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Approximate Graph Schema Extraction for Semi-structured Data [chapter]

Qiu Yue Wang, Jeffrey Xu Yu, Kam-Fai Wong
2000 Lecture Notes in Computer Science  
Furthermore, an accurate graph schema is generally very large, hence impractical. In this paper, an approximation approach is proposed for graph schema extraction.  ...  Approximation is achieved by summarizing the semi-structured data graph using an incremental clustering method.  ...  Graph Schema For semi-structured data, the notion of a graph schema is formally introduced and studied in [5] .  ... 
doi:10.1007/3-540-46439-5_21 fatcat:7ksiel7vnzfftjdtb3hkqlm5y4

Schema Extraction on Semi-structured Data [article]

Panpan Li, Yikun Gong, Chen Wang
2021 arXiv   pre-print
With the continuous development of NoSQL databases, more and more developers choose to use semi-structured data for development and data management, which puts forward requirements for schema management  ...  of semi-structured data stored in NoSQL databases.  ...  For data, we focused on semi-structured data and the JSON format used to represent semi-structured data.  ... 
arXiv:2012.08105v2 fatcat:hco64wxnrfawrk3twlff2xia3i

Conceptual graphs as schemas for semi-structured databases

Yat Su, Kam Wong
2001 Proceedings Seventh International Conference on Database Systems for Advanced Applications DASFAA 2001 DASFAA-01  
Semi-structured data are usually represented in graph format, many graph schemas have then been proposed to extract schemas from those data graphs.  ...  As the World Wide Web grows dramatically in recent years, there is increasing interest in semi-structured data on the web.  ...  Introduction Accurate and approximate graph schemas have been proposed to extract schematic information from semistructured data, e.g., [1, 2, 3] .  ... 
doi:10.1109/dasfaa.2001.6044752 dblp:conf/dasfaa/SuW01 fatcat:uqnd2btogvhrtcamsddxty2jgq

Learning queries for relational, semi-structured, and graph databases

Radu Ciucanu
2013 Proceedings of the 2013 Sigmod/PODS Ph.D. symposium on PhD symposium - SIGMOD'13 PhD Symposium  
Web applications store their data within various database models, such as relational, semi-structured, and graph data models to name a few.  ...  We study learning algorithms for queries for the above mentioned models.  ...  The same query languages can be used to extract semi-structured data before shredding it into a graph database, based on RDF (scenario 3).  ... 
doi:10.1145/2483574.2483576 dblp:conf/sigmod/Ciucanu13 fatcat:vk47ezlnj5ceznht6utb44zs24

A novel method for measuring semantic similarity for XML schema matching

Buhwan Jeong, Daewon Lee, Hyunbo Cho, Jaewook Lee
2008 Expert systems with applications  
To this end, we present a supervised approach to measure semantic similarity between XML schema documents, and, more importantly, address a novel approach to augment reliably labeled training data from  ...  a given few labeled samples in a semi-supervised manner.  ...  Feature engineering: Read two XML schemas, extract features such as labels (e.g., schema or root element name) and structural data, and represent them in an internal format digestible by similarity computation  ... 
doi:10.1016/j.eswa.2007.01.025 fatcat:bjmh3wj75ncpvpeamydd7vl2qy

Comparative study of NoSQL databases for big data storage

Gourav Bathla, Rinkle Rani, Himanshu Aggarwal
2018 International Journal of Engineering & Technology  
Big data is a collection of large scale of structured, semi-structured and unstructured data.  ...  There are approximately 120 real solutions existing for these categories; most commonly used solutions are elaborated in Introduction section.  ...  Conclusion In this paper, techniques for Big data storage are highlighted. Several techniques and solutions are available for efficient storage of structured, semi-structured and unstructured data.  ... 
doi:10.14419/ijet.v7i2.6.10072 fatcat:mcy2ldvcnrczdhhkp7ld4akdpu

On Massive JSON Data Model and Schema

Teng Lv, Ping Yan, Weimin He
2019 Journal of Physics, Conference Series  
JSON (JavaScript Object Notation) is a lightweight semi-structured data format based on the data types of programming language JavaScript.  ...  It is a popular data exchange format over the World Wide Web and becomes a dominant standard format for sending API (Application Programming Interface) requests and responses in the past few years.  ...  In addition to the traditional structured data, a large number of semi-structured and unstructured data also show explosive growth, such as semi-structured data representation and exchange language XML  ... 
doi:10.1088/1742-6596/1302/2/022031 fatcat:qxtwvx2cjfh6vdu4s6htnbce3q

VizCurator

Bahar Ghadiri Bashardoost, Christina Christodoulakis, Soheil Hassas Yeganeh, Renée J. Miller, Kelly Lyons, Oktie Hassanzadeh
2015 Proceedings of the 24th International Conference on World Wide Web - WWW '15 Companion  
More importantly, VizCurator provides a rich set of tools for data curation.  ...  VizCurator permits the exploration, understanding and curation of open RDF data, its schema, and how it has been linked to other sources.  ...  VizCurator is useful for any RDF data source but especially for data that has been translated or extracted from another (structured or semi-structured) format where the data may not match its schema well  ... 
doi:10.1145/2740908.2742845 dblp:conf/www/BashardoostCYML15 fatcat:zfvzeolzqrh2dhpr6rhvzkeegq

