018-67007-28797, Siemens, and the Department of Energy under DE-IA0000025 for UI-ASSIST project.  ... 
doi:10.14778/3339490.3339501 fatcat:zi645j33bjbqzcqlltd4ci6vvq

Capability description and discovery of Internetware entity

PuWei Wang, Zhi Jin, HongYan Liu
2010 Science China Information Sciences  
In the process, capability description of Internetware entity plays an important role. This paper proposes a capability description of Internetware entity based on environment ontology.  ...  The environment ontology includes environment entities and possible interactions with the environment entities in a particular domain.  ...  Based on the capability description and domain environment ontology, transition graph of environment (called "transition graph" for short) under the effects of Internetware entity can be obtained.  ... 
doi:10.1007/s11432-010-0087-8 fatcat:b2bcmci26jgcpob7bpg72dbbxi


Chao Fu, Jihong Liu, Shude Wang
2021 IEEE Access  
based on this graph.  ...  System model graph is constructed by defining the SysML metamodel ontology and the construction strategy is given.  ...  to fuzzy search in the knowledge graph, and the entity names are matched by regular expressions.  ... 
doi:10.1109/access.2021.3115165 fatcat:gmasqubbzvhhfc5xuch62ko7xu

Towards a Parametric Ontology Modularization Framework Based on Graph Transformation

Mathieu d'Aquin, Paul Doran, Enrico Motta, Valentina A. M. Tamma
2007 International Conference on Knowledge Capture  
As most of the existing approaches rely on the traversal of the graph underlying the ontology to harvest relevant entities and axioms, the framework chosen is based on graph transformation.  ...  An abstract model for representing ontologies as attributed graphs is described, along with the reformulation of existing module extraction techniques as graph transformation rules.  ...  Ontologies as attributed graphs. Ontology representation languages are mostly based on the RDF model, that is itself based on graphs.  ... 
dblp:conf/kcap/dAquinDMT07 fatcat:urmogfintvaslcfeqclrogahvm

A Generalized Framework for Ontology-Based Information Retrieval Application to a public-transportation system [article]

Amir Zidi, Mourad Abed
2014 arXiv   pre-print
In order to achieve more scalability, we propose an approach for semantic indexing based on entity retrieval model.  ...  In this paper we present a generic framework for ontology-based information retrieval.  ...  The graph G represents datasets, entities and their relationships: We illustrate an example of an RDF graph extracted from our knowledge base.  ... 
arXiv:1409.0921v1 fatcat:ggshzpypkbhbvlt33owoyv23py

Type Prediction for Efficient Coreference Resolution in Heterogeneous Semantic Graphs

Jennifer Sleeman, Tim Finin
2013 2013 IEEE Seventh International Conference on Semantic Computing  
We describe an approach for performing entity type recognition in heterogeneous semantic graphs in order to reduce the computational cost of performing coreference resolution.  ...  This problem is similar to coreference resolution in unstructured text, where entities and their types are identified using contextual information and linguistic-based analysis.  ...  Instead, we develop dictionaries based on common ontologies and then map attributes associated with an instance with attributes found in the dictionary.  ... 
doi:10.1109/icsc.2013.22 dblp:conf/semco/SleemanF13 fatcat:zna7amykpzasdkqg5koq6cvyii

Querying Heterogeneous Spatial Databases: Combining an Ontology with Similarity Functions [chapter]

Mariella Gutiérrez, Andrea Rodríguez
2004 Lecture Notes in Computer Science  
This paper uses a knowledge-based approach to querying heterogeneous spatial databases based on an ontology and conceptual and attribute similarities.  ...  In addition, the specification of a query is done not only by identifying entity classes but also by considering constraints based on attribute values.  ...  Max Egenhofer for his contribution to previous works published in [12, 13] .  ... 
doi:10.1007/978-3-540-30466-1_15 fatcat:efzklcg6efcf7mirgujtzogoc4

Construction and Application of Knowledge Graph for Quality and Safety Supervision of Transportation Engineering

Sheng Huang, Chuanle Liu
2021 Journal on Artificial Intelligence  
We use the entity relation extraction method to extract the entity triples from the multi-sources heterogeneous data, and then employ knowledge inference to complete the edges in the constructed knowledge  ...  Knowledge graph technology play a more and more important role in various fields of industry and academia.  ...  entity concepts, attributes, and relationships between entities from various data sources to form ontology-based knowledge representation.  ... 
doi:10.32604/jai.2021.025175 fatcat:n4xrymlgdffexktbu7bkymptvi

Attack Analysis Framework for Cyber-Attack and Defense Test Platform

Yulu Qi, Rong Jiang, Yan Jia, Aiping Li
2020 Electronics  
This paper proposes an attack analysis framework for cyber-attack and defense test platforms, which stores prior knowledge in a cyber security knowledge graph and attack rule base as data that can be understood  ...  In 2012, Google first proposed the knowledge graph and applied it in the field of intelligent searching.  ...  The five-tuple model includes entities, attributes of entities, relationships between entities, and reasoning rules.  ... 
doi:10.3390/electronics9091413 fatcat:gz2mrlxznjcshitckhnsddxrb4

FCAMap-KG Results for OAEI 2019

Fei Chang, Guowei Chen, Songmao Zhang
2019 International Semantic Web Conference  
This year, we present a variant called FCAMap-KG, following the rationale of FCA-Map and designed for matching knowledge graphs.  ...  In OAEI 2016, we submitted the system FCA-Map for taking advantage of the Formal Concept Analysis (FCA) formalism in aligning large and complex biomedical ontologies.  ...  In general, FCAMap-KG is not restricted this way and can find cases when one entity is matched to multiple entities in another knowledge graph.  ... 
dblp:conf/semweb/ChangCZ19 fatcat:6l3oe6oyybd3vea6asi6ialct4

A Semi-supervised Learning Approach for Ontology Matching [chapter]

Zhichun Wang
2014 Communications in Computer and Information Science  
Ontology matching is the task of finding correspondences between semantically related entities in different ontologies, which is a key solution to the semantic heterogeneity problem.  ...  In this paper, we propose a semi-supervised learning approach for ontology matching.  ...  Given a source ontology O S , a target ontology O T , and a entity e i in O S , the procedure to find the semantically equivalent entity e j in O T is called ontology matching, denoted as M .  ... 
doi:10.1007/978-3-662-45495-4_2 fatcat:meip466qkbd6hi4cxsxh5k46xu

Ranking Ontologies Using Verified Entities to Facilitate Federated Queries

Neda Alipanah, Piyush Srivastava, Pallabi Parveen, Bhavani Thuraisingham
2010 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology  
Overlapping entities are determined by considering entities and relationships between them in ontology's graph.  ...  Since ontologies for a same domain usually overlap, we aim to rank ontologies based on the commonality of overlapping entities and distance between each pair of ontologies.  ...  We find out the CSE between two ontologies using the name similarity and the structural similarity of RDF graph with an efficient graph-based matching algorithm.  ... 
doi:10.1109/wi-iat.2010.147 dblp:conf/webi/AlipanahSPT10 fatcat:sbos4iit5nhc5pirxuu4wg5bjq

Research on the Construction Technology of Knowledge Graph in Aviation

Xue Wang, Xizhong Yang, Jiapan Fu, Xuyi Qiu
2020 IOP Conference Series: Materials Science and Engineering  
In order to alleviate the overload of airspace information under the network environment and integrate the scattered and useful airspace information, the technical architecture of knowledge graph in the  ...  Finally, an instance of knowledge graph for air combat is constructed.  ...  entity appellation to the corresponding entity in the knowledge base.  ... 
doi:10.1088/1757-899x/751/1/012040 fatcat:samlndmzsjcpblhk4rtceo7x2u

Measuring Relatedness and Augmentation of Information of Interest within Free Text Law Enforcement Documents

J. R. Johnson, A. Miller, L. Khan, B. Thuraisingham
2012 2012 European Intelligence and Security Informatics Conference  
Graph structures are generated initially from syntactic links and ontological class hierarchies, and augmented by inferred links resulting from triggered DL-Safe rules and abductive hypotheses.  ...  semantic content items and key entities such as events and temporal items.  ...  Edge 1 in graph 1 (E1:Event -> relatedness to edge 1 of graph 2 (E1 high match corresponding to the (1 due to the match of the attributes well as the match of the link funct relatedness matrix identifies  ... 
doi:10.1109/eisic.2012.49 dblp:conf/eisic/JohnsonMKT12 fatcat:zebugleblnabfdgezlghviwgyy

A Survey of Schema-Based Matching Approaches [chapter]

Pavel Shvaiko, Jérôme Euzenat
2005 Lecture Notes in Computer Science  
In this paper we present a new classification of schema-based matching techniques that builds on the top of state of the art in both schema and ontology matching.  ...  Schema and ontology matching is a critical problem in many application domains, such as semantic web, schema/ontology integration, data warehouses, e-commerce, etc.  ...  -Graph matching. There have been done a lot of work on graph (tree) matching in graph theory and also with respect to schema/ontology matching applications, see, for example, [65, 77] .  ... 
doi:10.1007/11603412_5 fatcat:givft2xinzaofbvtkmeoaubqbq
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