Type Prediction for Efficient Coreference Resolution in Heterogeneous Semantic Graphs

Jennifer Sleeman, Tim Finin
2013 2013 IEEE Seventh International Conference on Semantic Computing  
Semantic graphs are semi-structured with very little contextual information and trivial grammars that do not convey additional information.  ...  We describe an approach for performing entity type recognition in heterogeneous semantic graphs in order to reduce the computational cost of performing coreference resolution.  ...  For example, there is no sentence structure,specifically in the semi-structured graph-based data.  ... 
doi:10.1109/icsc.2013.22 dblp:conf/semco/SleemanF13 fatcat:zna7amykpzasdkqg5koq6cvyii

Data lake concept and systems: a survey [article]

Rihan Hai, Christoph Quix, Matthias Jarke
2021 arXiv   pre-print
Although big data has been discussed for some years, it still has many research challenges, especially the variety of data.  ...  It poses a huge difficulty to efficiently integrate, access, and query the large volume of diverse data in information silos with the traditional 'schema-on-write' approaches such as data warehouses.  ...  The following work Constance [56] can also extract structural metadata, i.e., schemas from semi-structured files such as XML and JSON.  ... 
arXiv:2106.09592v1 fatcat:qqwgp52s6vdhhjvx6y24pvj6jm

Extracting XML schema from multiple implicit xml documents based on inductive reasoning

Masaya Eki, Tadachika Ozono, Toramatsu Shintani
2008 Proceeding of the 17th international conference on World Wide Web - WWW '08  
The goal of this work is to type a large collection of XML approximately but efficiently. This can also process XML code written in a different schema or even code which is schema-less.  ...  We evaluate similarity of data type and data range by using an ontology dictionary, and XML Schema is made from results of second and last step.  ...  [4] proposed an approach to extract schema from semi-structured data. Our research is mainly based on that study. Constraint logic Copyright is held by the author/owner(s).  ... 
doi:10.1145/1367497.1367735 dblp:conf/www/EkiOS08 fatcat:kythyi765bf7loeuypk4cjouy4

Graph transformation to infer schemata from XML documents

Luciano Baresi, Elisa Quintarelli
2005 Proceedings of the 2005 ACM symposium on Applied computing - SAC '05  
Semi-structured data are characterized by the lack of a predefined schema.  ...  The paper adopts XML as the language to render semi-structured data and proposes an approach -based on graph transformation techniques -to infer the schemata of XML documents.  ...  Among them, the database community concentrated on XML to represent and exchange semi-structured data, that is, data with no absolute and fixed schema and with a possibly irregular and incomplete structure  ... 
doi:10.1145/1066677.1066824 dblp:conf/sac/BaresiQ05 fatcat:pwjpstgshjantjc6wz6ldh54nq

Graph Neural Network based Agent in Google Research Football [article]

Yizhan Niu, Jinglong Liu, Yuhao Shi, Jiren Zhu
2022 arXiv   pre-print
The GNN transforms the input data into a graph which better represents the football players' locations so that it extracts more information of the interactions between different players.  ...  Deep neural networks (DNN) can approximate value functions or policies for reinforcement learning, which makes the reinforcement learning algorithms more powerful.  ...  In other domains such as learning from non-structural data like texts and images, reasoning on extracted structures, like the dependency tree of sentences and the scene graph of images, was an important  ... 
arXiv:2204.11142v1 fatcat:ufoqf5u5qzgg7dj2q37r4x7qli

Large Scale Graph Matching(LSGM): Techniques, Tools, Applications and Challenges

Azka Mahmood, Hina Farooq, Javed Ferzund
2017 International Journal of Advanced Computer Science and Applications  
Semantic Matching (conceptual), Syntactic Matching (structural) and Schematic Matching (Schema based).  ...  rather than focusing on structural details of graphs.  ...  Data models (Relational model for structured data and XML model for semi-structured/Unstructured data) are discussed in which input data could be available for matching problems and it have to be transformed  ... 
doi:10.14569/ijacsa.2017.080465 fatcat:i4wunwwhu5d43pfj7roloojwmm

Automatic Bootstrapping of GraphQL Endpoints for RDF Triple Stores

Lars Christoph Gleim, Tim Holzheim, István Koren, Stefan Josef Decker
2020 CEUR Workshop Proceedings  
GraphQL is a query language for graph-structured Web APIs, increasingly popular among Web developers and recently explored as an alternative query language for Linked Data and its underlying RDF data model  ...  extraction, mapping and query translation approach.  ...  extraction for data structure visualization.  ... 
doi:10.18154/rwth-conv-242785 fatcat:ig7ssod575g4rmlkzbb6zxtiyu
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